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init

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  1. .gitattributes +1 -0
  2. ARIMAMetrics/ARIMA-DAILY.csv +103 -0
  3. ARIMAMetrics/ARIMA-MONTHLY.csv +161 -0
  4. ARIMAMetrics/ARIMA-QUARTERLY.csv +78 -0
  5. ARIMAMetrics/ARIMA-WEEKLY.csv +49 -0
  6. Explore/PREDICTIONS/Daily/50.csv +0 -0
  7. Explore/PREDICTIONS/Daily/60.csv +0 -0
  8. Explore/PREDICTIONS/Daily/80.csv +0 -0
  9. Explore/PREDICTIONS/Monthly/50.csv +78 -0
  10. Explore/PREDICTIONS/Monthly/60.csv +63 -0
  11. Explore/PREDICTIONS/Monthly/80.csv +32 -0
  12. Explore/PREDICTIONS/Quarterly/50.csv +27 -0
  13. Explore/PREDICTIONS/Quarterly/60.csv +22 -0
  14. Explore/PREDICTIONS/Quarterly/80.csv +12 -0
  15. Explore/PREDICTIONS/Weekly/50.csv +390 -0
  16. Explore/PREDICTIONS/Weekly/60.csv +313 -0
  17. Explore/PREDICTIONS/Weekly/80.csv +157 -0
  18. LSTM.csv +13 -0
  19. Slider.jpg +0 -0
  20. StandardDeviation.csv +17 -0
  21. assets/images/Accuracy.png +0 -0
  22. assets/images/Checkbox_Details.gif +3 -0
  23. assets/images/Conceptual Framework.png +0 -0
  24. assets/images/Download_CSV.gif +3 -0
  25. assets/images/Select1.gif +3 -0
  26. assets/images/Set_pdq_values.gif +3 -0
  27. assets/images/Slider1.gif +3 -0
  28. assets/images/Split1.gif +3 -0
  29. assets/images/make.png +0 -0
  30. assets/images/pdq.gif +3 -0
  31. bak.py +291 -0
  32. bestDaily.csv +1851 -0
  33. bestMonthly.csv +63 -0
  34. bestQuarterly.csv +27 -0
  35. bestWeekly.csv +390 -0
  36. pages/1_πŸ”Ž_About.py +155 -0
  37. pages/2_πŸ“ˆ_Explore.py +78 -0
  38. pages/3_πŸ“Š_Make_a_Model.py +249 -0
  39. requirements.txt +20 -0
  40. 🏠_Home.py +231 -0
.gitattributes CHANGED
@@ -29,3 +29,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ *.gif filter=lfs diff=lfs merge=lfs -text
ARIMAMetrics/ARIMA-DAILY.csv ADDED
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ARIMAMetrics/ARIMA-MONTHLY.csv ADDED
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ARIMAMetrics/ARIMA-QUARTERLY.csv ADDED
@@ -0,0 +1,78 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ,Train Split,Order,MSE,MAPE,Time(s),Mean
2
+ 0,0.800,"(0, 0, 0)",843.235,0.529,0.831,-9.036
3
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4
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5
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6
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7
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8
+ 6,0.800,"(0, 2, 1)",354.008,0.334,1.067,5.579
9
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12
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13
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14
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15
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16
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17
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18
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19
+ 17,0.800,"(2, 1, 1)",659.589,0.476,1.885,8.157
20
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21
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22
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23
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24
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26
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27
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29
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30
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31
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41
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42
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49
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50
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51
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53
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54
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55
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56
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57
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58
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61
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62
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63
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64
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65
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66
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67
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68
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72
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74
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77
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78
+ 76,0.600,"(3, 2, 1)",418.636,0.351,4.314,4.266
ARIMAMetrics/ARIMA-WEEKLY.csv ADDED
@@ -0,0 +1,49 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ,Train Split,Order,MSE,MAPE,Time(s),Mean
2
+ 0,0.800,"(0, 0, 0)",709.989,0.447,1.891,-12.240
3
+ 1,0.800,"(0, 0, 1)",205.758,0.238,9.981,-6.327
4
+ 2,0.800,"(0, 1, 0)",15.261,0.047,2.205,0.348
5
+ 3,0.800,"(0, 1, 1)",15.357,0.047,4.826,0.331
6
+ 4,0.800,"(0, 2, 0)",31.837,0.063,2.096,0.028
7
+ 5,0.800,"(0, 2, 1)",15.656,0.047,25.837,0.435
8
+ 6,0.800,"(1, 0, 0)",15.274,0.047,8.413,0.250
9
+ 7,0.800,"(1, 0, 1)",15.370,0.047,50.321,0.228
10
+ 8,0.800,"(1, 1, 0)",15.369,0.047,4.992,0.329
11
+ 9,0.800,"(1, 2, 0)",24.229,0.056,4.978,0.018
12
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13
+ 11,0.800,"(2, 0, 0)",15.383,0.047,14.201,0.224
14
+ 12,0.800,"(2, 0, 1)",15.372,0.046,70.868,0.067
15
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16
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17
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18
+ 16,0.500,"(0, 0, 0)",895.077,0.521,3.451,-22.002
19
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20
+ 18,0.500,"(0, 1, 0)",9.370,0.039,4.145,0.204
21
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22
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23
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24
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25
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26
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27
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28
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29
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30
+ 28,0.500,"(2, 0, 1)",9.574,0.039,150.865,-0.204
31
+ 29,0.500,"(2, 1, 0)",9.505,0.039,16.389,0.186
32
+ 30,0.500,"(2, 1, 1)",9.582,0.038,118.038,0.157
33
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34
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35
+ 33,0.600,"(0, 0, 1)",189.009,0.224,19.267,-8.881
36
+ 34,0.600,"(0, 1, 0)",10.336,0.038,3.311,0.243
37
+ 35,0.600,"(0, 1, 1)",10.367,0.038,8.114,0.234
38
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39
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40
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41
+ 39,0.600,"(1, 0, 1)",10.337,0.038,93.371,0.089
42
+ 40,0.600,"(1, 1, 0)",10.372,0.038,8.889,0.232
43
+ 41,0.600,"(1, 2, 0)",16.262,0.047,8.210,0.007
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45
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46
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47
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+ 46,0.600,"(2, 1, 1)",10.492,0.038,107.466,0.165
49
+ 47,0.600,"(2, 2, 0)",13.136,0.043,11.696,-0.003
Explore/PREDICTIONS/Daily/50.csv ADDED
The diff for this file is too large to render. See raw diff
Explore/PREDICTIONS/Daily/60.csv ADDED
The diff for this file is too large to render. See raw diff
Explore/PREDICTIONS/Daily/80.csv ADDED
The diff for this file is too large to render. See raw diff
Explore/PREDICTIONS/Monthly/50.csv ADDED
@@ -0,0 +1,78 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ,Date,Close Prices,"ARIMA_50.0_(0, 0, 0)_Predictions","ARIMA_50.0_(0, 0, 1)_Predictions","ARIMA_50.0_(0, 1, 0)_Predictions","ARIMA_50.0_(0, 1, 1)_Predictions","ARIMA_50.0_(0, 2, 0)_Predictions","ARIMA_50.0_(0, 2, 1)_Predictions","ARIMA_50.0_(1, 0, 0)_Predictions","ARIMA_50.0_(1, 0, 1)_Predictions","ARIMA_50.0_(1, 1, 0)_Predictions","ARIMA_50.0_(1, 1, 1)_Predictions","ARIMA_50.0_(1, 2, 0)_Predictions","ARIMA_50.0_(1, 2, 1)_Predictions","ARIMA_50.0_(2, 0, 0)_Predictions","ARIMA_50.0_(2, 0, 1)_Predictions","ARIMA_50.0_(2, 1, 0)_Predictions","ARIMA_50.0_(2, 1, 1)_Predictions","ARIMA_50.0_(2, 2, 0)_Predictions","ARIMA_50.0_(2, 2, 1)_Predictions","ARIMA_50.0_(3, 0, 0)_Predictions","ARIMA_50.0_(3, 0, 1)_Predictions","ARIMA_50.0_(3, 1, 0)_Predictions","ARIMA_50.0_(3, 1, 1)_Predictions","ARIMA_50.0_(3, 2, 0)_Predictions","ARIMA_50.0_(3, 2, 1)_Predictions","ARIMA_50.0_(4, 0, 0)_Predictions","ARIMA_50.0_(4, 1, 0)_Predictions","ARIMA_50.0_(4, 1, 1)_Predictions","ARIMA_50.0_(4, 2, 0)_Predictions","ARIMA_50.0_(4, 2, 1)_Predictions","ARIMA_50.0_(5, 0, 0)_Predictions","ARIMA_50.0_(5, 0, 1)_Predictions","ARIMA_50.0_(5, 1, 0)_Predictions","ARIMA_50.0_(5, 1, 1)_Predictions","ARIMA_50.0_(5, 2, 0)_Predictions","ARIMA_50.0_(5, 2, 1)_Predictions","ARIMA_50.0_(6, 0, 0)_Predictions","ARIMA_50.0_(6, 0, 1)_Predictions","ARIMA_50.0_(6, 1, 0)_Predictions","ARIMA_50.0_(6, 1, 1)_Predictions","ARIMA_50.0_(6, 2, 0)_Predictions","ARIMA_50.0_(6, 2, 1)_Predictions","ARIMA_50.0_(7, 0, 0)_Predictions","ARIMA_50.0_(7, 0, 1)_Predictions","ARIMA_50.0_(7, 1, 0)_Predictions","ARIMA_50.0_(7, 1, 1)_Predictions","ARIMA_50.0_(7, 2, 0)_Predictions","ARIMA_50.0_(7, 2, 1)_Predictions","ARIMA_50.0_(8, 0, 0)_Predictions","ARIMA_50.0_(8, 0, 1)_Predictions","ARIMA_50.0_(8, 1, 0)_Predictions","ARIMA_50.0_(8, 1, 1)_Predictions","ARIMA_50.0_(8, 2, 0)_Predictions","ARIMA_50.0_(8, 2, 1)_Predictions",LSTM_50.0_MONTHLY
2
+ 0,01/12/2014,57.33,95.56,79.06,70.12,65.65,54.14,68.32,71.89,67.83,65.12,65.33,56.3,63.52,66.93,66.7,65.25,64.94,57,63.6,66.82,66.85,64.93,65.15,57.4,63.17,66.19,64.98,66.59,57.54,63.32,66.08,66.16,66.03,66.02,59.26,64.35,66.62,66.62,66.02,66.02,59.83,64.3,66.58,66.43,66.1,66.01,60.2,64.32,66.51,66.57,66.25,68.08,61.8,61.81,
3
+ 1,01/01/2015,52.99,95.06,76.63,57.13,54.37,44.25,47.89,59.67,57.71,52.82,53.36,43.18,51.04,56.05,55.31,53.1,53.09,44.91,51.17,55.62,56.26,52.85,53.28,45.01,50.86,55.4,53.99,55.18,45.52,52,55.79,55.5,54.26,54.19,45.98,52.29,55.73,55.55,54.2,54.19,47.21,52.09,55.41,55.26,54.22,54.31,47.69,52.09,55.4,55.35,54.35,56.1,48.3,48.21,
4
+ 2,01/04/2015,66.78,94.52,74.4,52.73,52.27,48.51,50.22,55.35,55.68,51.36,51.79,45.66,49.56,55.33,54.55,51.62,51.14,43.84,49.74,54.95,55.16,50.94,51.37,43.98,48.96,53.82,51.71,53.21,44.1,49.73,53.96,53.76,52.86,52.84,45.87,50.82,54.44,54.5,52.84,52.85,45.87,50.78,54.43,54.17,52.95,52.71,46.76,50.77,54.25,54.43,52.99,54.66,47.37,47.36,
5
+ 3,01/05/2015,65.56,94.17,87.64,66.7,71.69,80.66,64.57,68.58,74.25,71.33,71.82,75.2,70.04,75.35,74.98,71.83,71.33,71.08,70.41,75.19,75.36,71.6,71.83,70.28,70.13,74.35,73.95,75.34,70.4,72.31,75.34,74.38,74.27,74.24,70.31,72.55,75.33,75.23,74.25,74.23,70.56,72.49,75.19,75.06,74.32,76.26,69.88,72.54,75.18,75.2,74.55,76.33,70.5,70.51,
6
+ 4,01/06/2015,63.59,93.81,74.97,65.47,63.54,64.24,63.54,67.38,65.68,65.14,63.96,69.06,63.81,67.93,69.26,64.45,65.14,64.94,63.1,68.77,67.92,64.14,64.44,64.09,62.82,68.26,65.91,68.63,63.11,64.41,68.76,68.23,68.55,68.51,63.68,66.87,70.18,70.2,68.52,68.52,63.81,66.81,70.1,69.96,68.64,70.71,64.24,66.89,70.07,70.15,68.67,70.74,63.55,63.55,
7
+ 5,01/07/2015,52.21,93.44,83.74,63.48,63.5,61.51,61.53,65.45,66.14,62.91,63.23,61.7,61.51,65.75,66.07,62.93,62.92,66.31,61.48,65.83,65.79,63.43,62.93,65.39,62.05,68.31,64.93,67.99,64.5,63.32,68.58,68.34,66.82,66.55,61.15,65.01,69.33,68.92,66.61,66.57,61.55,64.68,68.58,68.42,66.69,66.72,61.59,64.73,68.56,68.86,66.77,68.62,62.11,62.11,
8
+ 6,01/08/2015,54.15,92.94,66.11,51.96,48.34,40.61,49.75,54.48,51.35,48.41,48.28,43.47,46.74,51.6,51.78,48.32,48.41,44.44,46.64,51.71,51.6,48.32,48.3,46.24,46.64,51.95,46.22,47.61,45.09,44.31,50.7,51.94,47.88,47.52,42.2,45.82,51.2,51.1,47.19,47.31,40.65,45.14,50.3,49.65,47.5,47.5,41.31,45.33,50.05,49.93,47.51,47.46,41.77,41.78,
9
+ 7,01/09/2015,48.37,92.47,82.4,53.92,55.69,56.03,51.69,56.27,58.9,54.62,55.25,51.65,53.01,58.3,58.05,55.17,54.63,53.09,53.45,58.13,58.31,55.18,55.18,53.16,53.47,58.56,55.3,55.92,54.64,53.47,58.42,58.58,52.73,52.4,51.28,50.48,56.46,56.01,52.34,52.4,49.45,50.16,55.92,55.18,52.85,52.88,47.39,50.6,55.8,55.91,52.97,52.81,47.58,47.58,
10
+ 8,01/10/2015,49.56,91.94,63.31,48.08,45.92,42.44,45.79,50.56,48.84,46.41,46.23,44.93,44.75,49.83,50.19,46.28,46.4,41.94,44.59,50.14,50.01,46.29,46.27,42.68,44.57,49.64,46.02,46.04,42.75,44.21,49.3,49.68,46.35,47.16,47.64,44.33,49.04,50.1,47.05,47.19,45.96,45,51,48.5,47.34,47.34,43.93,45.28,50.87,50.89,47.29,47.1,41.24,41.25,
11
+ 9,01/12/2015,37.28,91.44,80.07,49.28,50.35,50.69,47.02,51.63,53.44,49.76,49.95,48.3,48.12,53.34,53.3,49.93,49.76,49.71,48.24,53.28,53.38,49.89,49.99,48.15,48.2,53.83,51.31,51.4,48.53,49.46,54.26,53.99,50.82,50.47,48.62,48.76,53.45,53.05,50.74,50.51,50.97,48.76,53.6,54.15,50.25,50.25,49.02,48.11,54.12,54.13,50.26,50.13,46.11,45.95,
12
+ 10,01/01/2016,34.74,90.81,55.35,36.86,33.21,24.78,34.38,39.47,36.26,33.31,33.23,29.33,31.49,36.64,37.09,33.23,34.23,28.67,31.39,37.04,36.6,33.34,33.22,29.89,31.48,36.98,32.98,33.85,29.23,31.04,36.72,37.17,35.49,35.71,30.99,33.4,38.08,38.63,35.51,35.72,31.37,33.48,38.4,38.5,35.56,35.65,34.72,33.45,38.31,38.45,35.92,35.98,32.53,32.13,
13
+ 11,01/02/2016,35.97,90.17,73.48,34.3,34.72,32.09,31.69,36.82,38.08,33.7,33.85,28.59,31.76,37.44,37.19,33.86,32.52,31.11,31.89,37.18,37.46,33.76,33.87,30.49,31.75,37.56,34.29,34.82,30.89,32.19,37.61,37.6,33.5,32.46,27.68,31.12,36.39,35.39,32.72,32.47,28.24,30.43,35.42,35.27,32.68,32.67,28.74,30.32,35.3,35.27,32.65,32.75,32.79,32.54,
14
+ 12,01/03/2016,39.6,89.55,58.59,35.55,35.91,37.14,33.01,37.95,38.87,36.06,36.09,35.8,34.22,39.75,39.83,36.11,36.89,32.94,34.24,39.85,41,36.3,36.09,34.18,34.41,39.61,35.83,36.28,33.9,33.83,39.3,39.56,36.94,37.6,35.9,34.71,39.57,40.57,37.19,37.61,34.37,34.99,40.35,40.67,38.15,38.16,35.21,35.89,40.69,40.76,38.17,38.22,35.56,35.83,
15
+ 13,01/04/2016,48.13,88.99,73.57,39.22,40.27,43.2,36.86,41.47,43.07,40.44,40.43,42.34,38.75,43.93,44.16,40.43,39.62,41.21,38.7,44.13,43.04,40.49,40.44,39.32,38.72,44.22,41.4,41.73,39.72,39.52,44.43,44.27,40.34,39.72,38.27,38.14,43.08,42.42,40.06,39.71,38.91,37.95,42.87,42.58,39.71,39.64,36.27,37.45,42.61,42.51,39.42,39.17,37,37.06,
16
+ 14,01/06/2016,49.68,88.54,67.45,47.85,50.09,56.68,45.79,49.82,52.5,50.55,50.53,55,49.16,53.75,54.05,50.52,51.09,54.02,49.1,53.99,54.57,50.5,50.52,53.17,49.03,54.18,50.7,51.49,52.35,49.07,54.1,54.1,52.54,53.1,54.19,50.62,54.98,55.86,52.85,53.11,53.29,50.99,55.89,55.99,53.24,53.24,54.14,51.27,55.94,55.99,53.23,53.27,50.21,50.22,
17
+ 15,01/07/2016,42.46,88.11,73.46,49.42,49.32,51.17,47.55,51.28,51.46,49.99,49.85,53.54,48.69,52.62,53.15,49.82,49.71,52.94,48.52,53.06,52.35,49.78,49.15,52.54,48.43,53.25,49.7,50.3,52.17,48.17,53.06,53.29,50.08,49.4,48.8,48.22,52.82,52.16,49.67,49.41,49.73,47.88,52.24,52.07,49.21,49.22,48.52,47.28,52.04,52.01,49.24,49.11,49.91,49.42,
18
+ 16,01/08/2016,47.04,87.62,61.75,42.13,40.18,35.09,40.16,44.18,42.58,40.08,39.99,37.96,38.61,42.63,42.77,39.96,40.56,40.43,38.47,42.75,43.22,39.71,39.95,40.45,38.16,43.02,39.59,39.94,40.37,37.88,42.77,44.06,39.56,39.67,39.05,37.51,42.24,42.57,39.37,39.65,37.91,37.43,42.21,42.46,40.09,40.09,39.36,38.07,42.47,42.54,40.1,40.21,37.8,38.04,
19
+ 17,01/09/2016,49.06,87.18,75.02,46.76,48.68,51.6,44.87,48.62,51.01,48.2,48.41,47.51,46.84,50.93,50.8,48.42,47.46,48.75,46.99,50.81,50.15,48.34,48.42,49.88,46.9,51.03,47.53,47.39,49.83,45.96,50.53,50.56,47.19,47.24,49.37,45.26,49.83,49.87,47.26,47.21,48.72,45.42,50.25,50.19,47.59,47.56,46.67,45.6,50.27,50.22,47.49,47.36,48.23,47.86,
20
+ 18,01/10/2016,48.3,86.77,65.12,48.81,48.92,51.03,47.06,50.55,50.91,49.49,49.36,51.87,48.25,51.91,52.09,49.37,50.37,49.06,48.13,52.07,52.85,49.52,49.37,49.72,48.23,51.91,49.11,48.37,50.28,47.73,51.59,52.66,47.69,47.86,50.12,45.98,50.16,50.36,47.82,47.85,49.98,46.2,50.64,50.55,47.69,47.68,48.8,45.88,50.44,50.43,47.66,47.52,46.02,46.26,
21
+ 19,01/11/2016,50.47,86.37,72.41,48.04,47.88,47.46,46.34,49.77,49.91,47.91,47.86,48.37,46.67,50.19,50.31,47.84,47.11,49.27,46.59,50.28,49.57,47.77,47.86,47.8,46.51,50.52,48.54,47.99,48.14,47.16,50.79,49.68,47.82,48.33,50.14,46.21,49.92,50.42,48.23,48.29,50.15,46.7,50.85,50.77,48.01,48.02,49.89,46.3,50.6,50.62,48.03,48,48.34,47.81,
22
+ 20,01/12/2016,56.13,86,67.6,50.24,50.97,52.59,48.62,51.85,52.87,50.96,50.99,51.56,49.8,53.17,53.2,50.99,51.44,52.02,49.81,53.19,53.73,50.95,50.97,52.43,49.77,53.35,50.52,50.53,51.68,49.25,53,54.35,51.84,51.97,52.89,50.34,53.73,53.95,52.1,51.97,53.56,50.69,54.3,54.07,51.41,51.41,53.56,49.84,53.83,53.83,51.43,51.49,53.19,52.76,
23
+ 21,01/02/2017,55.59,85.69,76.11,55.96,57.42,61.78,54.52,57.31,59.01,57.7,57.67,60.57,56.73,59.67,59.74,57.67,61.93,59.51,56.69,59.72,59.17,57.68,57.05,59.59,56.69,59.76,57.42,56.99,59.75,56.35,59.54,59.08,56.59,56.08,56.91,55.28,58.61,58.12,56.21,56.08,57.25,54.94,58.14,58.02,55.85,55.88,58.39,54.49,57.88,57.92,55.95,56.15,58.23,58.07,
24
+ 22,01/03/2017,52.83,85.38,68.16,55.41,54.91,54.98,54.06,56.77,56.44,55.33,55.16,57.06,54.34,57.07,57.24,55.16,56.16,56.7,54.2,57.21,57.82,55.15,55.73,56.29,54.18,57.31,55.23,54.82,56.37,54.18,57.25,58.01,54.79,55.33,57.08,53.53,56.63,57.23,55.06,55.33,56.14,53.89,57.22,57.42,55.58,55.6,56.77,54.3,57.43,57.48,55.64,55.83,58.38,58.34,
25
+ 23,01/04/2017,51.73,85.05,72.22,52.63,52.05,49.97,51.25,54.07,53.73,51.9,51.9,50.68,50.85,53.69,53.72,51.88,51.06,52.5,50.82,53.71,53.16,51.81,51.21,52.45,50.77,53.97,51.74,51.54,52.31,50.63,53.83,53.54,51.93,51.87,52.67,50.63,53.71,53.65,52.05,51.87,53.05,50.83,54.02,53.81,51.69,51.68,51.47,50.39,53.76,53.71,51.63,51.59,52.37,52.77,
26
+ 24,01/05/2017,50.31,84.72,67.47,51.52,51.44,50.55,50.12,52.98,53.13,51.28,51.34,49.94,50.23,53.14,53.13,51.34,52.06,50.37,50.27,53.13,53.64,51.34,51.93,51.33,50.26,53.2,50.77,50.44,51.32,49.66,52.8,53.93,50.65,50.61,50.74,49.36,52.43,52.46,50.6,50.61,50.9,49.36,52.47,52.43,50.44,50.45,51.55,49.13,52.31,52.34,50.48,50.53,49.47,49.75,
27
+ 25,01/06/2017,47.92,84.38,69.96,50.09,49.78,48.81,48.68,51.57,51.49,49.76,49.76,48.87,48.71,51.64,51.65,49.77,48.97,48.46,48.7,51.65,51.27,49.79,49.34,48.67,48.71,51.64,49.74,49.15,49.12,48.61,51.52,51.14,48.72,48.78,49.07,47.44,50.45,50.51,48.76,48.78,48.88,47.54,50.63,50.63,48.83,48.83,49.14,47.54,50.6,50.62,48.85,48.92,50,49.65,
28
+ 26,01/07/2017,52.65,84.02,65.39,47.67,47.16,45.44,46.25,49.22,48.94,47.06,47.08,45.72,45.99,48.99,49.01,47.08,47.82,45.88,45.98,49.01,49.42,47.08,47.5,45.68,45.98,49.05,47.29,46.94,45.79,46.13,49.07,49.48,47.23,47.59,47.6,45.94,48.79,49.19,47.54,47.58,47.62,46.33,49.37,49.34,47.48,47.48,47.32,46.21,49.27,49.27,47.48,47.49,47.69,47.82,
29
+ 27,01/08/2017,52.38,83.72,72.98,52.45,54.01,57.36,51.13,53.8,55.61,53.91,54.01,54.92,52.99,55.79,55.76,54.01,53.16,54.54,53.05,55.77,55.01,54.01,53.59,54.36,53.05,55.81,54.05,53.9,54.21,53.03,55.74,55.44,54.34,54.31,54.51,53.18,55.77,55.76,54.43,54.31,55.01,53.33,55.99,55.83,54.04,54.04,54.93,52.9,55.71,55.71,54.05,54.07,54.29,54.34,
30
+ 28,01/09/2017,57.54,83.41,66,52.18,51.74,52.04,50.93,53.52,53.22,52.18,52.02,53.72,51.27,53.87,53.97,52.03,53.04,52.29,51.13,53.96,54.75,52.07,52.57,52.18,51.15,53.91,52.09,52.03,52.11,51.11,53.82,54.31,52.19,52.07,51.52,51.08,53.69,53.63,52.08,52.07,51.69,51,53.63,53.6,51.96,51.97,52.55,50.85,53.5,53.53,52,52.11,52.57,52.47,
31
+ 29,01/11/2017,63.57,83.17,76.05,57.39,59.01,62.69,56.27,58.5,60.33,58.95,59,60.79,58.19,60.51,60.51,58.99,58.15,61.62,58.2,60.51,59.67,58.91,58.15,60.69,58.15,60.69,59.24,59.22,60.6,58.39,60.8,60.21,59.18,59.27,60.2,58.19,60.56,60.68,59.21,59.27,59.83,58.27,60.68,60.72,59.36,59.37,59.98,58.36,60.73,60.74,59.39,59.48,60.85,60.78,
32
+ 30,01/12/2017,66.6,82.98,72.45,63.48,64.77,69.6,62.55,64.31,65.7,65.3,65.2,69.28,64.71,66.52,66.61,65.2,66.29,67.8,64.64,66.6,67.24,65.22,65.88,68.14,64.64,66.59,64.68,64.66,67.7,64.07,66.21,67.29,65.21,65.29,67.27,64.43,66.46,66.58,65.3,65.29,67.04,64.58,66.66,66.63,65.29,65.28,66.34,64.51,66.61,66.6,65.27,65.29,66.39,66.51,
33
+ 31,01/01/2018,69.05,82.83,77.91,66.54,67.07,69.6,65.75,67.22,67.84,67.47,67.35,70.6,66.94,68.41,68.53,67.34,66.66,70.65,66.84,68.51,67.57,67.3,66.6,69.95,66.82,68.66,67.42,67.09,70.13,66.88,68.67,68.03,66.46,66.25,68.27,65.79,67.74,67.51,66.31,66.25,68.16,65.67,67.58,67.52,66.2,66.21,67.74,65.52,67.48,67.48,66.21,66.22,66.78,66.84,
34
+ 32,01/02/2018,65.78,82.7,75.22,69.02,69.58,71.46,68.31,69.56,70.22,69.77,69.72,71.63,69.28,70.53,70.6,69.71,70.66,72.47,69.24,70.59,71.43,69.66,70.18,72.55,69.23,70.78,69.29,69.03,72.24,68.83,70.51,71.53,69.49,70,72.98,68.89,70.54,71.09,69.84,70,72.32,69.34,71.12,71.22,70.04,70.05,72.1,69.47,71.2,71.22,70.07,70.11,71.5,71.29,
35
+ 33,01/03/2018,70.27,82.55,74.57,65.72,64.65,62.42,64.99,66.42,65.43,64.79,64.71,64.33,64.19,65.6,65.67,64.7,63.96,64.98,64.13,65.66,65.27,64.67,64.24,65.64,64.11,65.74,64.13,63.66,65.75,63.58,65.36,65.37,63.56,63.25,64.58,62.91,64.75,64.41,63.47,63.25,65.09,62.84,64.67,64.46,63.02,63.01,64.05,62.39,64.37,64.34,62.98,62.95,64,63.93,
36
+ 34,01/05/2018,77.59,82.44,78.8,70.25,71.82,74.74,69.59,70.72,72.42,71.58,71.68,72.03,71.14,72.31,72.24,71.67,71.74,72.84,71.19,72.24,72.45,71.63,71.93,72.97,71.18,72.36,71.4,70.67,73.26,70.94,72.19,72.78,70.41,70.8,73.55,69.88,71.3,71.71,70.64,70.8,72.94,70.18,71.69,71.79,70.77,70.78,73.61,70.26,71.74,71.78,70.82,70.95,71.98,71.88,
37
+ 35,01/06/2018,79.44,82.39,81.38,77.63,79.27,84.92,77.16,77.74,79.39,79.81,79.73,83.94,79.56,80.15,80.2,79.74,79.16,81.66,79.52,80.19,79.49,79.77,79.62,81.9,79.51,80.06,79.42,78.7,81.92,79.17,79.85,79.86,78.94,79.26,82.93,78.65,79.43,79.67,79.36,79.27,82.92,79.17,80.06,79.94,79.09,79.08,81.89,78.89,79.9,79.87,79.07,79.13,82.58,82.17,
38
+ 36,01/08/2018,77.42,82.37,80.73,79.5,79.56,81.25,79.13,79.51,79.57,80.05,79.87,83.09,79.79,80.14,80.26,79.87,80.84,82.84,79.67,80.23,80.93,79.85,79.91,81.77,79.68,80.33,80.23,79.72,81.92,80.02,80.54,80.35,79.62,79.7,82.01,79.38,80.02,80.06,79.8,79.7,82.5,79.61,80.28,80.14,79.31,79.33,82.53,79.16,80.01,80.01,79.39,79.48,81.29,81.4,
39
+ 37,01/09/2018,82.72,82.32,79.52,77.46,76.86,75.32,77.08,77.57,77.02,76.87,76.82,76.59,76.53,76.99,77.03,76.8,76.11,78.39,76.48,77.02,76.82,76.74,76.56,78.47,76.48,77.24,76.52,76.38,77.98,76.27,77.1,77.34,77.24,77.44,78.59,76.92,77.63,77.84,77.43,77.44,78.76,77.15,77.92,77.89,77.21,77.24,79.65,76.94,77.78,77.81,77.32,77.52,79.89,79.71,
40
+ 38,01/10/2018,75.47,82.33,85.05,82.81,84.47,88.01,82.51,82.64,84.35,84.35,84.45,85.49,84.18,84.32,84.27,84.44,84.42,85.87,84.24,84.28,84.36,84.44,84.57,86.62,84.26,84.37,83.84,83.38,86.62,83.71,84.05,84.58,83.35,83.05,84.73,83.19,83.63,83.31,83.15,83.05,84.85,82.96,83.34,83.26,82.94,82.96,85.03,82.78,83.22,83.23,83.02,83.23,85.98,85.97,
41
+ 39,01/11/2018,58.71,82.27,74.14,75.49,73.04,68.1,75.12,75.71,73.24,73.43,73.27,72.43,73.01,73.54,73.7,73.27,73.56,71.6,72.92,73.68,73.72,73.29,73.29,72.17,72.91,73.57,73.03,72.39,72.63,72.68,73.4,73.48,72,72.24,72.83,71.67,72.52,72.72,72.12,72.24,72.41,71.8,72.7,72.8,72.32,72.33,72.79,71.98,72.8,72.83,72.36,72.49,73.43,73.76,
42
+ 40,01/12/2018,52.28,82.06,68.96,58.59,54.42,41.75,57.86,59.65,55.66,53.58,53.74,44.82,52.74,54.5,54.5,53.68,54.04,49.08,52.83,54.5,54.4,53.71,53.46,49.13,52.91,54.84,54.11,53.79,49.47,53.31,55.04,54.7,53.85,53.97,51.48,53.08,54.72,54.81,54.05,53.97,52.02,53.3,55.04,54.94,53.88,53.87,51.56,53.16,54.93,54.9,53.84,53.82,52.51,52.81,
43
+ 41,01/01/2019,61.89,81.81,67.63,52.1,51.48,45.74,51.13,53.44,53.07,50.21,50.8,42.18,49.37,51.75,51.75,50.78,49.48,43.85,49.8,51.75,51.56,50.78,51.05,45.66,49.77,51.68,50.06,49.96,45.67,49.14,51.18,52.11,50.8,50.82,47.27,49.87,51.68,51.74,50.86,50.82,48.02,49.93,51.8,51.73,50.64,50.65,48.81,49.75,51.65,51.66,50.67,50.68,48.18,48.4,54.04
44
+ 42,01/02/2019,66.03,81.64,76.77,61.8,64.93,71.53,60.96,62.7,66.02,64.67,65.06,66.44,64.17,66.12,66.32,65.26,64.67,61.88,64.67,66.3,66.11,65.29,65.51,61.98,64.58,65.8,65.51,64.91,62.64,64.79,65.91,65.32,63.96,63.86,62.39,63.32,64.57,64.43,63.85,63.86,62.56,63.18,64.43,64.44,63.83,63.85,63.45,63.17,64.41,64.43,63.9,63.96,63.9,63.66,73.15
45
+ 43,01/03/2019,68.39,81.51,72.38,65.97,66.31,70.15,65.3,66.66,67.05,67.23,66.61,71.87,66.81,68.23,67.93,66.66,67.37,67.81,66.27,68.02,68.43,66.7,66.78,65.3,66.24,67.73,67.95,68.13,65.3,67.38,68.41,67.47,68.4,69.02,68.47,67.84,68.74,69.39,68.9,69.01,68.22,68.41,69.47,69.52,69.01,69.01,68.42,68.52,69.52,69.52,69.02,69.07,69.39,69.37,67.49
46
+ 44,01/04/2019,72.8,81.4,78.02,68.35,68.99,70.72,67.77,68.92,69.67,69.08,68.98,71.25,68.68,69.87,69.78,68.85,69.02,72.97,68.46,69.78,69.77,68.79,68.44,70.88,68.46,70.11,69.6,70.76,69.89,69.19,70.52,69.94,72.22,71.83,69.81,71.72,72.62,72.26,72.09,71.84,71.1,71.54,72.44,72.21,71.61,71.59,70.72,71.14,72.19,72.15,71.57,71.57,70.92,71.19,69.42
47
+ 45,01/05/2019,64.49,81.33,76.9,72.8,73.96,77.19,72.32,73.13,74.35,74.13,74.08,76.53,73.83,74.69,74.65,74.06,74.21,76.86,73.76,74.66,74.81,74.05,74.28,77.71,73.78,74.83,73.23,74.15,76.93,72.99,74.33,75.45,74.87,74.11,72.48,74.52,75.58,74.9,74.1,74.15,72.35,73.6,74.49,74.58,74.23,74.27,74.14,73.72,74.55,74.61,74.38,74.46,73.64,73.76,74.53
48
+ 46,01/06/2019,66.55,81.19,70.64,64.42,61.6,56.06,63.85,65.18,62.43,62.03,61.6,60.05,61.47,62.77,62.55,61.59,62.54,60.59,61.09,62.6,63.29,61.58,61.36,61.24,61.09,62.65,61.17,61.18,61.84,60.68,62.33,62.32,59.8,59.33,58.02,59.28,61.07,60.58,58.99,59.21,56.47,58.37,60.05,60.29,59.64,59.64,56.44,58.92,60.35,60.36,59.63,59.63,58.86,58.86,59.29
49
+ 47,01/07/2019,65.17,81.07,77.61,66.5,67.93,68.57,65.91,67.15,68.78,67.12,67.7,65.16,66.67,68,68.21,67.63,66.5,67.83,67.11,68.15,67.36,67.58,67.63,67.83,67.12,68.4,67.52,67.25,68.15,67.05,68.33,68.73,66.79,67.55,70.14,66.28,67.64,68.39,67.37,67.63,68.56,66.96,68.52,68.73,68.08,68.08,66.33,67.58,68.89,68.86,68.08,67.9,65.83,66.34,70.01
50
+ 48,01/08/2019,60.43,80.94,70.36,65.11,64.32,63.73,64.52,65.82,65.08,64.75,64.5,64.81,64.27,65.61,65.54,64.6,65.41,62.22,64.15,65.56,66.31,64.68,64.84,63.61,64.16,65.33,63.92,63.57,63.64,63.45,64.81,65.33,63.88,63.87,64.83,63.38,64.69,64.64,64.16,63.91,65.75,63.71,65.12,64.87,63.62,63.61,63.46,63.22,64.83,64.77,63.56,63.34,60.55,60.59,64.64
51
+ 49,01/10/2019,60.23,80.78,72.33,60.33,59.2,55.6,59.66,61.27,60.3,59.01,59.06,56.65,58.43,60.07,60.05,59.01,58.33,57.91,58.43,60.05,59.32,59,58.73,56.75,58.44,60.17,59.96,59.56,57.56,59.33,60.74,59.84,58.79,58.75,57.67,58.19,59.7,59.65,58.76,58.74,58.27,58.16,59.7,59.64,58.46,58.49,59.69,57.89,59.5,59.55,58.55,58.56,56.79,56.23,58.9
52
+ 50,01/11/2019,62.43,80.62,70.31,60.13,60.44,59.98,59.44,61.07,61.54,60.12,60.37,58.46,59.57,61.29,61.38,60.37,60.73,58.99,59.79,61.35,61.92,60.37,60.62,59.47,59.79,61.39,60.12,60.37,58.75,59.56,61.17,61.78,61.58,62.08,61.45,60.95,62.28,62.83,62.01,62.1,61.41,61.44,62.93,62.96,62.05,62.07,62.3,61.48,62.93,62.95,62.12,62.22,64.04,63.37,63.12
53
+ 51,01/01/2020,58.16,80.47,73.77,62.35,62.94,64.6,61.7,63.17,63.88,63.02,63,63.79,62.55,64.12,64.1,63.05,64.76,62.29,62.57,64.11,63.93,63.06,62.95,62.39,62.55,63.99,63.04,63,62.63,62.52,63.92,63.68,62.61,61.85,60.17,62.09,63.48,62.7,62.1,61.82,61.17,61.49,62.79,62.57,61.64,61.64,61.05,61.1,62.52,62.49,61.63,61.68,62.08,62.3,65.67
54
+ 52,01/02/2020,50.52,80.3,67,58.05,56.66,53.8,57.36,59.06,57.8,56.88,56.67,55.87,56.3,58.04,57.93,56.67,57.49,55.78,56.12,57.96,58.66,56.67,56.79,55.25,56.11,57.96,57.14,57.27,55.36,56.54,58.2,58.09,57.19,57.64,56.29,56.57,58.13,58.65,57.3,57.63,55.47,56.7,58.34,58.63,57.85,57.88,57.04,57.19,58.66,58.72,57.95,58.05,57.05,57.33,56.61
55
+ 53,01/04/2020,25.27,80.07,66.02,50.35,48.54,42.77,49.52,51.69,50.09,48.21,48.38,43.81,47.48,49.69,49.73,48.33,47.51,45.95,47.59,49.71,48.98,48.33,48.13,46.11,47.62,49.88,48.43,48.89,45.88,47.7,49.86,49.74,49.28,49.02,46.35,48.5,50.42,50.17,49.18,49.03,46.9,48.39,50.34,50.22,49.05,49.04,45.74,48.28,50.25,50.21,49,48.93,47.84,47.94,48.99
56
+ 54,01/05/2020,35.33,79.65,44.83,24.9,17.75,-0.23,23.64,27.09,20.23,17.15,17.14,5.25,15.96,19.39,19.35,17.18,17.59,7.63,15.99,19.36,19.83,17.21,17.4,9.4,16,19.33,16.9,17.4,9.75,15.72,18.99,19.52,17.4,16.84,9.39,16.2,19.18,18.75,16.76,16.78,10.19,15.47,18.45,18.47,16.75,16.77,11.54,15.47,18.39,18.44,16.76,16.71,10.97,11.32,17.72
57
+ 55,01/06/2020,41.15,79.31,71.26,35.04,39.39,45.42,33.77,36.98,42.16,37.68,39.06,32.49,36.73,40.61,41.1,39.21,37,34.46,38.04,41.02,39.9,39.19,39,34.62,38.03,41.06,39.49,39.58,35.53,38.3,41.16,40.88,38.72,39.02,36,37.51,40.36,40.69,38.67,38.91,34.97,37.47,40.37,40.69,39.36,39.39,35.98,38.07,40.73,40.79,39.39,39.39,36.37,38.11,52.06
58
+ 56,01/07/2020,43.3,79.02,53.44,40.91,41.36,46.96,39.83,42.63,43.23,42.49,41.65,48.39,41.74,44.89,44.64,41.92,43.5,38.28,41.17,44.7,45.93,42.42,42.88,39.09,41.48,44.21,42.34,42.52,39.05,41.39,44.08,44.5,42.85,43.13,41.51,41.85,44.33,44.64,43.11,43.03,41.51,42.16,44.82,44.64,43.19,43.01,39.75,42.23,44.82,44.64,42.81,42.8,40.47,41.74,44.18
59
+ 57,01/08/2020,45.1,78.75,70.21,43.08,43.6,45.42,42.09,44.69,45.52,43.7,43.57,46.63,42.98,45.82,45.67,43.36,42.85,48.19,42.63,45.67,44.95,43.17,42.26,42.35,42.45,45.93,45.69,46.31,42.76,44.75,47.35,44.56,45.52,45.12,42.47,44.56,47.04,46.68,45.37,45.21,43.45,44.38,46.87,46.69,44.97,44.98,43.36,44.02,46.59,46.62,44.92,44.85,41.72,43.94,46.37
60
+ 58,01/09/2020,40.95,78.5,57.27,44.89,45.3,46.86,43.97,46.41,47.04,45.43,45.35,46.96,44.74,47.39,47.32,45.31,46.35,48.02,44.61,47.32,48.33,45.2,46.32,49.03,44.51,47.48,44.39,46.22,45.68,43.67,46.93,49.15,48.71,48.83,46.74,47.77,50.22,50.59,48.77,49.01,46.53,47.85,50.38,50.59,49,49.11,48.19,48.05,50.48,50.61,49.24,49.24,48.1,48.34,49.72
61
+ 59,01/10/2020,37.46,78.22,64.48,40.71,39.56,36.72,39.76,42.36,41.43,39.72,39.56,38.69,38.95,41.67,41.55,39.53,38.82,39.34,38.75,41.56,40.75,39.49,38.43,40.24,38.71,41.61,38.97,39.49,41.1,38.15,41.17,40.53,37.85,35.82,32.5,36.95,40.12,38.18,36.62,36.17,33.15,35.52,38.28,38.03,36.51,36.43,32.87,35.42,38.17,38.05,36.38,36.4,34.4,35.23,41.06
62
+ 60,01/12/2020,51.34,77.92,55.03,37.2,36.65,33.9,36.18,38.93,38.67,36.37,36.57,33.64,35.56,38.47,38.51,36.56,37.17,35.21,35.71,38.5,39.27,36.49,37.53,35.64,35.64,38.56,36.34,36.29,36.33,35.45,38.34,39.6,35.64,37.3,38.24,34.67,37.61,39.51,35.98,37.2,34.38,35.07,38.37,39.58,37.81,37.9,35.33,36.69,39.4,39.65,37.87,37.85,34.95,36.76,40.04
63
+ 61,01/01/2021,55.88,77.73,74.65,51.18,55.09,65.27,50.37,52.41,56.65,54.75,55.12,59.45,54.26,56.72,56.87,55.2,54.09,57.6,54.64,56.85,56.03,55.23,54.58,57.73,54.66,56.84,54.92,54.85,57.73,54.32,56.58,56.05,54.57,53.49,58.79,53.9,56.2,55.06,55.02,53.48,59.02,54.45,57.01,55.35,54.1,53.47,52.29,53.46,56.22,55.39,53.17,53.13,52.49,52.3,67.97
64
+ 62,01/02/2021,66.13,77.57,61.78,55.76,55.97,60.41,55.13,56.77,57.04,56.96,56.09,63.57,56.54,58.33,57.85,56.07,58,59.48,55.7,57.95,59.38,56.18,56.96,58.57,55.76,57.84,56.35,56.06,58.69,55.89,57.87,58.54,55.96,56.96,58.78,55.44,57.48,58.52,56.17,56.96,59.07,55.71,57.89,58.44,55.31,55.51,59.8,54.79,57.15,57.64,55.51,55.42,54.23,55.08,56.9
65
+ 63,01/03/2021,63.54,77.49,81.15,66.08,68.76,76.41,65.65,66.61,69.44,68.78,68.79,74.45,68.56,69.7,69.67,68.66,67.98,76.53,68.45,69.67,68.88,68.31,67.71,74.07,68.18,69.89,68.92,68.66,73.26,68.69,70.18,69.02,69.03,68.56,73.23,68.73,70.19,69.67,69.32,68.55,73.12,69.1,70.69,69.91,69.03,69.03,73.87,68.75,70.42,69.92,69.35,68.46,74.16,69.18,73.44
66
+ 64,01/04/2021,67.25,77.39,62.71,63.47,62.16,60.88,63.08,64.12,62.8,62.85,62.36,65.32,62.51,63.56,63.4,62.27,63.84,64.96,62,63.41,64.56,62.2,63.08,66.84,61.93,63.42,61,62.17,65.1,60.77,62.67,64.73,61.78,62.03,63.78,61.45,63.13,63.59,61.7,62.08,63.96,61.39,63.1,63.37,61.18,61.75,63.79,60.84,62.65,63.37,61.26,61.78,64.55,60.96,60.85
67
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+ 66,01/06/2021,75.13,77.26,67.76,69.61,69.9,71.98,69.33,69.95,70.25,70.23,70.07,72.42,70.02,70.7,70.67,70.08,71.37,70.87,69.9,70.67,71.83,70.18,71.25,72.75,69.97,70.65,69.3,69.38,72.55,69.16,70.16,72.31,69.07,70.83,75.32,68.89,69.95,71.59,69.89,70.78,74.42,69.86,71.28,71.8,70.58,70.44,73.4,70.45,71.69,71.8,70.55,70.8,73.66,70.43,70.5
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+ 68,01/09/2021,78.52,77.24,71.45,76.36,76.32,77.49,76.23,76.35,76.29,76.67,76.48,78.97,76.56,76.69,76.66,76.43,77.8,78.55,76.37,76.66,77.83,76.4,77.54,78.75,76.34,76.66,76.16,75.5,78.01,76.13,76.54,78.35,76.5,78.36,80.67,76.44,76.77,78.6,77.3,78.36,80.59,77.34,77.92,78.72,77.02,78.17,82.59,77.05,77.7,78.76,77.49,77.88,81.01,77.65,75.43
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+ 69,01/10/2021,84.38,77.25,83.1,78.56,79.12,80.68,78.48,78.44,79.02,79.12,79.12,80.31,79.05,79.03,79.03,79.09,78.06,81.36,79.03,79.03,77.96,78.91,77.9,81.08,78.89,79.05,78.83,77.93,81.23,78.82,79.01,77.59,78.44,76.75,79.65,78.45,78.72,77.02,78.24,76.75,80.32,78.22,78.44,77,77.03,76.67,80.1,77.08,77.59,77.02,77.13,76.41,81.53,77.2,78.18
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+ 70,01/11/2021,70.57,77.3,78.37,84.46,85.8,90.24,84.47,84.04,85.36,85.95,85.93,88.94,86,85.6,85.6,85.92,87.17,88.34,85.98,85.6,86.82,85.89,87.24,88.87,85.96,85.6,85.52,84.59,88.61,85.63,85.43,87.09,85.36,86.95,88.81,85.48,85.33,86.84,85.66,86.94,88.31,85.8,85.73,86.92,85.96,86.94,90.17,86.08,85.94,86.92,86.43,86.44,89.9,86.65,85.1
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+ 71,01/12/2021,79.2,77.25,70.79,70.56,66.82,56.62,70.41,70.85,67.02,67.18,66.84,63.55,66.88,67.17,67.12,66.78,65.99,64.39,66.56,67.13,65.96,66.77,65.88,64.86,66.56,67.13,66.73,65.83,65.65,66.54,67.1,66.16,66.24,65.35,65.72,66.09,66.73,65.73,66.24,65.32,66.2,66.07,66.74,65.92,65.78,65.71,65.25,65.66,66.43,65.89,65.73,65.72,67.14,65.57,63.87
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+ 72,01/01/2022,91.21,77.26,84.31,79.24,81.94,87.84,79.13,79.09,81.98,81.19,81.6,79.33,81.16,81.24,81.09,81.65,81.2,82.59,81.51,81.09,81.13,81.35,81.87,82.4,81.28,81.16,81.32,80.02,82.43,81.27,81.15,81.74,81.17,81.92,83.51,81.14,81.06,81.83,81.5,81.9,83.22,81.5,81.53,81.76,81.56,81.57,83.92,81.57,81.58,81.67,81.57,81.59,82.62,81.63,84
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+ 73,01/02/2022,100.99,77.36,83.15,91.34,93.5,103.26,91.44,90.54,92.61,94.15,93.76,102.05,94.36,93.53,93.45,93.86,93.51,95.38,94.11,93.47,92.88,94.15,94.01,96.99,94.3,93.18,93.36,92.96,96.62,93.6,92.79,92.91,93.26,92.83,96.41,93.51,92.75,92.21,93.45,92.87,96.58,93.7,92.96,92.58,93.05,93.05,95.97,93.35,92.75,92.42,93.06,93.07,96.46,93.35,93.66
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+ 74,01/03/2022,107.91,77.52,92.47,101.18,103.01,110.79,101.5,99.91,101.62,103.54,103.25,111.59,103.88,102.27,102.23,103.13,104.48,110.91,103.53,102.23,102.33,102.93,102.62,106.62,103.38,102.25,103.95,103.45,107.7,104.32,102.75,101.75,102.89,103.18,106.84,103.34,102.08,102.26,103.01,103.16,106.67,103.46,102.18,102.24,102.84,102.88,106.88,103.31,102.11,102.19,102.91,102.93,106.17,103.41,102.22
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+ 75,01/04/2022,109.34,77.72,90.69,108.14,109.36,114.83,108.61,106.57,107.59,109.83,109.61,115.85,110.23,108.1,108.1,109.53,109.11,116.75,109.99,108.1,107.37,109.26,109.56,116.47,109.78,108.16,108.78,109.06,113.38,109.35,107.93,108.64,110.15,110.73,115.43,110.66,108.9,109.53,110.94,110.84,115.12,111.49,109.89,109.85,110.84,110.86,114.82,111.41,109.88,109.73,110.88,110.92,115.02,111.47,107.48
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+ 76,01/06/2022,114.81,77.92,93.6,109.58,109.58,110.74,110.11,107.97,107.74,109.89,109.71,112.67,110.27,107.94,107.95,109.65,110.73,113.98,110.08,107.95,108.78,109.43,109.39,114.9,109.91,108,108.7,108.51,114.89,109.25,107.65,107.88,108.12,106.84,109.28,108.72,107.3,106.08,107.13,106.65,110.12,107.61,105.8,105.38,106.32,106.33,109.61,106.89,105.37,105.53,106.34,106.36,109.43,106.9,108.15
Explore/PREDICTIONS/Monthly/60.csv ADDED
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1
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+ 1,01/08/2016,47.04,87.62,61.75,42.13,40.18,35.09,40.16,44.18,42.58,40.08,39.99,37.96,38.61,42.63,42.77,39.96,40.56,40.43,38.47,42.75,43.22,39.71,39.95,40.45,38.16,43.02,39.59,39.94,40.37,37.88,42.77,44.06,39.56,39.67,39.05,37.51,42.24,42.57,39.37,39.65,37.91,37.43,42.21,42.46,40.09,40.09,39.36,38.07,42.47,42.54,40.1,40.21,37.8,38.04,
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+ 3,01/10/2016,48.3,86.77,65.12,48.81,48.92,51.03,47.06,50.55,50.91,49.49,49.36,51.87,48.25,51.91,52.09,49.37,50.37,49.06,48.13,52.07,52.85,49.52,49.37,49.72,48.23,51.91,49.11,48.37,50.28,47.73,51.59,52.66,47.69,47.86,50.12,45.98,50.16,50.36,47.82,47.85,49.98,46.2,50.64,50.55,47.69,47.68,48.8,45.88,50.44,50.43,47.66,47.52,46.02,46.26,
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+ 4,01/11/2016,50.47,86.37,72.41,48.04,47.88,47.46,46.34,49.77,49.91,47.91,47.86,48.37,46.67,50.19,50.31,47.84,47.11,49.27,46.59,50.28,49.57,47.77,47.86,47.8,46.51,50.52,48.54,47.99,48.14,47.16,50.79,49.68,47.82,48.33,50.14,46.21,49.92,50.42,48.23,48.29,50.15,46.7,50.85,50.77,48.01,48.02,49.89,46.3,50.6,50.62,48.03,48,48.34,47.81,
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+ 5,01/12/2016,56.13,86,67.6,50.24,50.97,52.59,48.62,51.85,52.87,50.96,50.99,51.56,49.8,53.17,53.2,50.99,51.44,52.02,49.81,53.19,53.73,50.95,50.97,52.43,49.77,53.35,50.52,50.53,51.68,49.25,53,54.35,51.84,51.97,52.89,50.34,53.73,53.95,52.1,51.97,53.56,50.69,54.3,54.07,51.41,51.41,53.56,49.84,53.83,53.83,51.43,51.49,53.19,52.76,
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+ 6,01/02/2017,55.59,85.69,76.11,55.96,57.42,61.78,54.52,57.31,59.01,57.7,57.67,60.57,56.73,59.67,59.74,57.67,61.93,59.51,56.69,59.72,59.17,57.68,57.05,59.59,56.69,59.76,57.42,56.99,59.75,56.35,59.54,59.08,56.59,56.08,56.91,55.28,58.61,58.12,56.21,56.08,57.25,54.94,58.14,58.02,55.85,55.88,58.39,54.49,57.88,57.92,55.95,56.15,58.23,58.07,
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+ 7,01/03/2017,52.83,85.38,68.16,55.41,54.91,54.98,54.06,56.77,56.44,55.33,55.16,57.06,54.34,57.07,57.24,55.16,56.16,56.7,54.2,57.21,57.82,55.15,55.73,56.29,54.18,57.31,55.23,54.82,56.37,54.18,57.25,58.01,54.79,55.33,57.08,53.53,56.63,57.23,55.06,55.33,56.14,53.89,57.22,57.42,55.58,55.6,56.77,54.3,57.43,57.48,55.64,55.83,58.38,58.34,
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+ 8,01/04/2017,51.73,85.05,72.22,52.63,52.05,49.97,51.25,54.07,53.73,51.9,51.9,50.68,50.85,53.69,53.72,51.88,51.06,52.5,50.82,53.71,53.16,51.81,51.21,52.45,50.77,53.97,51.74,51.54,52.31,50.63,53.83,53.54,51.93,51.87,52.67,50.63,53.71,53.65,52.05,51.87,53.05,50.83,54.02,53.81,51.69,51.68,51.47,50.39,53.76,53.71,51.63,51.59,52.37,52.77,
11
+ 9,01/05/2017,50.31,84.72,67.47,51.52,51.44,50.55,50.12,52.98,53.13,51.28,51.34,49.94,50.23,53.14,53.13,51.34,52.06,50.37,50.27,53.13,53.64,51.34,51.93,51.33,50.26,53.2,50.77,50.44,51.32,49.66,52.8,53.93,50.65,50.61,50.74,49.36,52.43,52.46,50.6,50.61,50.9,49.36,52.47,52.43,50.44,50.45,51.55,49.13,52.31,52.34,50.48,50.53,49.47,49.75,
12
+ 10,01/06/2017,47.92,84.38,69.96,50.09,49.78,48.81,48.68,51.57,51.49,49.76,49.76,48.87,48.71,51.64,51.65,49.77,48.97,48.46,48.7,51.65,51.27,49.79,49.34,48.67,48.71,51.64,49.74,49.15,49.12,48.61,51.52,51.14,48.72,48.78,49.07,47.44,50.45,50.51,48.76,48.78,48.88,47.54,50.63,50.63,48.83,48.83,49.14,47.54,50.6,50.62,48.85,48.92,50,49.65,
13
+ 11,01/07/2017,52.65,84.02,65.39,47.67,47.16,45.44,46.25,49.22,48.94,47.06,47.08,45.72,45.99,48.99,49.01,47.08,47.82,45.88,45.98,49.01,49.42,47.08,47.5,45.68,45.98,49.05,47.29,46.94,45.79,46.13,49.07,49.48,47.23,47.59,47.6,45.94,48.79,49.19,47.54,47.58,47.62,46.33,49.37,49.34,47.48,47.48,47.32,46.21,49.27,49.27,47.48,47.49,47.69,47.82,
14
+ 12,01/08/2017,52.38,83.72,72.98,52.45,54.01,57.36,51.13,53.8,55.61,53.91,54.01,54.92,52.99,55.79,55.76,54.01,53.16,54.54,53.05,55.77,55.01,54.01,53.59,54.36,53.05,55.81,54.05,53.9,54.21,53.03,55.74,55.44,54.34,54.31,54.51,53.18,55.77,55.76,54.43,54.31,55.01,53.33,55.99,55.83,54.04,54.04,54.93,52.9,55.71,55.71,54.05,54.07,54.29,54.34,
15
+ 13,01/09/2017,57.54,83.41,66,52.18,51.74,52.04,50.93,53.52,53.22,52.18,52.02,53.72,51.27,53.87,53.97,52.03,53.04,52.29,51.13,53.96,54.75,52.07,52.57,52.18,51.15,53.91,52.09,52.03,52.11,51.11,53.82,54.31,52.19,52.07,51.52,51.08,53.69,53.63,52.08,52.07,51.69,51,53.63,53.6,51.96,51.97,52.55,50.85,53.5,53.53,52,52.11,52.57,52.47,
16
+ 14,01/11/2017,63.57,83.17,76.05,57.39,59.01,62.69,56.27,58.5,60.33,58.95,59,60.79,58.19,60.51,60.51,58.99,58.15,61.62,58.2,60.51,59.67,58.91,58.15,60.69,58.15,60.69,59.24,59.22,60.6,58.39,60.8,60.21,59.18,59.27,60.2,58.19,60.56,60.68,59.21,59.27,59.83,58.27,60.68,60.72,59.36,59.37,59.98,58.36,60.73,60.74,59.39,59.48,60.85,60.78,
17
+ 15,01/12/2017,66.6,82.98,72.45,63.48,64.77,69.6,62.55,64.31,65.7,65.3,65.2,69.28,64.71,66.52,66.61,65.2,66.29,67.8,64.64,66.6,67.24,65.22,65.88,68.14,64.64,66.59,64.68,64.66,67.7,64.07,66.21,67.29,65.21,65.29,67.27,64.43,66.46,66.58,65.3,65.29,67.04,64.58,66.66,66.63,65.29,65.28,66.34,64.51,66.61,66.6,65.27,65.29,66.39,66.51,
18
+ 16,01/01/2018,69.05,82.83,77.91,66.54,67.07,69.6,65.75,67.22,67.84,67.47,67.35,70.6,66.94,68.41,68.53,67.34,66.66,70.65,66.84,68.51,67.57,67.3,66.6,69.95,66.82,68.66,67.42,67.09,70.13,66.88,68.67,68.03,66.46,66.25,68.27,65.79,67.74,67.51,66.31,66.25,68.16,65.67,67.58,67.52,66.2,66.21,67.74,65.52,67.48,67.48,66.21,66.22,66.78,66.84,
19
+ 17,01/02/2018,65.78,82.7,75.22,69.02,69.58,71.46,68.31,69.56,70.22,69.77,69.72,71.63,69.28,70.53,70.6,69.71,70.66,72.47,69.24,70.59,71.43,69.66,70.18,72.55,69.23,70.78,69.29,69.03,72.24,68.83,70.51,71.53,69.49,70,72.98,68.89,70.54,71.09,69.84,70,72.32,69.34,71.12,71.22,70.04,70.05,72.1,69.47,71.2,71.22,70.07,70.11,71.5,71.29,
20
+ 18,01/03/2018,70.27,82.55,74.57,65.72,64.65,62.42,64.99,66.42,65.43,64.79,64.71,64.33,64.19,65.6,65.67,64.7,63.96,64.98,64.13,65.66,65.27,64.67,64.24,65.64,64.11,65.74,64.13,63.66,65.75,63.58,65.36,65.37,63.56,63.25,64.58,62.91,64.75,64.41,63.47,63.25,65.09,62.84,64.67,64.46,63.02,63.01,64.05,62.39,64.37,64.34,62.98,62.95,64,63.93,
21
+ 19,01/05/2018,77.59,82.44,78.8,70.25,71.82,74.74,69.59,70.72,72.42,71.58,71.68,72.03,71.14,72.31,72.24,71.67,71.74,72.84,71.19,72.24,72.45,71.63,71.93,72.97,71.18,72.36,71.4,70.67,73.26,70.94,72.19,72.78,70.41,70.8,73.55,69.88,71.3,71.71,70.64,70.8,72.94,70.18,71.69,71.79,70.77,70.78,73.61,70.26,71.74,71.78,70.82,70.95,71.98,71.88,
22
+ 20,01/06/2018,79.44,82.39,81.38,77.63,79.27,84.92,77.16,77.74,79.39,79.81,79.73,83.94,79.56,80.15,80.2,79.74,79.16,81.66,79.52,80.19,79.49,79.77,79.62,81.9,79.51,80.06,79.42,78.7,81.92,79.17,79.85,79.86,78.94,79.26,82.93,78.65,79.43,79.67,79.36,79.27,82.92,79.17,80.06,79.94,79.09,79.08,81.89,78.89,79.9,79.87,79.07,79.13,82.58,82.17,
23
+ 21,01/08/2018,77.42,82.37,80.73,79.5,79.56,81.25,79.13,79.51,79.57,80.05,79.87,83.09,79.79,80.14,80.26,79.87,80.84,82.84,79.67,80.23,80.93,79.85,79.91,81.77,79.68,80.33,80.23,79.72,81.92,80.02,80.54,80.35,79.62,79.7,82.01,79.38,80.02,80.06,79.8,79.7,82.5,79.61,80.28,80.14,79.31,79.33,82.53,79.16,80.01,80.01,79.39,79.48,81.29,81.4,
24
+ 22,01/09/2018,82.72,82.32,79.52,77.46,76.86,75.32,77.08,77.57,77.02,76.87,76.82,76.59,76.53,76.99,77.03,76.8,76.11,78.39,76.48,77.02,76.82,76.74,76.56,78.47,76.48,77.24,76.52,76.38,77.98,76.27,77.1,77.34,77.24,77.44,78.59,76.92,77.63,77.84,77.43,77.44,78.76,77.15,77.92,77.89,77.21,77.24,79.65,76.94,77.78,77.81,77.32,77.52,79.89,79.71,
25
+ 23,01/10/2018,75.47,82.33,85.05,82.81,84.47,88.01,82.51,82.64,84.35,84.35,84.45,85.49,84.18,84.32,84.27,84.44,84.42,85.87,84.24,84.28,84.36,84.44,84.57,86.62,84.26,84.37,83.84,83.38,86.62,83.71,84.05,84.58,83.35,83.05,84.73,83.19,83.63,83.31,83.15,83.05,84.85,82.96,83.34,83.26,82.94,82.96,85.03,82.78,83.22,83.23,83.02,83.23,85.98,85.97,
26
+ 24,01/11/2018,58.71,82.27,74.14,75.49,73.04,68.1,75.12,75.71,73.24,73.43,73.27,72.43,73.01,73.54,73.7,73.27,73.56,71.6,72.92,73.68,73.72,73.29,73.29,72.17,72.91,73.57,73.03,72.39,72.63,72.68,73.4,73.48,72,72.24,72.83,71.67,72.52,72.72,72.12,72.24,72.41,71.8,72.7,72.8,72.32,72.33,72.79,71.98,72.8,72.83,72.36,72.49,73.43,73.76,
27
+ 25,01/12/2018,52.28,82.06,68.96,58.59,54.42,41.75,57.86,59.65,55.66,53.58,53.74,44.82,52.74,54.5,54.5,53.68,54.04,49.08,52.83,54.5,54.4,53.71,53.46,49.13,52.91,54.84,54.11,53.79,49.47,53.31,55.04,54.7,53.85,53.97,51.48,53.08,54.72,54.81,54.05,53.97,52.02,53.3,55.04,54.94,53.88,53.87,51.56,53.16,54.93,54.9,53.84,53.82,52.51,52.81,
28
+ 26,01/01/2019,61.89,81.81,67.63,52.1,51.48,45.74,51.13,53.44,53.07,50.21,50.8,42.18,49.37,51.75,51.75,50.78,49.48,43.85,49.8,51.75,51.56,50.78,51.05,45.66,49.77,51.68,50.06,49.96,45.67,49.14,51.18,52.11,50.8,50.82,47.27,49.87,51.68,51.74,50.86,50.82,48.02,49.93,51.8,51.73,50.64,50.65,48.81,49.75,51.65,51.66,50.67,50.68,48.18,48.4,
29
+ 27,01/02/2019,66.03,81.64,76.77,61.8,64.93,71.53,60.96,62.7,66.02,64.67,65.06,66.44,64.17,66.12,66.32,65.26,64.67,61.88,64.67,66.3,66.11,65.29,65.51,61.98,64.58,65.8,65.51,64.91,62.64,64.79,65.91,65.32,63.96,63.86,62.39,63.32,64.57,64.43,63.85,63.86,62.56,63.18,64.43,64.44,63.83,63.85,63.45,63.17,64.41,64.43,63.9,63.96,63.9,63.66,
30
+ 28,01/03/2019,68.39,81.51,72.38,65.97,66.31,70.15,65.3,66.66,67.05,67.23,66.61,71.87,66.81,68.23,67.93,66.66,67.37,67.81,66.27,68.02,68.43,66.7,66.78,65.3,66.24,67.73,67.95,68.13,65.3,67.38,68.41,67.47,68.4,69.02,68.47,67.84,68.74,69.39,68.9,69.01,68.22,68.41,69.47,69.52,69.01,69.01,68.42,68.52,69.52,69.52,69.02,69.07,69.39,69.37,
31
+ 29,01/04/2019,72.8,81.4,78.02,68.35,68.99,70.72,67.77,68.92,69.67,69.08,68.98,71.25,68.68,69.87,69.78,68.85,69.02,72.97,68.46,69.78,69.77,68.79,68.44,70.88,68.46,70.11,69.6,70.76,69.89,69.19,70.52,69.94,72.22,71.83,69.81,71.72,72.62,72.26,72.09,71.84,71.1,71.54,72.44,72.21,71.61,71.59,70.72,71.14,72.19,72.15,71.57,71.57,70.92,71.19,
32
+ 30,01/05/2019,64.49,81.33,76.9,72.8,73.96,77.19,72.32,73.13,74.35,74.13,74.08,76.53,73.83,74.69,74.65,74.06,74.21,76.86,73.76,74.66,74.81,74.05,74.28,77.71,73.78,74.83,73.23,74.15,76.93,72.99,74.33,75.45,74.87,74.11,72.48,74.52,75.58,74.9,74.1,74.15,72.35,73.6,74.49,74.58,74.23,74.27,74.14,73.72,74.55,74.61,74.38,74.46,73.64,73.76,
33
+ 31,01/06/2019,66.55,81.19,70.64,64.42,61.6,56.06,63.85,65.18,62.43,62.03,61.6,60.05,61.47,62.77,62.55,61.59,62.54,60.59,61.09,62.6,63.29,61.58,61.36,61.24,61.09,62.65,61.17,61.18,61.84,60.68,62.33,62.32,59.8,59.33,58.02,59.28,61.07,60.58,58.99,59.21,56.47,58.37,60.05,60.29,59.64,59.64,56.44,58.92,60.35,60.36,59.63,59.63,58.86,58.86,
34
+ 32,01/07/2019,65.17,81.07,77.61,66.5,67.93,68.57,65.91,67.15,68.78,67.12,67.7,65.16,66.67,68,68.21,67.63,66.5,67.83,67.11,68.15,67.36,67.58,67.63,67.83,67.12,68.4,67.52,67.25,68.15,67.05,68.33,68.73,66.79,67.55,70.14,66.28,67.64,68.39,67.37,67.63,68.56,66.96,68.52,68.73,68.08,68.08,66.33,67.58,68.89,68.86,68.08,67.9,65.83,66.34,
35
+ 33,01/08/2019,60.43,80.94,70.36,65.11,64.32,63.73,64.52,65.82,65.08,64.75,64.5,64.81,64.27,65.61,65.54,64.6,65.41,62.22,64.15,65.56,66.31,64.68,64.84,63.61,64.16,65.33,63.92,63.57,63.64,63.45,64.81,65.33,63.88,63.87,64.83,63.38,64.69,64.64,64.16,63.91,65.75,63.71,65.12,64.87,63.62,63.61,63.46,63.22,64.83,64.77,63.56,63.34,60.55,60.59,
36
+ 34,01/10/2019,60.23,80.78,72.33,60.33,59.2,55.6,59.66,61.27,60.3,59.01,59.06,56.65,58.43,60.07,60.05,59.01,58.33,57.91,58.43,60.05,59.32,59,58.73,56.75,58.44,60.17,59.96,59.56,57.56,59.33,60.74,59.84,58.79,58.75,57.67,58.19,59.7,59.65,58.76,58.74,58.27,58.16,59.7,59.64,58.46,58.49,59.69,57.89,59.5,59.55,58.55,58.56,56.79,56.23,58.82
37
+ 35,01/11/2019,62.43,80.62,70.31,60.13,60.44,59.98,59.44,61.07,61.54,60.12,60.37,58.46,59.57,61.29,61.38,60.37,60.73,58.99,59.79,61.35,61.92,60.37,60.62,59.47,59.79,61.39,60.12,60.37,58.75,59.56,61.17,61.78,61.58,62.08,61.45,60.95,62.28,62.83,62.01,62.1,61.41,61.44,62.93,62.96,62.05,62.07,62.3,61.48,62.93,62.95,62.12,62.22,64.04,63.37,60.49
38
+ 36,01/01/2020,58.16,80.47,73.77,62.35,62.94,64.6,61.7,63.17,63.88,63.02,63,63.79,62.55,64.12,64.1,63.05,64.76,62.29,62.57,64.11,63.93,63.06,62.95,62.39,62.55,63.99,63.04,63,62.63,62.52,63.92,63.68,62.61,61.85,60.17,62.09,63.48,62.7,62.1,61.82,61.17,61.49,62.79,62.57,61.64,61.64,61.05,61.1,62.52,62.49,61.63,61.68,62.08,62.3,63.11
39
+ 37,01/02/2020,50.52,80.3,67,58.05,56.66,53.8,57.36,59.06,57.8,56.88,56.67,55.87,56.3,58.04,57.93,56.67,57.49,55.78,56.12,57.96,58.66,56.67,56.79,55.25,56.11,57.96,57.14,57.27,55.36,56.54,58.2,58.09,57.19,57.64,56.29,56.57,58.13,58.65,57.3,57.63,55.47,56.7,58.34,58.63,57.85,57.88,57.04,57.19,58.66,58.72,57.95,58.05,57.05,57.33,56.6
40
+ 38,01/04/2020,25.27,80.07,66.02,50.35,48.54,42.77,49.52,51.69,50.09,48.21,48.38,43.81,47.48,49.69,49.73,48.33,47.51,45.95,47.59,49.71,48.98,48.33,48.13,46.11,47.62,49.88,48.43,48.89,45.88,47.7,49.86,49.74,49.28,49.02,46.35,48.5,50.42,50.17,49.18,49.03,46.9,48.39,50.34,50.22,49.05,49.04,45.74,48.28,50.25,50.21,49,48.93,47.84,47.94,49.36
41
+ 39,01/05/2020,35.33,79.65,44.83,24.9,17.75,-0.23,23.64,27.09,20.23,17.15,17.14,5.25,15.96,19.39,19.35,17.18,17.59,7.63,15.99,19.36,19.83,17.21,17.4,9.4,16,19.33,16.9,17.4,9.75,15.72,18.99,19.52,17.4,16.84,9.39,16.2,19.18,18.75,16.76,16.78,10.19,15.47,18.45,18.47,16.75,16.77,11.54,15.47,18.39,18.44,16.76,16.71,10.97,11.32,25.89
42
+ 40,01/06/2020,41.15,79.31,71.26,35.04,39.39,45.42,33.77,36.98,42.16,37.68,39.06,32.49,36.73,40.61,41.1,39.21,37,34.46,38.04,41.02,39.9,39.19,39,34.62,38.03,41.06,39.49,39.58,35.53,38.3,41.16,40.88,38.72,39.02,36,37.51,40.36,40.69,38.67,38.91,34.97,37.47,40.37,40.69,39.36,39.39,35.98,38.07,40.73,40.79,39.39,39.39,36.37,38.11,45.24
43
+ 41,01/07/2020,43.3,79.02,53.44,40.91,41.36,46.96,39.83,42.63,43.23,42.49,41.65,48.39,41.74,44.89,44.64,41.92,43.5,38.28,41.17,44.7,45.93,42.42,42.88,39.09,41.48,44.21,42.34,42.52,39.05,41.39,44.08,44.5,42.85,43.13,41.51,41.85,44.33,44.64,43.11,43.03,41.51,42.16,44.82,44.64,43.19,43.01,39.75,42.23,44.82,44.64,42.81,42.8,40.47,41.74,43.67
44
+ 42,01/08/2020,45.1,78.75,70.21,43.08,43.6,45.42,42.09,44.69,45.52,43.7,43.57,46.63,42.98,45.82,45.67,43.36,42.85,48.19,42.63,45.67,44.95,43.17,42.26,42.35,42.45,45.93,45.69,46.31,42.76,44.75,47.35,44.56,45.52,45.12,42.47,44.56,47.04,46.68,45.37,45.21,43.45,44.38,46.87,46.69,44.97,44.98,43.36,44.02,46.59,46.62,44.92,44.85,41.72,43.94,44.91
45
+ 43,01/09/2020,40.95,78.5,57.27,44.89,45.3,46.86,43.97,46.41,47.04,45.43,45.35,46.96,44.74,47.39,47.32,45.31,46.35,48.02,44.61,47.32,48.33,45.2,46.32,49.03,44.51,47.48,44.39,46.22,45.68,43.67,46.93,49.15,48.71,48.83,46.74,47.77,50.22,50.59,48.77,49.01,46.53,47.85,50.38,50.59,49,49.11,48.19,48.05,50.48,50.61,49.24,49.24,48.1,48.34,46.74
46
+ 44,01/10/2020,37.46,78.22,64.48,40.71,39.56,36.72,39.76,42.36,41.43,39.72,39.56,38.69,38.95,41.67,41.55,39.53,38.82,39.34,38.75,41.56,40.75,39.49,38.43,40.24,38.71,41.61,38.97,39.49,41.1,38.15,41.17,40.53,37.85,35.82,32.5,36.95,40.12,38.18,36.62,36.17,33.15,35.52,38.28,38.03,36.51,36.43,32.87,35.42,38.17,38.05,36.38,36.4,34.4,35.23,41.7
47
+ 45,01/12/2020,51.34,77.92,55.03,37.2,36.65,33.9,36.18,38.93,38.67,36.37,36.57,33.64,35.56,38.47,38.51,36.56,37.17,35.21,35.71,38.5,39.27,36.49,37.53,35.64,35.64,38.56,36.34,36.29,36.33,35.45,38.34,39.6,35.64,37.3,38.24,34.67,37.61,39.51,35.98,37.2,34.38,35.07,38.37,39.58,37.81,37.9,35.33,36.69,39.4,39.65,37.87,37.85,34.95,36.76,39.5
48
+ 46,01/01/2021,55.88,77.73,74.65,51.18,55.09,65.27,50.37,52.41,56.65,54.75,55.12,59.45,54.26,56.72,56.87,55.2,54.09,57.6,54.64,56.85,56.03,55.23,54.58,57.73,54.66,56.84,54.92,54.85,57.73,54.32,56.58,56.05,54.57,53.49,58.79,53.9,56.2,55.06,55.02,53.48,59.02,54.45,57.01,55.35,54.1,53.47,52.29,53.46,56.22,55.39,53.17,53.13,52.49,52.3,57.93
49
+ 47,01/02/2021,66.13,77.57,61.78,55.76,55.97,60.41,55.13,56.77,57.04,56.96,56.09,63.57,56.54,58.33,57.85,56.07,58,59.48,55.7,57.95,59.38,56.18,56.96,58.57,55.76,57.84,56.35,56.06,58.69,55.89,57.87,58.54,55.96,56.96,58.78,55.44,57.48,58.52,56.17,56.96,59.07,55.71,57.89,58.44,55.31,55.51,59.8,54.79,57.15,57.64,55.51,55.42,54.23,55.08,55.74
50
+ 48,01/03/2021,63.54,77.49,81.15,66.08,68.76,76.41,65.65,66.61,69.44,68.78,68.79,74.45,68.56,69.7,69.67,68.66,67.98,76.53,68.45,69.67,68.88,68.31,67.71,74.07,68.18,69.89,68.92,68.66,73.26,68.69,70.18,69.02,69.03,68.56,73.23,68.73,70.19,69.67,69.32,68.55,73.12,69.1,70.69,69.91,69.03,69.03,73.87,68.75,70.42,69.92,69.35,68.46,74.16,69.18,69.72
51
+ 49,01/04/2021,67.25,77.39,62.71,63.47,62.16,60.88,63.08,64.12,62.8,62.85,62.36,65.32,62.51,63.56,63.4,62.27,63.84,64.96,62,63.41,64.56,62.2,63.08,66.84,61.93,63.42,61,62.17,65.1,60.77,62.67,64.73,61.78,62.03,63.78,61.45,63.13,63.59,61.7,62.08,63.96,61.39,63.1,63.37,61.18,61.75,63.79,60.84,62.65,63.37,61.26,61.78,64.55,60.96,61.45
52
+ 50,01/05/2021,69.63,77.31,81.11,67.21,68.49,70.94,66.86,67.67,69.1,68.17,68.36,68.72,67.92,68.82,68.85,68.32,67.17,71.59,68.05,68.85,67.81,67.95,67.31,71.25,67.74,68.9,67.79,67.64,72.6,67.57,68.78,67.69,66.16,65.55,69.09,65.95,67.54,66.66,65.78,65.44,68.71,65.55,67.04,66.88,65.94,65.74,69.08,65.66,67.1,66.84,66.11,65.6,68.84,65.89,68.61
53
+ 51,01/06/2021,75.13,77.26,67.76,69.61,69.9,71.98,69.33,69.95,70.25,70.23,70.07,72.42,70.02,70.7,70.67,70.08,71.37,70.87,69.9,70.67,71.83,70.18,71.25,72.75,69.97,70.65,69.3,69.38,72.55,69.16,70.16,72.31,69.07,70.83,75.32,68.89,69.95,71.59,69.89,70.78,74.42,69.86,71.28,71.8,70.58,70.44,73.4,70.45,71.69,71.8,70.55,70.8,73.66,70.43,69.87
54
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Explore/PREDICTIONS/Monthly/80.csv ADDED
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+ 48,12/21/2015,37.89,90.65,68.33,36.79,35.84,36.78,36.31,37.26,37.25,36.78,33.69,36.31,37.25,37.17,36.38,36.18,34.03,
51
+ 49,12/28/2015,37.28,90.53,63.41,37.81,38.91,37.82,37.33,38.26,38.29,37.82,37.82,37.35,38.3,38.32,37.74,37.25,36.14,
52
+ 50,1/4/2016,33.55,90.41,67.14,37.19,36.68,37.19,36.72,37.65,37.65,37.19,37.54,36.72,37.65,37.73,37.27,36.85,37.15,
53
+ 51,1/11/2016,31.01,90.28,60.32,33.46,29.82,33.41,32.97,33.92,33.87,33.4,31.48,32.93,33.86,33.82,33.36,33.15,32.55,
54
+ 52,1/18/2016,32.18,90.15,64.02,30.91,28.47,30.88,30.4,31.38,31.34,30.87,27.84,30.38,31.34,31.2,30.59,30.37,28.65,
55
+ 53,1/25/2016,34.74,90.01,61.58,32.08,33.36,32.1,31.58,32.54,32.58,32.1,31.39,31.6,32.58,32.54,31.91,31.46,30.36,
56
+ 54,2/1/2016,34.06,89.89,65.93,34.65,37.32,34.69,34.16,35.1,35.16,34.69,36.58,34.21,35.17,35.34,34.79,34.26,35.13,
57
+ 55,2/8/2016,33.36,89.76,61.27,33.97,33.39,33.96,33.49,34.42,34.42,33.96,35.11,33.49,34.42,34.65,34.16,33.88,35.22,
58
+ 56,2/15/2016,33.01,89.64,64.69,33.27,32.67,33.26,32.78,33.72,33.71,33.26,32.68,32.78,33.71,33.94,33.21,33.15,33.74,
59
+ 57,2/22/2016,35.1,89.51,61.15,32.92,32.67,32.91,32.43,33.36,33.37,32.91,32.48,32.44,33.37,33.6,32.87,32.77,32.43,
60
+ 58,2/29/2016,38.72,89.39,66.08,35.01,37.2,35.04,34.54,35.45,35.5,35.05,35.91,34.57,35.51,35.86,35.02,34.87,35.38,
61
+ 59,3/7/2016,40.39,89.27,64.76,38.64,42.36,38.7,38.19,39.06,39.15,38.71,41.55,38.25,39.16,39.72,38.86,38.7,40.5,
62
+ 60,3/14/2016,41.2,89.17,67.34,40.31,42.07,40.34,39.88,40.73,40.77,40.35,43.11,39.92,40.78,41.47,40.62,40.66,42.95,
63
+ 61,3/21/2016,40.44,89.06,65.62,41.13,42.02,41.14,40.71,41.53,41.56,41.14,42.48,40.73,41.57,42.28,41.27,41.54,43.26,
64
+ 62,3/28/2016,39.66,88.95,66.37,40.36,39.69,40.35,39.94,40.77,40.77,40.35,40.52,39.94,40.77,41.43,40.42,40.76,41.07,
65
+ 63,4/4/2016,41.94,88.84,64.86,39.58,38.89,39.57,39.16,39.99,39.99,39.57,38.9,39.16,39.99,40.56,39.52,39.84,39.41,
66
+ 64,4/11/2016,43.1,88.74,68.16,41.87,44.23,41.91,41.46,42.26,42.32,41.91,42.62,41.5,42.33,42.96,41.86,42.01,42.1,
67
+ 65,4/18/2016,45.11,88.64,66.12,43.03,44.27,43.05,42.63,43.42,43.45,43.05,44.87,42.66,43.46,44.15,43.23,43.33,44.07,
68
+ 66,4/25/2016,48.13,88.54,69.67,45.04,47.13,45.08,44.66,45.42,45.47,45.09,46.69,44.71,45.48,46.24,45.18,45.38,46.91,
69
+ 67,5/2/2016,45.37,88.45,69.09,48.07,51.17,48.13,47.71,48.43,48.5,48.14,50.64,47.77,48.52,49.38,48.29,48.5,50.19,
70
+ 68,5/9/2016,47.83,88.36,67.04,45.31,42.61,45.26,44.94,45.68,45.63,45.25,45.67,44.89,45.62,46.36,45.49,45.88,46.34,
71
+ 69,5/16/2016,48.72,88.27,70.99,47.77,50.3,47.81,47.41,48.13,48.19,47.82,47.54,47.46,48.19,48.93,47.61,48.01,48.52,
72
+ 70,5/23/2016,49.32,88.19,68.15,48.66,49.62,48.68,48.31,49.01,49.04,48.68,50.45,48.34,49.04,49.8,48.87,49.05,49.03,
73
+ 71,5/30/2016,49.64,88.1,71.15,49.26,49.93,49.27,48.92,49.61,49.63,49.28,50.09,48.94,49.63,50.37,49.35,49.65,50.65,
74
+ 72,6/6/2016,50.54,88.02,68.65,49.59,49.97,49.59,49.25,49.92,49.94,49.59,50.12,49.26,49.94,50.65,49.64,49.94,50.26,
75
+ 73,6/13/2016,49.17,87.94,71.62,50.49,51.45,50.5,50.72,50.82,50.84,50.51,51.15,50.18,50.85,51.54,50.53,50.8,51.14,
76
+ 74,6/20/2016,48.41,87.85,67.63,49.11,47.81,49.09,48.78,49.45,49.43,49.09,49.01,48.76,49.43,50.03,49.16,49.43,49.21,
77
+ 75,6/27/2016,49.84,87.77,70.45,48.35,47.66,48.34,48.01,48.7,48.69,48.34,47.33,48.01,48.69,49.18,48.24,48.5,47.97,
78
+ 76,7/4/2016,46.76,87.69,69.11,49.79,51.28,49.81,49.45,50.12,50.15,49.81,50.12,49.49,50.16,50.67,49.76,49.84,49.55,
79
+ 77,7/11/2016,47.61,87.6,67.45,46.7,43.68,46.65,46.36,47.05,47,46.65,46.07,46.31,46.99,47.37,46.76,46.87,46.13,
80
+ 78,7/18/2016,45.69,87.51,69.62,47.55,48.47,47.57,47.21,47.89,47.92,47.57,46.39,47.23,47.92,48.26,47.34,47.44,47.18,
81
+ 79,7/25/2016,42.46,87.42,65.84,45.63,43.78,45.6,45.28,45.98,45.95,45.6,45.24,45.26,45.95,46.21,45.67,45.62,44.44,
82
+ 80,8/1/2016,44.27,87.33,66.23,42.39,39.23,42.34,42.03,42.76,42.71,42.33,39.92,41.98,42.7,42.79,42.19,42.23,41.05,
83
+ 81,8/8/2016,46.97,87.24,67.41,44.21,46.09,44.23,43.84,44.56,44.61,44.24,43.42,43.88,44.61,44.75,43.99,43.82,42.97,
84
+ 82,8/15/2016,50.88,87.15,68.7,46.91,49.69,46.95,46.57,47.25,47.31,46.96,49.22,46.62,47.32,47.63,47.1,46.76,47.42,
85
+ 83,8/22/2016,49.92,87.07,70.99,50.83,54.81,50.9,50.51,51.14,51.23,50.91,54.17,50.59,51.25,51.75,51.11,50.93,53.68,
86
+ 84,8/29/2016,46.83,86.99,67.97,49.87,48.97,49.85,49.55,50.19,50.17,49.85,51.54,49.54,50.17,50.69,50.15,50.26,51.99,
87
+ 85,9/5/2016,48.01,86.91,67.81,46.77,43.74,46.72,46.44,47.11,47.05,46.71,44.86,46.39,47.05,47.38,46.65,47,46.81,
88
+ 86,9/12/2016,45.77,86.83,68.93,47.95,49.2,47.97,47.63,48.28,48.32,47.98,46.95,47.66,48.32,48.63,47.75,47.9,46.91,
89
+ 87,9/19/2016,45.89,86.74,65.81,45.71,43.53,45.67,45.38,46.05,46.01,45.67,45.34,45.34,46.01,46.25,45.76,45.77,44.54,
90
+ 88,9/26/2016,49.06,86.66,68.65,45.83,46.02,45.83,45.49,46.17,46.18,45.83,44.77,45.5,46.18,46.38,45.67,45.71,45.48,
91
+ 89,10/3/2016,51.93,86.58,68.86,49.01,52.25,49.06,48.69,49.33,49.4,49.07,50.64,48.75,49.41,49.75,49.07,48.92,49.35,
92
+ 90,10/10/2016,51.95,86.51,71.19,51.88,54.82,51.93,51.58,52.18,52.25,51.94,54.98,51.65,52.26,52.76,52.17,52.07,54.04,
93
+ 91,10/17/2016,51.78,86.43,69.03,51.9,51.98,51.9,51.61,52.2,52.21,51.9,53.48,51.62,52.21,52.73,52.11,52.27,54.07,
94
+ 92,10/24/2016,49.71,86.36,70.76,51.73,51.62,51.73,51.44,52.03,52.03,51.73,51.72,51.45,52.03,52.51,51.73,52.03,52.68,
95
+ 93,10/31/2016,45.58,86.29,67.24,49.66,47.64,49.62,49.36,49.97,49.93,49.62,48.64,49.33,49.93,50.28,49.61,49.88,49.03,
96
+ 94,11/7/2016,44.75,86.2,66.6,45.52,41.45,45.44,45.2,45.86,45.77,45.43,42.53,45.12,45.76,45.9,45.29,45.53,43.49,
97
+ 95,11/14/2016,46.86,86.12,66.34,44.69,43.93,44.67,44.36,45.03,45.02,44.67,42.19,44.35,45.02,45.05,44.38,44.4,42.29,
98
+ 96,11/21/2016,47.24,86.03,68.4,46.8,48.98,46.84,46.48,47.13,47.19,46.85,47.44,46.54,47.19,47.32,46.79,46.53,45.87,
99
+ 97,11/28/2016,54.46,85.95,66.79,47.18,47.63,47.19,46.87,47.51,47.52,47.19,48.54,46.89,47.53,47.73,47.34,47.12,47.88,
100
+ 98,12/5/2016,54.33,85.89,74.72,54.42,61.7,54.56,54.14,54.69,54.87,54.58,58.11,54.31,54.89,55.36,54.6,54.43,57.51,
101
+ 99,12/12/2016,55.21,85.83,67.36,54.29,54.21,54.28,54.02,54.56,54.56,54.29,58.09,54.03,54.56,55.15,54.82,54.81,57.14,
102
+ 100,12/19/2016,55.16,85.76,74.76,55.17,56.1,55.19,54.91,55.43,55.46,55.19,55.57,54.94,55.46,56.03,55.18,55.58,57.77,
103
+ 101,12/26/2016,56.13,85.7,67.95,55.12,55.12,55.12,54.86,55.38,55.39,55.12,55.61,54.87,55.39,55.92,55.19,55.51,55.44,
104
+ 102,1/2/2017,57.1,85.64,74.94,56.09,57.11,56.11,55.84,56.35,56.37,56.11,56.57,55.87,56.38,56.89,56.11,56.41,56.7,
105
+ 103,1/9/2017,55.45,85.58,69.42,57.06,58.08,57.08,56.82,57.31,57.34,57.09,58.08,56.85,57.34,57.86,57.16,57.39,57.76,
106
+ 104,1/16/2017,55.49,85.52,72.87,55.41,53.81,55.38,55.16,55.67,55.64,55.38,55.18,55.13,55.63,56.07,55.45,55.73,55.63,
107
+ 105,1/23/2017,55.52,85.46,69.72,55.45,55.54,55.45,55.2,55.71,55.72,55.45,54.65,55.21,55.72,56.08,55.33,55.59,55.2,
108
+ 106,1/30/2017,56.81,85.4,72.54,55.48,55.56,55.48,55.23,55.74,55.74,55.48,55.56,55.24,55.75,56.09,55.49,55.6,55.02,
109
+ 107,2/6/2017,56.7,85.34,71.09,56.77,58.11,56.8,56.53,57.02,57.05,56.8,57.45,56.57,57.06,57.42,56.8,56.88,57.24,
110
+ 108,2/13/2017,55.81,85.28,72.25,56.66,56.6,56.66,56.43,56.91,56.91,56.66,57.34,56.43,56.91,57.27,56.76,56.84,57.17,
111
+ 109,2/20/2017,55.99,85.23,70.33,55.77,54.93,55.76,55.53,56.02,56.01,55.75,55.34,55.52,56.01,56.31,55.75,55.9,55.92,
112
+ 110,2/27/2017,55.9,85.17,72.17,55.95,56.18,55.96,55.71,56.2,56.21,55.96,55.62,55.72,56.21,56.48,55.89,56,55.68,
113
+ 111,3/6/2017,51.37,85.11,70.36,55.86,55.82,55.86,55.62,56.11,56.12,55.86,55.96,55.63,56.12,56.37,55.88,55.91,55.66,
114
+ 112,3/13/2017,51.76,85.04,67.83,51.32,46.84,51.24,51.07,51.61,51.51,51.23,49.17,50.97,51.5,51.58,51.23,51.34,50.01,
115
+ 113,3/20/2017,50.8,84.97,70.4,51.71,52.16,51.72,51.45,51.99,52.01,51.72,49.56,51.47,52.01,52.02,51.39,51.41,50.16,
116
+ 114,3/27/2017,52.83,84.91,67.13,50.75,49.85,50.73,50.49,51.04,51.02,50.73,50.56,50.47,51.02,51.03,50.77,50.54,49.2,
117
+ 115,4/3/2017,55.24,84.84,71.87,52.79,54.87,52.82,52.53,53.06,53.11,52.83,53.3,52.58,53.12,53.2,52.76,52.56,53.23,
118
+ 116,4/10/2017,55.89,84.78,69.7,55.2,57.66,55.25,54.96,55.45,55.51,55.25,57.47,55.02,55.52,55.75,55.4,55.18,56.44,
119
+ 117,4/17/2017,51.96,84.73,72.2,55.85,56.55,55.86,55.62,56.1,56.12,55.87,57.48,55.64,56.12,56.42,56.05,56.01,57.66,
120
+ 118,4/24/2017,51.73,84.66,66.3,51.91,48.03,51.84,51.67,52.19,52.11,51.83,50.44,51.59,52.1,52.25,51.89,52.07,51.77,
121
+ 119,5/1/2017,49.1,84.6,71.38,51.68,51.51,51.68,51.43,51.96,51.96,51.68,49.56,51.43,51.96,52.03,51.4,51.54,50.4,
122
+ 120,5/8/2017,50.84,84.53,64.31,49.05,46.47,49,48.79,49.34,49.29,48.99,47.73,48.74,49.28,49.27,48.98,48.91,46.95,
123
+ 121,5/15/2017,53.61,84.46,72.24,50.79,52.59,50.83,50.53,51.07,51.12,50.83,50.29,50.58,51.13,51.14,50.64,50.51,50.32,
124
+ 122,5/22/2017,52.15,84.4,67.49,53.57,56.39,53.62,53.32,53.83,53.9,53.63,55.86,53.39,53.91,54.08,53.75,53.48,54.29,
125
+ 123,5/29/2017,49.95,84.34,70.41,52.11,50.7,52.08,51.86,52.38,52.35,52.08,52.92,51.84,52.35,52.53,52.28,52.23,53.31,
126
+ 124,6/5/2017,48.15,84.27,65.69,49.9,47.75,49.86,49.65,50.19,50.14,49.85,48.14,49.61,50.14,50.22,49.76,49.89,49.62,
127
+ 125,6/12/2017,47.37,84.2,68.27,48.1,46.36,48.06,47.83,48.39,48.36,48.06,46.14,47.8,48.36,48.34,47.91,47.93,46.31,
128
+ 126,6/19/2017,45.54,84.13,65.14,47.32,46.6,47.3,47.05,47.62,47.61,47.3,46.06,47.04,47.6,47.55,47.18,47.06,45.76,
129
+ 127,6/26/2017,47.92,84.05,66.25,45.48,43.71,45.45,45.21,45.79,45.76,45.44,44.26,45.17,45.75,45.66,45.39,45.22,44.11,
130
+ 128,7/3/2017,46.71,83.98,67.33,47.87,50.31,47.92,47.6,48.16,48.22,47.92,48.1,47.66,48.23,48.22,47.79,47.55,47.73,
131
+ 129,7/10/2017,48.91,83.91,65.18,46.66,45.51,46.63,46.39,46.96,46.94,46.63,47.39,46.37,46.93,46.97,46.81,46.57,46.65,
132
+ 130,7/17/2017,48.06,83.85,69.06,48.86,51.12,48.9,48.6,49.15,49.2,48.91,49.33,48.65,49.21,49.31,48.82,48.72,49.9,
133
+ 131,7/24/2017,52.52,83.78,64.69,48.01,47.22,47.99,47.75,48.3,48.29,47.99,48.82,47.74,48.29,48.42,48.16,48.05,48.25,
134
+ 132,7/31/2017,52.42,83.72,72.65,52.48,57,52.56,52.24,52.74,52.84,52.57,54.2,52.33,52.85,53.13,52.5,52.47,54.28,
135
+ 133,8/7/2017,52.1,83.66,65.26,52.38,52.33,52.37,52.14,52.64,52.64,52.38,54.74,52.15,52.64,52.99,52.71,52.69,53.82,
136
+ 134,8/14/2017,52.72,83.6,71.63,52.06,51.79,52.05,51.82,52.32,52.32,52.05,51.9,51.82,52.32,52.63,52.05,52.3,53.39,
137
+ 135,8/21/2017,52.41,83.54,66.34,52.68,53.35,52.69,52.45,52.93,52.95,52.69,52.85,52.47,52.95,53.26,52.67,52.85,52.77,
138
+ 136,8/28/2017,52.32,83.48,70.81,52.37,52.11,52.36,52.14,52.62,52.62,52.36,52.6,52.14,52.62,52.91,52.41,52.55,52.46,
139
+ 137,9/4/2017,53.78,83.42,66.6,52.28,52.24,52.28,52.05,52.53,52.54,52.28,52.12,52.05,52.54,52.8,52.26,52.4,52.38,
140
+ 138,9/11/2017,55.62,83.36,71.7,53.74,55.25,53.77,53.52,53.98,54.02,53.77,54.43,53.55,54.03,54.32,53.76,53.84,54.11,
141
+ 139,9/18/2017,56.86,83.31,68.68,55.58,57.47,55.62,55.37,55.81,55.86,55.62,57.27,55.42,55.86,56.23,55.73,55.77,56.72,
142
+ 140,9/25/2017,57.54,83.26,72.51,56.83,58.11,56.85,56.62,57.05,57.08,56.85,58.43,56.66,57.08,57.5,56.99,57.11,58.41,
143
+ 141,10/2/2017,55.62,83.21,69.59,57.51,58.23,57.52,57.31,57.72,57.74,57.52,58.53,57.33,57.74,58.17,57.61,57.83,58.81,
144
+ 142,10/9/2017,57.17,83.16,70.45,55.58,53.7,55.55,55.38,55.81,55.78,55.54,55.07,55.35,55.77,56.1,55.6,55.88,55.69,
145
+ 143,10/16/2017,57.75,83.11,71.02,57.14,58.73,57.17,56.94,57.35,57.39,57.17,56.9,56.98,57.4,57.71,57.03,57.24,57.14,
146
+ 144,10/23/2017,60.44,83.06,70.98,57.72,58.34,57.73,57.53,57.93,57.94,57.73,58.85,57.54,57.95,58.29,57.85,57.92,57.91,
147
+ 145,10/30/2017,62.07,83.02,73.42,60.41,63.14,60.46,60.23,60.6,60.66,60.47,62.03,60.3,60.67,61.09,60.51,60.62,61.99,
148
+ 146,11/6/2017,63.52,82.98,72.65,62.05,63.71,62.08,61.88,62.22,62.26,62.08,64.27,61.92,62.26,62.76,62.28,62.41,63.78,
149
+ 147,11/13/2017,62.72,82.95,74.64,63.5,64.98,63.53,63.34,63.66,63.69,63.53,65.08,63.38,63.7,64.22,63.65,63.91,65.44,
150
+ 148,11/20/2017,63.86,82.91,72.06,62.7,61.93,62.68,62.54,62.86,62.85,62.68,63.11,62.53,62.85,63.31,62.79,63.12,63.55,
151
+ 149,11/27/2017,63.49,82.87,75.41,63.84,65.01,63.86,63.69,64,64.02,63.86,63.99,63.72,64.03,64.47,63.8,64.13,64.37,
152
+ 150,12/4/2017,63.4,82.84,71.98,63.47,63.13,63.46,63.32,63.63,63.62,63.46,63.92,63.31,63.62,64.02,63.55,63.78,63.56,
153
+ 151,12/11/2017,63.23,82.8,74.98,63.38,63.32,63.38,63.23,63.54,63.54,63.38,63.17,63.23,63.54,63.89,63.35,63.6,63.6,
154
+ 152,12/18/2017,65.25,82.76,72.06,63.21,63.07,63.21,63.06,63.37,63.37,63.21,63.11,63.06,63.37,63.67,63.2,63.38,63.03,
155
+ 153,12/25/2017,66.6,82.73,76.53,65.23,67.28,65.27,65.09,65.37,65.42,65.28,66.13,65.14,65.43,65.77,65.26,65.36,65.79,
156
+ 154,1/1/2018,67.62,82.7,73.66,66.58,67.96,66.61,66.45,66.71,66.75,66.61,68.32,66.48,66.75,67.15,66.76,66.84,67.74,
157
+ 155,1/8/2018,69.87,82.67,77.17,67.61,68.65,67.63,67.48,67.73,67.75,67.63,68.82,67.5,67.76,68.17,67.73,67.91,69.09,
158
+ 156,1/15/2018,68.61,82.65,76,69.86,72.13,69.9,69.74,69.96,70.01,69.91,71.49,69.8,70.02,70.49,69.99,70.18,71.39,
159
+ 157,1/22/2018,70.52,82.63,75.9,68.6,67.36,68.57,68.48,68.71,68.68,68.57,69.21,68.45,68.68,69.1,68.74,69,69.41,
160
+ 158,1/29/2018,68.58,82.6,77.71,70.51,72.44,70.55,70.4,70.6,70.65,70.55,70.77,70.45,70.66,71.06,70.45,70.76,71.35,
161
+ 159,2/5/2018,62.79,82.58,74.27,68.57,66.64,68.53,68.45,68.68,68.64,68.53,68.68,68.41,68.63,68.96,68.68,68.89,68.32,
162
+ 160,2/12/2018,64.84,82.54,72.09,62.77,57,62.66,62.63,62.93,62.8,62.64,59.02,62.49,62.78,62.84,62.5,62.85,60.88,
163
+ 161,2/19/2018,67.31,82.51,75.91,64.82,66.9,64.86,64.68,64.97,65.02,64.86,62.76,64.73,65.02,65.03,64.43,64.51,62.66,
164
+ 162,2/26/2018,64.37,82.48,74.65,67.3,69.79,67.34,67.17,67.42,67.47,67.35,69.57,67.23,67.48,67.63,67.49,67.2,67.01,
165
+ 163,3/5/2018,65.49,82.45,73.08,64.35,61.43,64.3,64.22,64.5,64.44,64.29,64.28,64.16,64.43,64.52,64.47,64.44,65.06,
166
+ 164,3/12/2018,66.21,82.42,75.5,65.47,66.62,65.49,65.34,65.61,65.64,65.5,64.48,65.36,65.64,65.71,65.29,65.34,65.53,
167
+ 165,3/19/2018,70.45,82.39,73.93,66.19,66.94,66.21,66.06,66.33,66.34,66.21,67.15,66.08,66.35,66.46,66.29,66.17,65.91,
168
+ 166,3/26/2018,70.27,82.37,79.2,70.44,74.71,70.52,70.33,70.53,70.63,70.53,72.86,70.42,70.64,70.91,70.57,70.49,72.39,
169
+ 167,4/2/2018,67.11,82.35,74.21,70.26,70.1,70.26,70.16,70.36,70.35,70.26,72.43,70.15,70.35,70.67,70.56,70.59,72.05,
170
+ 168,4/9/2018,72.58,82.32,75.85,67.1,63.95,67.04,66.98,67.22,67.16,67.03,65.51,66.91,67.15,67.32,67.02,67.33,67.43,
171
+ 169,4/16/2018,74.06,82.3,79.32,72.58,78.07,72.66,72.47,72.65,72.75,72.67,73.53,72.58,72.77,73.06,72.45,72.55,73.02,
172
+ 170,4/23/2018,74.64,82.29,77.49,74.06,75.55,74.08,73.97,74.12,74.14,74.09,77.65,74,74.15,74.56,74.46,74.43,75.54,
173
+ 171,4/30/2018,74.87,82.27,79.67,74.64,75.23,74.65,74.56,74.69,74.7,74.65,75.7,74.57,74.71,75.11,74.75,75.04,77.15,
174
+ 172,5/7/2018,77.12,82.26,77.88,74.87,75.11,74.87,74.79,74.92,74.93,74.87,75.29,74.8,74.93,75.3,74.91,75.23,75.64,
175
+ 173,5/14/2018,78.51,82.25,81.55,77.12,79.38,77.16,77.05,77.15,77.2,77.17,78.32,77.1,77.2,77.62,77.18,77.43,78.09,
176
+ 174,5/21/2018,76.44,82.24,79.47,78.52,79.91,78.54,78.45,78.53,78.56,78.54,80.36,78.48,78.56,79.02,78.69,78.92,79.86,
177
+ 175,5/28/2018,77.59,82.23,79.47,76.44,74.37,76.41,76.38,76.48,76.44,76.4,76.19,76.33,76.43,76.78,76.5,76.86,77.06,
178
+ 176,6/4/2018,76.46,82.23,80.51,77.6,78.75,77.61,77.53,77.62,77.64,77.62,77.06,77.55,77.64,77.95,77.47,77.78,77.63,
179
+ 177,6/11/2018,73.44,82.21,78.53,76.46,75.34,76.44,76.39,76.5,76.48,76.44,76.53,76.37,76.47,76.72,76.52,76.69,75.88,
180
+ 178,6/18/2018,75.55,82.2,77.57,73.44,70.42,73.39,73.36,73.5,73.44,73.38,71.41,73.3,73.43,73.52,73.31,73.53,72.47,
181
+ 179,6/25/2018,79.44,82.19,80.35,75.55,77.67,75.59,75.47,75.59,75.64,75.59,74.98,75.52,75.64,75.74,75.38,75.42,74.71,
182
+ 180,7/2/2018,77.11,82.18,81.35,79.45,83.34,79.51,79.39,79.45,79.53,79.52,82.42,79.47,79.54,79.8,79.65,79.5,80.45,
183
+ 181,7/9/2018,75.33,82.17,78.31,77.11,74.78,77.08,77.05,77.14,77.1,77.07,78.04,77.01,77.09,77.31,77.33,77.42,78.53,
184
+ 182,7/16/2018,73.07,82.16,79.45,75.33,73.55,75.3,75.26,75.38,75.34,75.3,73.27,75.22,75.34,75.43,75.15,75.41,75.2,
185
+ 183,7/23/2018,74.29,82.15,76.33,73.07,70.81,73.03,72.98,73.13,73.09,73.02,71.06,72.94,73.08,73.06,72.91,73,70.96,
186
+ 184,7/30/2018,73.21,82.13,80.27,74.29,75.52,74.31,74.21,74.34,74.37,74.31,73.7,74.23,74.37,74.35,74.17,74.09,73.26,
187
+ 185,8/6/2018,72.81,82.12,75.68,73.21,72.14,73.19,73.12,73.27,73.25,73.19,73.34,73.1,73.25,73.23,73.27,73.13,72.6,
188
+ 186,8/13/2018,71.83,82.1,79.48,72.81,72.42,72.8,72.72,72.88,72.87,72.8,72.06,72.71,72.87,72.82,72.73,72.67,72.69,
189
+ 187,8/20/2018,75.82,82.08,75.11,71.82,70.86,71.81,71.73,71.9,71.89,71.81,71.16,71.72,71.88,71.81,71.78,71.69,71.04,
190
+ 188,8/27/2018,77.42,82.07,82.72,75.82,79.82,75.88,75.74,75.86,75.94,75.89,77.23,75.82,75.95,76.01,75.83,75.65,76.57,
191
+ 189,9/3/2018,76.83,82.06,77.24,77.42,79.03,77.45,77.36,77.45,77.48,77.45,80.28,77.39,77.49,77.67,77.71,77.56,79.08,
192
+ 190,9/10/2018,78.09,82.05,81.68,76.83,76.25,76.82,76.77,76.86,76.85,76.82,77.39,76.76,76.85,77.02,76.92,77.05,78.54,
193
+ 191,9/17/2018,78.8,82.05,78.77,78.1,79.36,78.12,78.03,78.11,78.14,78.12,78.39,78.06,78.14,78.33,78.08,78.23,78.79,
194
+ 192,9/24/2018,82.72,82.04,82.07,78.81,79.52,78.82,78.75,78.82,78.83,78.82,79.81,78.77,78.83,79.04,78.9,79,79.3,
195
+ 193,10/1/2018,84.16,82.04,82.64,82.73,86.65,82.8,82.69,82.71,82.78,82.81,84.98,82.77,82.8,83.12,82.85,82.95,84.61,
196
+ 194,10/8/2018,80.43,82.05,83.43,84.18,85.61,84.2,84.15,84.13,84.16,84.2,86.91,84.18,84.17,84.58,84.45,84.62,86.29,
197
+ 195,10/15/2018,79.78,82.04,79.31,80.44,76.7,80.38,80.4,80.43,80.36,80.37,79.4,80.32,80.35,80.6,80.46,80.87,81.09,
198
+ 196,10/22/2018,77.62,82.04,82.47,79.79,79.14,79.78,79.74,79.79,79.78,79.78,77.53,79.73,79.77,79.9,79.55,79.88,78.68,
199
+ 197,10/29/2018,72.83,82.03,77.62,77.62,75.46,77.59,77.57,77.65,77.6,77.58,76.25,77.52,77.6,77.62,77.54,77.65,75.5,77.67
200
+ 198,11/5/2018,70.18,82.02,77.66,72.83,68.04,72.74,72.75,72.9,72.79,72.73,69.41,72.64,72.78,72.61,72.59,72.67,70.34,72.73
201
+ 199,11/12/2018,66.76,82,75.19,70.17,67.53,70.12,70.08,70.27,70.21,70.11,66.41,70.02,70.2,69.87,69.81,69.72,66.9,70.4
202
+ 200,11/19/2018,58.8,81.97,74.3,66.75,63.34,66.67,66.64,66.87,66.79,66.66,63.74,66.55,66.78,66.34,66.49,66.18,63.17,67.02
203
+ 201,11/26/2018,58.71,81.93,67.82,58.77,50.83,58.58,58.63,58.97,58.76,58.55,53.19,58.4,58.72,58.03,58.33,57.99,54.22,59.48
204
+ 202,12/3/2018,61.67,81.89,73.6,58.68,58.63,58.69,58.53,58.88,58.89,58.68,54.51,58.53,58.89,58.09,58.13,57.56,54.64,58.81
205
+ 203,12/10/2018,60.28,81.86,70.99,61.65,64.64,61.72,61.5,61.82,61.91,61.73,63.06,61.6,61.92,61.35,61.72,60.83,59.96,61.88
206
+ 204,12/17/2018,53.82,81.82,72.07,60.26,58.9,60.22,60.11,60.44,60.4,60.22,61.16,60.08,60.4,59.97,60.41,59.77,60.9,60.63
207
+ 205,12/24/2018,52.2,81.78,65.15,53.78,47.36,53.62,53.62,54.02,53.84,53.6,49.97,53.43,53.82,53.25,53.53,53.23,52.27,54.83
208
+ 206,12/31/2018,57.06,81.73,69.93,52.16,50.58,52.12,51.98,52.41,52.38,52.11,48.07,51.94,52.37,51.67,51.72,51.3,48.91,52.54
209
+ 207,1/7/2019,60.48,81.68,69.96,57.03,61.94,57.16,56.86,57.24,57.39,57.17,58.6,57.01,57.41,56.93,57.07,56.34,55.89,56.62
210
+ 208,1/14/2019,62.7,81.65,73.01,60.46,63.91,60.55,60.31,60.64,60.75,60.56,64.66,60.43,60.77,60.6,60.83,60.26,62.79,60.64
211
+ 209,1/21/2019,61.64,81.62,72.22,62.68,64.93,62.74,62.55,62.84,62.92,62.75,65.55,62.63,62.93,62.96,62.95,62.76,66.22,63.03
212
+ 210,1/28/2019,61.87,81.58,71.94,61.62,60.59,61.59,61.48,61.79,61.76,61.58,62.27,61.46,61.76,61.84,61.71,61.78,63.21,61.98
213
+ 211,2/4/2019,62.1,81.55,72.37,61.85,62.11,61.86,61.71,62.02,62.03,61.86,61.45,61.73,62.03,62.09,61.8,61.92,62.3,62.18
214
+ 212,2/11/2019,66.25,81.52,72.16,62.08,62.34,62.09,61.95,62.25,62.26,62.09,62.34,61.96,62.26,62.33,62.1,62.16,61.92,62.42
215
+ 213,2/18/2019,67.12,81.49,76.11,66.24,70.41,66.36,66.12,66.37,66.5,66.37,68.41,66.26,66.52,66.7,66.38,66.38,67.75,66.82
216
+ 214,2/25/2019,66.01,81.47,73.28,67.11,68,67.13,67,67.23,67.26,67.14,69.68,67.03,67.27,67.58,67.37,67.46,68.96,67.55
217
+ 215,3/4/2019,65.74,81.44,74.82,66,64.91,65.96,65.89,66.13,66.09,65.96,65.92,65.85,66.09,66.37,66.01,66.3,67.32,66.37
218
+ 216,3/11/2019,67.16,81.42,73.14,65.73,65.48,65.72,65.61,65.86,65.86,65.72,65.05,65.61,65.85,66.06,65.66,65.9,65.55,66.14
219
+ 217,3/18/2019,67.03,81.39,75.94,67.15,68.59,67.19,67.04,67.27,67.32,67.19,67.72,67.09,67.32,67.53,67.18,67.3,67.17,67.65
220
+ 218,3/25/2019,68.39,81.37,73.25,67.02,66.91,67.01,66.91,67.14,67.14,67.01,67.7,66.91,67.14,67.37,67.09,67.21,67.41,67.43
221
+ 219,4/1/2019,70.34,81.35,76.92,68.38,69.76,68.42,68.28,68.49,68.54,68.42,69,68.33,68.54,68.77,68.41,68.55,69.25,68.9
222
+ 220,4/8/2019,71.55,81.33,75.33,70.33,72.3,70.39,70.24,70.42,70.49,70.4,72,70.31,70.5,70.79,70.47,70.58,71.42,70.88
223
+ 221,4/15/2019,71.97,81.31,77.87,71.54,72.77,71.58,71.46,71.62,71.66,71.58,73.15,71.51,71.67,72.02,71.69,71.86,73.08,72.01
224
+ 222,4/22/2019,72.15,81.3,75.92,71.97,72.4,71.98,71.89,72.04,72.05,71.98,72.8,71.9,72.06,72.41,72.05,72.29,73.18,72.35
225
+ 223,4/29/2019,70.85,81.28,77.85,72.15,72.34,72.15,72.07,72.22,72.23,72.15,72.46,72.08,72.23,72.55,72.17,72.43,72.76,72.52
226
+ 224,5/6/2019,70.62,81.27,74.89,70.84,69.56,70.8,70.76,70.93,70.89,70.8,70.31,70.72,70.88,71.14,70.81,71.05,70.64,71.11
227
+ 225,5/13/2019,72.21,81.25,77.36,70.61,70.4,70.61,70.53,70.7,70.7,70.61,69.85,70.52,70.69,70.87,70.53,70.71,70.15,71
228
+ 226,5/20/2019,68.69,81.24,76.54,72.21,73.81,72.25,72.13,72.28,72.33,72.26,72.88,72.19,72.34,72.53,72.24,72.3,72.23,72.73
229
+ 227,5/27/2019,64.49,81.22,74.06,68.68,65.17,68.58,68.59,68.78,68.67,68.57,67.79,68.48,68.66,68.8,68.66,68.78,68.05,68.83
230
+ 228,6/3/2019,63.29,81.19,72.47,64.47,60.29,64.35,64.37,64.62,64.48,64.33,60.63,64.22,64.46,64.39,64.14,64.28,62.41,64.81
231
+ 229,6/10/2019,62.01,81.16,72.79,63.27,62.1,63.24,63.15,63.43,63.39,63.23,60.56,63.12,63.39,63.17,63,62.88,60.28,63.65
232
+ 230,6/17/2019,65.2,81.13,71.3,61.99,60.73,61.95,61.87,62.16,62.12,61.94,60.77,61.83,62.11,61.88,61.88,61.59,59.81,62.36
233
+ 231,6/24/2019,66.55,81.1,75.54,65.18,68.4,65.29,65.07,65.32,65.44,65.3,66.12,65.19,65.45,65.29,65.22,64.88,65.4,65.67
234
+ 232,7/1/2019,64.23,81.08,72.88,66.54,67.91,66.58,66.43,66.66,66.71,66.58,68.85,66.49,66.72,66.72,66.76,66.48,67.71,67.01
235
+ 233,7/8/2019,66.72,81.05,73.17,64.21,61.91,64.14,64.1,64.36,64.28,64.13,63.79,64.03,64.27,64.29,64.21,64.19,64.99,64.57
236
+ 234,7/15/2019,62.47,81.03,75.15,66.71,69.22,66.79,66.6,66.83,66.92,66.79,66.76,66.7,66.93,66.93,66.66,66.62,67.16,67.26
237
+ 235,7/22/2019,63.46,81,69.44,62.45,58.22,62.32,62.34,62.61,62.48,62.31,61.67,62.2,62.46,62.46,62.46,62.44,61.23,62.83
238
+ 236,7/29/2019,61.89,80.97,75.52,63.44,64.46,63.47,63.33,63.59,63.63,63.47,61.77,63.36,63.63,63.54,63.23,63.23,63.08,63.81
239
+ 237,8/5/2019,58.53,80.94,68.51,61.87,60.32,61.82,61.75,62.04,61.99,61.82,61.64,61.7,61.99,61.91,61.88,61.73,60.37,62.24
240
+ 238,8/12/2019,58.64,80.9,71.8,58.5,55.17,58.41,58.37,58.7,58.6,58.4,56.09,58.27,58.58,58.41,58.31,58.25,57.22,58.96
241
+ 239,8/19/2019,59.34,80.87,68.86,58.61,58.76,58.62,58.48,58.81,58.82,58.62,56.97,58.49,58.82,58.59,58.43,58.24,56.98,58.78
242
+ 240,8/26/2019,60.43,80.84,72.15,59.32,60.05,59.34,59.18,59.5,59.53,59.34,59.75,59.21,59.53,59.37,59.34,59.04,58.52,59.52
243
+ 241,9/2/2019,61.54,80.8,70.11,60.41,61.53,60.44,60.28,60.58,60.62,60.44,61.33,60.32,60.63,60.55,60.48,60.25,61.07,60.65
244
+ 242,9/9/2019,60.22,80.77,72.95,61.52,62.66,61.55,61.4,61.69,61.73,61.56,62.65,61.44,61.73,61.74,61.62,61.47,62.52,61.82
245
+ 243,9/16/2019,64.28,80.74,69.12,60.2,58.9,60.16,60.07,60.38,60.34,60.16,60.15,60.03,60.33,60.36,60.22,60.2,60.55,60.55
246
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248
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249
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250
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251
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252
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253
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254
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255
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256
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258
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259
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341
+ 339,7/19/2021,74.1,77.11,72.57,73.59,71.63,73.51,73.57,73.62,73.53,73.49,72.31,73.47,73.52,73.75,73.46,73.72,72.71,73.72
342
+ 340,7/26/2021,76.33,77.1,78.52,74.1,74.62,74.12,74.08,74.12,74.15,74.12,73.37,74.1,74.15,74.27,74.01,74.14,73.39,74.5
343
+ 341,8/2/2021,70.7,77.1,75.1,76.33,78.57,76.43,76.32,76.33,76.44,76.44,77.7,76.43,76.45,76.59,76.46,76.46,76.66,76.87
344
+ 342,8/9/2021,70.59,77.09,73.06,70.69,65.07,70.46,70.67,70.75,70.49,70.43,69.05,70.4,70.47,70.62,70.58,70.7,69.75,70.56
345
+ 343,8/16/2021,65.18,77.09,74.82,70.58,70.49,70.59,70.55,70.64,70.65,70.58,67.68,70.55,70.64,70.53,70.26,70.37,69.27,71.02
346
+ 344,8/23/2021,72.7,77.07,68.22,65.17,59.77,64.94,65.12,65.27,65.03,64.92,62.46,64.86,65,64.85,64.93,64.82,61.58,65.4
347
+ 345,8/30/2021,72.61,77.06,81.19,72.7,80.24,72.98,72.66,72.73,73.04,73,73.62,72.98,73.07,72.85,72.66,72.42,73.23,73.95
348
+ 346,9/6/2021,72.92,77.06,69.18,72.61,72.53,72.59,72.58,72.64,72.63,72.6,76.43,72.58,72.64,72.74,73.06,72.71,73.64,72.83
349
+ 347,9/13/2021,75.34,77.05,80.49,72.92,73.24,72.93,72.89,72.95,72.96,72.93,73.03,72.91,72.97,73.05,72.92,73,75.32,73.29
350
+ 348,9/20/2021,78.09,77.05,72.33,75.34,77.77,75.43,75.32,75.35,75.45,75.44,76.69,75.42,75.46,75.58,75.45,75.48,76.24,75.91
351
+ 349,9/27/2021,79.28,77.05,82.35,78.09,80.85,78.19,78.09,78.08,78.19,78.21,80.68,78.2,78.2,78.44,78.35,78.39,79.98,78.66
352
+ 350,10/4/2021,82.39,77.05,74.24,79.29,80.48,79.33,79.28,79.26,79.3,79.34,81.28,79.34,79.31,79.63,79.5,79.66,81.42,79.66
353
+ 351,10/11/2021,84.86,77.06,84.55,82.4,85.51,82.52,82.41,82.34,82.47,82.53,84.53,82.54,82.49,82.85,82.6,82.83,84.71,83.07
354
+ 352,10/18/2021,85.53,77.07,77.36,84.87,87.34,84.96,84.89,84.8,84.89,84.98,87.67,85,84.91,85.37,85.16,85.42,87.18,85.51
355
+ 353,10/25/2021,84.38,77.08,84.58,85.54,86.21,85.57,85.57,85.46,85.48,85.57,87.13,85.6,85.49,85.97,85.72,86.09,87.61,86
356
+ 354,11/1/2021,82.74,77.09,76.91,84.39,83.23,84.35,84.41,84.32,84.27,84.34,84.16,84.36,84.26,84.67,84.39,84.81,85,84.63
357
+ 355,11/8/2021,82.17,77.1,82.46,82.75,81.1,82.69,82.77,82.69,82.62,82.68,81.35,82.69,82.61,82.88,82.61,82.98,81.99,82.91
358
+ 356,11/15/2021,78.89,77.11,76.85,82.18,81.61,82.16,82.19,82.13,82.1,82.15,81.06,82.17,82.1,82.25,82.05,82.27,81.04,82.45
359
+ 357,11/22/2021,72.72,77.11,78.99,78.9,75.61,78.77,78.9,78.87,78.74,78.75,76.99,78.75,78.72,78.77,78.72,78.84,77.09,78.82
360
+ 358,11/29/2021,69.88,77.1,71.36,72.72,66.55,72.47,72.7,72.75,72.49,72.43,68.02,72.4,72.44,72.28,72.24,72.34,69.3,72.51
361
+ 359,12/6/2021,75.15,77.09,75.74,69.87,67.04,69.76,69.84,69.94,69.82,69.74,65.34,69.7,69.79,69.36,69.35,69.23,65.7,70.11
362
+ 360,12/13/2021,73.52,77.09,76.55,75.15,80.43,75.37,75.13,75.16,75.4,75.39,76.32,75.38,75.43,75.02,75.21,74.74,74.01,76.13
363
+ 361,12/20/2021,76.85,77.09,74.31,73.52,71.89,73.44,73.5,73.55,73.47,73.44,75.41,73.42,73.47,73.33,73.76,73.35,73.98,73.6
364
+ 362,12/27/2021,79.2,77.09,79.42,76.85,80.19,76.99,76.84,76.85,77,77,77.66,76.99,77.01,76.87,76.89,76.76,79.01,77.55
365
+ 363,1/3/2022,81.75,77.09,76.89,79.21,81.56,79.29,79.2,79.18,79.28,79.31,82.06,79.31,79.3,79.34,79.51,79.34,80.69,79.71
366
+ 364,1/10/2022,86.06,77.1,81.56,81.76,84.31,81.86,81.77,81.71,81.82,81.88,84.21,81.89,81.84,82,82.01,82.03,84.48,82.33
367
+ 365,1/17/2022,87.89,77.11,81.24,86.08,90.38,86.25,86.1,85.98,86.17,86.28,89.49,86.31,86.2,86.49,86.43,86.53,89.15,86.98
368
+ 366,1/24/2022,90.03,77.12,83.23,87.91,89.73,87.98,87.94,87.8,87.87,87.99,90.99,88.03,87.89,88.33,88.26,88.48,90.84,88.55
369
+ 367,1/31/2022,93.27,77.14,83.39,90.05,92.18,90.14,90.09,89.92,90.02,90.15,92.02,90.19,90.03,90.49,90.26,90.64,92.74,90.82
370
+ 368,2/7/2022,94.44,77.16,86.24,93.29,96.52,93.43,93.34,93.14,93.28,93.45,95.96,93.51,93.31,93.81,93.58,93.95,95.69,94.25
371
+ 369,2/14/2022,93.54,77.18,84.72,94.47,95.62,94.51,94.52,94.3,94.34,94.52,96.67,94.58,94.36,94.92,94.73,95.13,96.66,95.15
372
+ 370,2/21/2022,97.93,77.2,85.31,93.56,92.64,93.52,93.62,93.41,93.36,93.52,93.7,93.57,93.35,93.85,93.6,94.08,94.66,94.03
373
+ 371,2/28/2022,118.11,77.23,88.82,97.96,102.33,98.15,98.03,97.77,97.97,98.17,99.64,98.24,97.99,98.4,98.1,98.48,99.44,98.98
374
+ 372,3/7/2022,112.67,77.29,104.19,118.17,138.32,119.22,119.13,117.81,118.92,119.37,130.38,119.52,119.08,119.74,119.58,119.66,126.28,118.67
375
+ 373,3/14/2022,107.93,77.33,85.13,112.72,107.23,112.47,112.86,112.4,112.11,112.48,120.58,112.6,112.12,113.51,113.71,114.38,119.6,111.42
376
+ 374,3/21/2022,120.65,77.37,98.32,107.97,103.19,107.78,108.09,107.69,107.47,107.75,102.84,107.85,107.43,108.28,107.5,108.76,111.07,107.26
377
+ 375,3/28/2022,107.67,77.43,97.94,120.71,133.39,121.19,121.39,120.34,120.85,121.21,124.66,121.37,120.88,121.61,121.01,121.56,121.38,119.04
378
+ 376,4/4/2022,102.78,77.47,86.41,107.71,94.68,107.47,107.84,107.42,107.11,107.45,107.99,107.56,107.08,107.67,108.06,108.83,106.29,107.01
379
+ 377,4/11/2022,111.7,77.5,92.55,102.82,97.89,102.7,102.91,102.57,102.43,102.68,93.75,102.77,102.4,102.47,102.18,102.8,101.48,102.63
380
+ 378,4/18/2022,106.65,77.55,95.15,111.75,120.64,111.94,111.86,111.42,111.65,111.94,113.7,112.06,111.65,111.83,111.82,111.64,108.04,111.37
381
+ 379,4/25/2022,109.34,77.58,88.15,106.69,101.6,106.61,106.8,106.41,106.29,106.6,108.69,106.71,106.29,106.46,106.86,107.03,106.12,106.16
382
+ 380,5/2/2022,112.39,77.62,97.1,109.39,112.04,109.42,109.49,109.08,109.13,109.43,108.11,109.54,109.13,109.25,109.27,109.37,111.87,108.79
383
+ 381,5/9/2022,111.55,77.67,91.72,112.44,115.45,112.48,112.56,112.11,112.16,112.49,115.27,112.61,112.17,112.39,112.56,112.6,112.3,111.33
384
+ 382,5/16/2022,112.55,77.71,95.94,111.6,110.71,111.58,111.72,111.28,111.25,111.58,112.69,111.7,111.25,111.45,111.67,111.89,113.29,110.47
385
+ 383,5/23/2022,119.43,77.76,93.03,112.6,113.56,112.61,112.72,112.27,112.29,112.61,112.63,112.74,112.29,112.45,112.59,112.78,113.73,111.36
386
+ 384,5/30/2022,119.72,77.81,102.09,119.49,126.32,119.6,119.63,119.11,119.24,119.6,123.35,119.75,119.25,119.59,119.62,119.73,121.54,117.46
387
+ 385,6/6/2022,122.01,77.87,94.08,119.78,120.02,119.78,119.93,119.4,119.4,119.78,123.36,119.93,119.4,119.8,119.97,120.36,122.4,117.55
388
+ 386,6/13/2022,113.12,77.92,103.61,122.07,124.31,122.11,122.23,121.68,121.72,122.11,123.3,122.26,121.73,122.12,122.11,122.56,125.4,119.64
389
+ 387,6/20/2022,113.12,77.97,86.71,113.17,104.22,113.05,113.3,112.84,112.67,113.04,109.9,113.17,112.66,112.73,113.11,113.64,111.26,111.72
390
+ 388,6/27/2022,116.26,78.01,102.28,113.17,113.13,113.17,113.29,112.84,112.84,113.17,108.59,113.29,112.83,112.72,112.91,113.02,111.08,111.79
Explore/PREDICTIONS/Weekly/60.csv ADDED
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1
+ ,Date,Close Prices,"ARIMA_60.0_(0, 0, 0)_Predictions","ARIMA_60.0_(0, 0, 1)_Predictions","ARIMA_60.0_(0, 1, 0)_Predictions","ARIMA_60.0_(0, 2, 0)_Predictions","ARIMA_60.0_(0, 1, 1)_Predictions","ARIMA_60.0_(0, 2, 1)_Predictions","ARIMA_60.0_(1, 0, 0)_Predictions","ARIMA_60.0_(1, 0, 1)_Predictions","ARIMA_60.0_(1, 1, 0)_Predictions","ARIMA_60.0_(1, 2, 0)_Predictions","ARIMA_60.0_(1, 2, 1)_Predictions","ARIMA_60.0_(2, 0, 0)_Predictions","ARIMA_60.0_(2, 0, 1)_Predictions","ARIMA_60.0_(2, 1, 0)_Predictions","ARIMA_60.0_(2, 1, 1)_Predictions","ARIMA_60.0_(2, 2, 0)_Predictions",LSTM_60.0_WEEKLY
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+ 0,7/11/2016,47.61,87.6,67.45,46.7,43.68,46.65,46.36,47.05,47,46.65,46.07,46.31,46.99,47.37,46.76,46.87,46.13,
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+ 3,8/1/2016,44.27,87.33,66.23,42.39,39.23,42.34,42.03,42.76,42.71,42.33,39.92,41.98,42.7,42.79,42.19,42.23,41.05,
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+ 4,8/8/2016,46.97,87.24,67.41,44.21,46.09,44.23,43.84,44.56,44.61,44.24,43.42,43.88,44.61,44.75,43.99,43.82,42.97,
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8
+ 6,8/22/2016,49.92,87.07,70.99,50.83,54.81,50.9,50.51,51.14,51.23,50.91,54.17,50.59,51.25,51.75,51.11,50.93,53.68,
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+ 7,8/29/2016,46.83,86.99,67.97,49.87,48.97,49.85,49.55,50.19,50.17,49.85,51.54,49.54,50.17,50.69,50.15,50.26,51.99,
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+ 8,9/5/2016,48.01,86.91,67.81,46.77,43.74,46.72,46.44,47.11,47.05,46.71,44.86,46.39,47.05,47.38,46.65,47,46.81,
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+ 9,9/12/2016,45.77,86.83,68.93,47.95,49.2,47.97,47.63,48.28,48.32,47.98,46.95,47.66,48.32,48.63,47.75,47.9,46.91,
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+ 10,9/19/2016,45.89,86.74,65.81,45.71,43.53,45.67,45.38,46.05,46.01,45.67,45.34,45.34,46.01,46.25,45.76,45.77,44.54,
13
+ 11,9/26/2016,49.06,86.66,68.65,45.83,46.02,45.83,45.49,46.17,46.18,45.83,44.77,45.5,46.18,46.38,45.67,45.71,45.48,
14
+ 12,10/3/2016,51.93,86.58,68.86,49.01,52.25,49.06,48.69,49.33,49.4,49.07,50.64,48.75,49.41,49.75,49.07,48.92,49.35,
15
+ 13,10/10/2016,51.95,86.51,71.19,51.88,54.82,51.93,51.58,52.18,52.25,51.94,54.98,51.65,52.26,52.76,52.17,52.07,54.04,
16
+ 14,10/17/2016,51.78,86.43,69.03,51.9,51.98,51.9,51.61,52.2,52.21,51.9,53.48,51.62,52.21,52.73,52.11,52.27,54.07,
17
+ 15,10/24/2016,49.71,86.36,70.76,51.73,51.62,51.73,51.44,52.03,52.03,51.73,51.72,51.45,52.03,52.51,51.73,52.03,52.68,
18
+ 16,10/31/2016,45.58,86.29,67.24,49.66,47.64,49.62,49.36,49.97,49.93,49.62,48.64,49.33,49.93,50.28,49.61,49.88,49.03,
19
+ 17,11/7/2016,44.75,86.2,66.6,45.52,41.45,45.44,45.2,45.86,45.77,45.43,42.53,45.12,45.76,45.9,45.29,45.53,43.49,
20
+ 18,11/14/2016,46.86,86.12,66.34,44.69,43.93,44.67,44.36,45.03,45.02,44.67,42.19,44.35,45.02,45.05,44.38,44.4,42.29,
21
+ 19,11/21/2016,47.24,86.03,68.4,46.8,48.98,46.84,46.48,47.13,47.19,46.85,47.44,46.54,47.19,47.32,46.79,46.53,45.87,
22
+ 20,11/28/2016,54.46,85.95,66.79,47.18,47.63,47.19,46.87,47.51,47.52,47.19,48.54,46.89,47.53,47.73,47.34,47.12,47.88,
23
+ 21,12/5/2016,54.33,85.89,74.72,54.42,61.7,54.56,54.14,54.69,54.87,54.58,58.11,54.31,54.89,55.36,54.6,54.43,57.51,
24
+ 22,12/12/2016,55.21,85.83,67.36,54.29,54.21,54.28,54.02,54.56,54.56,54.29,58.09,54.03,54.56,55.15,54.82,54.81,57.14,
25
+ 23,12/19/2016,55.16,85.76,74.76,55.17,56.1,55.19,54.91,55.43,55.46,55.19,55.57,54.94,55.46,56.03,55.18,55.58,57.77,
26
+ 24,12/26/2016,56.13,85.7,67.95,55.12,55.12,55.12,54.86,55.38,55.39,55.12,55.61,54.87,55.39,55.92,55.19,55.51,55.44,
27
+ 25,1/2/2017,57.1,85.64,74.94,56.09,57.11,56.11,55.84,56.35,56.37,56.11,56.57,55.87,56.38,56.89,56.11,56.41,56.7,
28
+ 26,1/9/2017,55.45,85.58,69.42,57.06,58.08,57.08,56.82,57.31,57.34,57.09,58.08,56.85,57.34,57.86,57.16,57.39,57.76,
29
+ 27,1/16/2017,55.49,85.52,72.87,55.41,53.81,55.38,55.16,55.67,55.64,55.38,55.18,55.13,55.63,56.07,55.45,55.73,55.63,
30
+ 28,1/23/2017,55.52,85.46,69.72,55.45,55.54,55.45,55.2,55.71,55.72,55.45,54.65,55.21,55.72,56.08,55.33,55.59,55.2,
31
+ 29,1/30/2017,56.81,85.4,72.54,55.48,55.56,55.48,55.23,55.74,55.74,55.48,55.56,55.24,55.75,56.09,55.49,55.6,55.02,
32
+ 30,2/6/2017,56.7,85.34,71.09,56.77,58.11,56.8,56.53,57.02,57.05,56.8,57.45,56.57,57.06,57.42,56.8,56.88,57.24,
33
+ 31,2/13/2017,55.81,85.28,72.25,56.66,56.6,56.66,56.43,56.91,56.91,56.66,57.34,56.43,56.91,57.27,56.76,56.84,57.17,
34
+ 32,2/20/2017,55.99,85.23,70.33,55.77,54.93,55.76,55.53,56.02,56.01,55.75,55.34,55.52,56.01,56.31,55.75,55.9,55.92,
35
+ 33,2/27/2017,55.9,85.17,72.17,55.95,56.18,55.96,55.71,56.2,56.21,55.96,55.62,55.72,56.21,56.48,55.89,56,55.68,
36
+ 34,3/6/2017,51.37,85.11,70.36,55.86,55.82,55.86,55.62,56.11,56.12,55.86,55.96,55.63,56.12,56.37,55.88,55.91,55.66,
37
+ 35,3/13/2017,51.76,85.04,67.83,51.32,46.84,51.24,51.07,51.61,51.51,51.23,49.17,50.97,51.5,51.58,51.23,51.34,50.01,
38
+ 36,3/20/2017,50.8,84.97,70.4,51.71,52.16,51.72,51.45,51.99,52.01,51.72,49.56,51.47,52.01,52.02,51.39,51.41,50.16,
39
+ 37,3/27/2017,52.83,84.91,67.13,50.75,49.85,50.73,50.49,51.04,51.02,50.73,50.56,50.47,51.02,51.03,50.77,50.54,49.2,
40
+ 38,4/3/2017,55.24,84.84,71.87,52.79,54.87,52.82,52.53,53.06,53.11,52.83,53.3,52.58,53.12,53.2,52.76,52.56,53.23,
41
+ 39,4/10/2017,55.89,84.78,69.7,55.2,57.66,55.25,54.96,55.45,55.51,55.25,57.47,55.02,55.52,55.75,55.4,55.18,56.44,
42
+ 40,4/17/2017,51.96,84.73,72.2,55.85,56.55,55.86,55.62,56.1,56.12,55.87,57.48,55.64,56.12,56.42,56.05,56.01,57.66,
43
+ 41,4/24/2017,51.73,84.66,66.3,51.91,48.03,51.84,51.67,52.19,52.11,51.83,50.44,51.59,52.1,52.25,51.89,52.07,51.77,
44
+ 42,5/1/2017,49.1,84.6,71.38,51.68,51.51,51.68,51.43,51.96,51.96,51.68,49.56,51.43,51.96,52.03,51.4,51.54,50.4,
45
+ 43,5/8/2017,50.84,84.53,64.31,49.05,46.47,49,48.79,49.34,49.29,48.99,47.73,48.74,49.28,49.27,48.98,48.91,46.95,
46
+ 44,5/15/2017,53.61,84.46,72.24,50.79,52.59,50.83,50.53,51.07,51.12,50.83,50.29,50.58,51.13,51.14,50.64,50.51,50.32,
47
+ 45,5/22/2017,52.15,84.4,67.49,53.57,56.39,53.62,53.32,53.83,53.9,53.63,55.86,53.39,53.91,54.08,53.75,53.48,54.29,
48
+ 46,5/29/2017,49.95,84.34,70.41,52.11,50.7,52.08,51.86,52.38,52.35,52.08,52.92,51.84,52.35,52.53,52.28,52.23,53.31,
49
+ 47,6/5/2017,48.15,84.27,65.69,49.9,47.75,49.86,49.65,50.19,50.14,49.85,48.14,49.61,50.14,50.22,49.76,49.89,49.62,
50
+ 48,6/12/2017,47.37,84.2,68.27,48.1,46.36,48.06,47.83,48.39,48.36,48.06,46.14,47.8,48.36,48.34,47.91,47.93,46.31,
51
+ 49,6/19/2017,45.54,84.13,65.14,47.32,46.6,47.3,47.05,47.62,47.61,47.3,46.06,47.04,47.6,47.55,47.18,47.06,45.76,
52
+ 50,6/26/2017,47.92,84.05,66.25,45.48,43.71,45.45,45.21,45.79,45.76,45.44,44.26,45.17,45.75,45.66,45.39,45.22,44.11,
53
+ 51,7/3/2017,46.71,83.98,67.33,47.87,50.31,47.92,47.6,48.16,48.22,47.92,48.1,47.66,48.23,48.22,47.79,47.55,47.73,
54
+ 52,7/10/2017,48.91,83.91,65.18,46.66,45.51,46.63,46.39,46.96,46.94,46.63,47.39,46.37,46.93,46.97,46.81,46.57,46.65,
55
+ 53,7/17/2017,48.06,83.85,69.06,48.86,51.12,48.9,48.6,49.15,49.2,48.91,49.33,48.65,49.21,49.31,48.82,48.72,49.9,
56
+ 54,7/24/2017,52.52,83.78,64.69,48.01,47.22,47.99,47.75,48.3,48.29,47.99,48.82,47.74,48.29,48.42,48.16,48.05,48.25,
57
+ 55,7/31/2017,52.42,83.72,72.65,52.48,57,52.56,52.24,52.74,52.84,52.57,54.2,52.33,52.85,53.13,52.5,52.47,54.28,
58
+ 56,8/7/2017,52.1,83.66,65.26,52.38,52.33,52.37,52.14,52.64,52.64,52.38,54.74,52.15,52.64,52.99,52.71,52.69,53.82,
59
+ 57,8/14/2017,52.72,83.6,71.63,52.06,51.79,52.05,51.82,52.32,52.32,52.05,51.9,51.82,52.32,52.63,52.05,52.3,53.39,
60
+ 58,8/21/2017,52.41,83.54,66.34,52.68,53.35,52.69,52.45,52.93,52.95,52.69,52.85,52.47,52.95,53.26,52.67,52.85,52.77,
61
+ 59,8/28/2017,52.32,83.48,70.81,52.37,52.11,52.36,52.14,52.62,52.62,52.36,52.6,52.14,52.62,52.91,52.41,52.55,52.46,
62
+ 60,9/4/2017,53.78,83.42,66.6,52.28,52.24,52.28,52.05,52.53,52.54,52.28,52.12,52.05,52.54,52.8,52.26,52.4,52.38,
63
+ 61,9/11/2017,55.62,83.36,71.7,53.74,55.25,53.77,53.52,53.98,54.02,53.77,54.43,53.55,54.03,54.32,53.76,53.84,54.11,
64
+ 62,9/18/2017,56.86,83.31,68.68,55.58,57.47,55.62,55.37,55.81,55.86,55.62,57.27,55.42,55.86,56.23,55.73,55.77,56.72,
65
+ 63,9/25/2017,57.54,83.26,72.51,56.83,58.11,56.85,56.62,57.05,57.08,56.85,58.43,56.66,57.08,57.5,56.99,57.11,58.41,
66
+ 64,10/2/2017,55.62,83.21,69.59,57.51,58.23,57.52,57.31,57.72,57.74,57.52,58.53,57.33,57.74,58.17,57.61,57.83,58.81,
67
+ 65,10/9/2017,57.17,83.16,70.45,55.58,53.7,55.55,55.38,55.81,55.78,55.54,55.07,55.35,55.77,56.1,55.6,55.88,55.69,
68
+ 66,10/16/2017,57.75,83.11,71.02,57.14,58.73,57.17,56.94,57.35,57.39,57.17,56.9,56.98,57.4,57.71,57.03,57.24,57.14,
69
+ 67,10/23/2017,60.44,83.06,70.98,57.72,58.34,57.73,57.53,57.93,57.94,57.73,58.85,57.54,57.95,58.29,57.85,57.92,57.91,
70
+ 68,10/30/2017,62.07,83.02,73.42,60.41,63.14,60.46,60.23,60.6,60.66,60.47,62.03,60.3,60.67,61.09,60.51,60.62,61.99,
71
+ 69,11/6/2017,63.52,82.98,72.65,62.05,63.71,62.08,61.88,62.22,62.26,62.08,64.27,61.92,62.26,62.76,62.28,62.41,63.78,
72
+ 70,11/13/2017,62.72,82.95,74.64,63.5,64.98,63.53,63.34,63.66,63.69,63.53,65.08,63.38,63.7,64.22,63.65,63.91,65.44,
73
+ 71,11/20/2017,63.86,82.91,72.06,62.7,61.93,62.68,62.54,62.86,62.85,62.68,63.11,62.53,62.85,63.31,62.79,63.12,63.55,
74
+ 72,11/27/2017,63.49,82.87,75.41,63.84,65.01,63.86,63.69,64,64.02,63.86,63.99,63.72,64.03,64.47,63.8,64.13,64.37,
75
+ 73,12/4/2017,63.4,82.84,71.98,63.47,63.13,63.46,63.32,63.63,63.62,63.46,63.92,63.31,63.62,64.02,63.55,63.78,63.56,
76
+ 74,12/11/2017,63.23,82.8,74.98,63.38,63.32,63.38,63.23,63.54,63.54,63.38,63.17,63.23,63.54,63.89,63.35,63.6,63.6,
77
+ 75,12/18/2017,65.25,82.76,72.06,63.21,63.07,63.21,63.06,63.37,63.37,63.21,63.11,63.06,63.37,63.67,63.2,63.38,63.03,
78
+ 76,12/25/2017,66.6,82.73,76.53,65.23,67.28,65.27,65.09,65.37,65.42,65.28,66.13,65.14,65.43,65.77,65.26,65.36,65.79,
79
+ 77,1/1/2018,67.62,82.7,73.66,66.58,67.96,66.61,66.45,66.71,66.75,66.61,68.32,66.48,66.75,67.15,66.76,66.84,67.74,
80
+ 78,1/8/2018,69.87,82.67,77.17,67.61,68.65,67.63,67.48,67.73,67.75,67.63,68.82,67.5,67.76,68.17,67.73,67.91,69.09,
81
+ 79,1/15/2018,68.61,82.65,76,69.86,72.13,69.9,69.74,69.96,70.01,69.91,71.49,69.8,70.02,70.49,69.99,70.18,71.39,
82
+ 80,1/22/2018,70.52,82.63,75.9,68.6,67.36,68.57,68.48,68.71,68.68,68.57,69.21,68.45,68.68,69.1,68.74,69,69.41,
83
+ 81,1/29/2018,68.58,82.6,77.71,70.51,72.44,70.55,70.4,70.6,70.65,70.55,70.77,70.45,70.66,71.06,70.45,70.76,71.35,
84
+ 82,2/5/2018,62.79,82.58,74.27,68.57,66.64,68.53,68.45,68.68,68.64,68.53,68.68,68.41,68.63,68.96,68.68,68.89,68.32,
85
+ 83,2/12/2018,64.84,82.54,72.09,62.77,57,62.66,62.63,62.93,62.8,62.64,59.02,62.49,62.78,62.84,62.5,62.85,60.88,
86
+ 84,2/19/2018,67.31,82.51,75.91,64.82,66.9,64.86,64.68,64.97,65.02,64.86,62.76,64.73,65.02,65.03,64.43,64.51,62.66,
87
+ 85,2/26/2018,64.37,82.48,74.65,67.3,69.79,67.34,67.17,67.42,67.47,67.35,69.57,67.23,67.48,67.63,67.49,67.2,67.01,
88
+ 86,3/5/2018,65.49,82.45,73.08,64.35,61.43,64.3,64.22,64.5,64.44,64.29,64.28,64.16,64.43,64.52,64.47,64.44,65.06,
89
+ 87,3/12/2018,66.21,82.42,75.5,65.47,66.62,65.49,65.34,65.61,65.64,65.5,64.48,65.36,65.64,65.71,65.29,65.34,65.53,
90
+ 88,3/19/2018,70.45,82.39,73.93,66.19,66.94,66.21,66.06,66.33,66.34,66.21,67.15,66.08,66.35,66.46,66.29,66.17,65.91,
91
+ 89,3/26/2018,70.27,82.37,79.2,70.44,74.71,70.52,70.33,70.53,70.63,70.53,72.86,70.42,70.64,70.91,70.57,70.49,72.39,
92
+ 90,4/2/2018,67.11,82.35,74.21,70.26,70.1,70.26,70.16,70.36,70.35,70.26,72.43,70.15,70.35,70.67,70.56,70.59,72.05,
93
+ 91,4/9/2018,72.58,82.32,75.85,67.1,63.95,67.04,66.98,67.22,67.16,67.03,65.51,66.91,67.15,67.32,67.02,67.33,67.43,
94
+ 92,4/16/2018,74.06,82.3,79.32,72.58,78.07,72.66,72.47,72.65,72.75,72.67,73.53,72.58,72.77,73.06,72.45,72.55,73.02,
95
+ 93,4/23/2018,74.64,82.29,77.49,74.06,75.55,74.08,73.97,74.12,74.14,74.09,77.65,74,74.15,74.56,74.46,74.43,75.54,
96
+ 94,4/30/2018,74.87,82.27,79.67,74.64,75.23,74.65,74.56,74.69,74.7,74.65,75.7,74.57,74.71,75.11,74.75,75.04,77.15,
97
+ 95,5/7/2018,77.12,82.26,77.88,74.87,75.11,74.87,74.79,74.92,74.93,74.87,75.29,74.8,74.93,75.3,74.91,75.23,75.64,
98
+ 96,5/14/2018,78.51,82.25,81.55,77.12,79.38,77.16,77.05,77.15,77.2,77.17,78.32,77.1,77.2,77.62,77.18,77.43,78.09,
99
+ 97,5/21/2018,76.44,82.24,79.47,78.52,79.91,78.54,78.45,78.53,78.56,78.54,80.36,78.48,78.56,79.02,78.69,78.92,79.86,
100
+ 98,5/28/2018,77.59,82.23,79.47,76.44,74.37,76.41,76.38,76.48,76.44,76.4,76.19,76.33,76.43,76.78,76.5,76.86,77.06,
101
+ 99,6/4/2018,76.46,82.23,80.51,77.6,78.75,77.61,77.53,77.62,77.64,77.62,77.06,77.55,77.64,77.95,77.47,77.78,77.63,
102
+ 100,6/11/2018,73.44,82.21,78.53,76.46,75.34,76.44,76.39,76.5,76.48,76.44,76.53,76.37,76.47,76.72,76.52,76.69,75.88,
103
+ 101,6/18/2018,75.55,82.2,77.57,73.44,70.42,73.39,73.36,73.5,73.44,73.38,71.41,73.3,73.43,73.52,73.31,73.53,72.47,
104
+ 102,6/25/2018,79.44,82.19,80.35,75.55,77.67,75.59,75.47,75.59,75.64,75.59,74.98,75.52,75.64,75.74,75.38,75.42,74.71,
105
+ 103,7/2/2018,77.11,82.18,81.35,79.45,83.34,79.51,79.39,79.45,79.53,79.52,82.42,79.47,79.54,79.8,79.65,79.5,80.45,
106
+ 104,7/9/2018,75.33,82.17,78.31,77.11,74.78,77.08,77.05,77.14,77.1,77.07,78.04,77.01,77.09,77.31,77.33,77.42,78.53,
107
+ 105,7/16/2018,73.07,82.16,79.45,75.33,73.55,75.3,75.26,75.38,75.34,75.3,73.27,75.22,75.34,75.43,75.15,75.41,75.2,
108
+ 106,7/23/2018,74.29,82.15,76.33,73.07,70.81,73.03,72.98,73.13,73.09,73.02,71.06,72.94,73.08,73.06,72.91,73,70.96,
109
+ 107,7/30/2018,73.21,82.13,80.27,74.29,75.52,74.31,74.21,74.34,74.37,74.31,73.7,74.23,74.37,74.35,74.17,74.09,73.26,
110
+ 108,8/6/2018,72.81,82.12,75.68,73.21,72.14,73.19,73.12,73.27,73.25,73.19,73.34,73.1,73.25,73.23,73.27,73.13,72.6,
111
+ 109,8/13/2018,71.83,82.1,79.48,72.81,72.42,72.8,72.72,72.88,72.87,72.8,72.06,72.71,72.87,72.82,72.73,72.67,72.69,
112
+ 110,8/20/2018,75.82,82.08,75.11,71.82,70.86,71.81,71.73,71.9,71.89,71.81,71.16,71.72,71.88,71.81,71.78,71.69,71.04,
113
+ 111,8/27/2018,77.42,82.07,82.72,75.82,79.82,75.88,75.74,75.86,75.94,75.89,77.23,75.82,75.95,76.01,75.83,75.65,76.57,
114
+ 112,9/3/2018,76.83,82.06,77.24,77.42,79.03,77.45,77.36,77.45,77.48,77.45,80.28,77.39,77.49,77.67,77.71,77.56,79.08,
115
+ 113,9/10/2018,78.09,82.05,81.68,76.83,76.25,76.82,76.77,76.86,76.85,76.82,77.39,76.76,76.85,77.02,76.92,77.05,78.54,
116
+ 114,9/17/2018,78.8,82.05,78.77,78.1,79.36,78.12,78.03,78.11,78.14,78.12,78.39,78.06,78.14,78.33,78.08,78.23,78.79,
117
+ 115,9/24/2018,82.72,82.04,82.07,78.81,79.52,78.82,78.75,78.82,78.83,78.82,79.81,78.77,78.83,79.04,78.9,79,79.3,
118
+ 116,10/1/2018,84.16,82.04,82.64,82.73,86.65,82.8,82.69,82.71,82.78,82.81,84.98,82.77,82.8,83.12,82.85,82.95,84.61,
119
+ 117,10/8/2018,80.43,82.05,83.43,84.18,85.61,84.2,84.15,84.13,84.16,84.2,86.91,84.18,84.17,84.58,84.45,84.62,86.29,
120
+ 118,10/15/2018,79.78,82.04,79.31,80.44,76.7,80.38,80.4,80.43,80.36,80.37,79.4,80.32,80.35,80.6,80.46,80.87,81.09,
121
+ 119,10/22/2018,77.62,82.04,82.47,79.79,79.14,79.78,79.74,79.79,79.78,79.78,77.53,79.73,79.77,79.9,79.55,79.88,78.68,
122
+ 120,10/29/2018,72.83,82.03,77.62,77.62,75.46,77.59,77.57,77.65,77.6,77.58,76.25,77.52,77.6,77.62,77.54,77.65,75.5,
123
+ 121,11/5/2018,70.18,82.02,77.66,72.83,68.04,72.74,72.75,72.9,72.79,72.73,69.41,72.64,72.78,72.61,72.59,72.67,70.34,
124
+ 122,11/12/2018,66.76,82,75.19,70.17,67.53,70.12,70.08,70.27,70.21,70.11,66.41,70.02,70.2,69.87,69.81,69.72,66.9,
125
+ 123,11/19/2018,58.8,81.97,74.3,66.75,63.34,66.67,66.64,66.87,66.79,66.66,63.74,66.55,66.78,66.34,66.49,66.18,63.17,
126
+ 124,11/26/2018,58.71,81.93,67.82,58.77,50.83,58.58,58.63,58.97,58.76,58.55,53.19,58.4,58.72,58.03,58.33,57.99,54.22,
127
+ 125,12/3/2018,61.67,81.89,73.6,58.68,58.63,58.69,58.53,58.88,58.89,58.68,54.51,58.53,58.89,58.09,58.13,57.56,54.64,
128
+ 126,12/10/2018,60.28,81.86,70.99,61.65,64.64,61.72,61.5,61.82,61.91,61.73,63.06,61.6,61.92,61.35,61.72,60.83,59.96,
129
+ 127,12/17/2018,53.82,81.82,72.07,60.26,58.9,60.22,60.11,60.44,60.4,60.22,61.16,60.08,60.4,59.97,60.41,59.77,60.9,
130
+ 128,12/24/2018,52.2,81.78,65.15,53.78,47.36,53.62,53.62,54.02,53.84,53.6,49.97,53.43,53.82,53.25,53.53,53.23,52.27,
131
+ 129,12/31/2018,57.06,81.73,69.93,52.16,50.58,52.12,51.98,52.41,52.38,52.11,48.07,51.94,52.37,51.67,51.72,51.3,48.91,
132
+ 130,1/7/2019,60.48,81.68,69.96,57.03,61.94,57.16,56.86,57.24,57.39,57.17,58.6,57.01,57.41,56.93,57.07,56.34,55.89,
133
+ 131,1/14/2019,62.7,81.65,73.01,60.46,63.91,60.55,60.31,60.64,60.75,60.56,64.66,60.43,60.77,60.6,60.83,60.26,62.79,
134
+ 132,1/21/2019,61.64,81.62,72.22,62.68,64.93,62.74,62.55,62.84,62.92,62.75,65.55,62.63,62.93,62.96,62.95,62.76,66.22,
135
+ 133,1/28/2019,61.87,81.58,71.94,61.62,60.59,61.59,61.48,61.79,61.76,61.58,62.27,61.46,61.76,61.84,61.71,61.78,63.21,
136
+ 134,2/4/2019,62.1,81.55,72.37,61.85,62.11,61.86,61.71,62.02,62.03,61.86,61.45,61.73,62.03,62.09,61.8,61.92,62.3,
137
+ 135,2/11/2019,66.25,81.52,72.16,62.08,62.34,62.09,61.95,62.25,62.26,62.09,62.34,61.96,62.26,62.33,62.1,62.16,61.92,
138
+ 136,2/18/2019,67.12,81.49,76.11,66.24,70.41,66.36,66.12,66.37,66.5,66.37,68.41,66.26,66.52,66.7,66.38,66.38,67.75,
139
+ 137,2/25/2019,66.01,81.47,73.28,67.11,68,67.13,67,67.23,67.26,67.14,69.68,67.03,67.27,67.58,67.37,67.46,68.96,
140
+ 138,3/4/2019,65.74,81.44,74.82,66,64.91,65.96,65.89,66.13,66.09,65.96,65.92,65.85,66.09,66.37,66.01,66.3,67.32,
141
+ 139,3/11/2019,67.16,81.42,73.14,65.73,65.48,65.72,65.61,65.86,65.86,65.72,65.05,65.61,65.85,66.06,65.66,65.9,65.55,
142
+ 140,3/18/2019,67.03,81.39,75.94,67.15,68.59,67.19,67.04,67.27,67.32,67.19,67.72,67.09,67.32,67.53,67.18,67.3,67.17,
143
+ 141,3/25/2019,68.39,81.37,73.25,67.02,66.91,67.01,66.91,67.14,67.14,67.01,67.7,66.91,67.14,67.37,67.09,67.21,67.41,
144
+ 142,4/1/2019,70.34,81.35,76.92,68.38,69.76,68.42,68.28,68.49,68.54,68.42,69,68.33,68.54,68.77,68.41,68.55,69.25,
145
+ 143,4/8/2019,71.55,81.33,75.33,70.33,72.3,70.39,70.24,70.42,70.49,70.4,72,70.31,70.5,70.79,70.47,70.58,71.42,
146
+ 144,4/15/2019,71.97,81.31,77.87,71.54,72.77,71.58,71.46,71.62,71.66,71.58,73.15,71.51,71.67,72.02,71.69,71.86,73.08,
147
+ 145,4/22/2019,72.15,81.3,75.92,71.97,72.4,71.98,71.89,72.04,72.05,71.98,72.8,71.9,72.06,72.41,72.05,72.29,73.18,
148
+ 146,4/29/2019,70.85,81.28,77.85,72.15,72.34,72.15,72.07,72.22,72.23,72.15,72.46,72.08,72.23,72.55,72.17,72.43,72.76,
149
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150
+ 148,5/13/2019,72.21,81.25,77.36,70.61,70.4,70.61,70.53,70.7,70.7,70.61,69.85,70.52,70.69,70.87,70.53,70.71,70.15,
151
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152
+ 150,5/27/2019,64.49,81.22,74.06,68.68,65.17,68.58,68.59,68.78,68.67,68.57,67.79,68.48,68.66,68.8,68.66,68.78,68.05,
153
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154
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155
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156
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157
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158
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159
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160
+ 158,7/22/2019,63.46,81,69.44,62.45,58.22,62.32,62.34,62.61,62.48,62.31,61.67,62.2,62.46,62.46,62.46,62.44,61.23,
161
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162
+ 160,8/5/2019,58.53,80.94,68.51,61.87,60.32,61.82,61.75,62.04,61.99,61.82,61.64,61.7,61.99,61.91,61.88,61.73,60.37,60.98
163
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164
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165
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166
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167
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168
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169
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170
+ 168,9/30/2019,58.37,80.68,67.56,61.89,59.54,61.82,61.78,62.05,61.98,61.82,62.85,61.71,61.98,62.13,62.06,62.07,62.18,60.98
171
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172
+ 170,10/14/2019,59.42,80.62,69.89,60.49,62.66,60.55,60.36,60.66,60.74,60.55,59.75,60.43,60.74,60.7,60.36,60.3,59.17,59.63
173
+ 171,10/21/2019,62.02,80.58,71.03,59.4,58.34,59.37,59.27,59.58,59.55,59.36,59.99,59.24,59.55,59.56,59.48,59.35,58.67,58.56
174
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175
+ 173,11/4/2019,62.51,80.52,69.46,60.19,58.4,60.14,60.07,60.36,60.31,60.14,60.67,60.02,60.31,60.4,60.29,60.26,60.21,59.34
176
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177
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178
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179
+ 177,12/2/2019,64.39,80.41,69.95,62.41,61.48,62.39,62.3,62.57,62.54,62.38,62.02,62.28,62.54,62.69,62.39,62.52,62.42,61.53
180
+ 178,12/9/2019,65.22,80.39,75.31,64.37,66.36,64.42,64.27,64.51,64.57,64.43,64.86,64.33,64.58,64.74,64.37,64.44,64.71,63.66
181
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182
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183
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184
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185
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186
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187
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188
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189
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190
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191
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192
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193
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194
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195
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196
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197
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198
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199
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200
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201
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202
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203
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204
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205
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206
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207
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208
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209
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210
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211
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212
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213
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214
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215
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216
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217
+ 215,8/24/2020,45.05,78.45,59.97,44.31,43.91,44.29,44.14,44.59,44.58,44.29,44.34,44.13,44.58,44.91,44.31,44.46,44.68,44.35
218
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219
+ 217,9/7/2020,39.83,78.35,58.12,42.61,40.27,42.52,42.44,42.91,42.81,42.51,41.85,42.34,42.8,43.07,42.56,42.67,41.98,43.14
220
+ 218,9/14/2020,43.15,78.3,61.53,39.78,37,39.67,39.6,40.09,39.98,39.65,37.22,39.47,39.96,40.07,39.51,39.64,38.23,40.64
221
+ 219,9/21/2020,41.92,78.25,61.39,43.1,46.48,43.24,42.93,43.39,43.56,43.26,43.35,43.09,43.57,43.62,43.08,42.99,42.53,42.64
222
+ 220,9/28/2020,39.27,78.19,60.34,41.87,40.69,41.82,41.7,42.17,42.12,41.82,43.01,41.65,42.12,42.3,42.03,41.88,41.84,42.36
223
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224
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225
+ 223,10/19/2020,41.77,78.03,59.21,42.88,43.02,42.88,42.72,43.17,43.18,42.89,44.8,42.73,43.19,43.4,43.1,42.97,43.43,43.07
226
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227
+ 225,11/2/2020,39.45,77.92,55.42,37.41,33.15,37.24,37.22,37.73,37.56,37.22,34.75,37.04,37.53,37.61,37.16,37.26,35.62,38.84
228
+ 226,11/9/2020,42.78,77.87,63.22,39.4,41.45,39.48,39.21,39.71,39.81,39.49,38.24,39.31,39.82,39.76,39.23,39.18,38.22,39.43
229
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230
+ 228,11/23/2020,48.18,77.77,64.83,44.92,47.15,45,44.76,45.19,45.29,45.02,47.73,44.87,45.31,45.58,45.2,45.13,47.5,44.63
231
+ 229,11/30/2020,49.25,77.73,62.44,48.14,51.41,48.27,48,48.39,48.54,48.29,50.89,48.16,48.56,48.94,48.41,48.5,51.08,47.47
232
+ 230,12/7/2020,49.97,77.68,65.58,49.21,50.33,49.25,49.08,49.45,49.5,49.26,51.42,49.14,49.52,50,49.45,49.65,51.44,48.72
233
+ 231,12/14/2020,52.26,77.65,63.32,49.93,50.7,49.96,49.8,50.17,50.21,49.97,50.88,49.84,50.22,50.69,50.03,50.34,51.59,49.37
234
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235
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236
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238
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251
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252
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253
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254
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255
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256
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257
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258
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287
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290
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291
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292
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293
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294
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295
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296
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+ 9,9/9/2019,60.22,80.77,72.95,61.52,61.55,62.66,61.4,61.69,61.73,61.56,62.65,61.44,61.73,61.74,61.62,61.47,62.52,
12
+ 10,9/16/2019,64.28,80.74,69.12,60.2,60.16,58.9,60.07,60.38,60.34,60.16,60.15,60.03,60.33,60.36,60.22,60.2,60.55,
13
+ 11,9/23/2019,61.91,80.71,76.3,64.26,64.38,68.35,64.15,64.41,64.54,64.39,65.59,64.29,64.56,64.64,64.31,64.26,65.48,
14
+ 12,9/30/2019,58.37,80.68,67.56,61.89,61.82,59.54,61.78,62.05,61.98,61.82,62.85,61.71,61.98,62.13,62.06,62.07,62.18,
15
+ 13,10/7/2019,60.51,80.65,72.27,58.34,58.25,54.83,58.22,58.54,58.44,58.23,55.43,58.11,58.42,58.41,58.11,58.3,57.72,
16
+ 14,10/14/2019,59.42,80.62,69.89,60.49,60.55,62.66,60.36,60.66,60.74,60.55,59.75,60.43,60.74,60.7,60.36,60.3,59.17,
17
+ 15,10/21/2019,62.02,80.58,71.03,59.4,59.37,58.34,59.27,59.58,59.55,59.36,59.99,59.24,59.55,59.56,59.48,59.35,58.67,
18
+ 16,10/28/2019,60.21,80.55,72.34,62,62.07,64.63,61.88,62.16,62.24,62.08,62.74,61.96,62.25,62.31,62.01,61.94,63.17,
19
+ 17,11/4/2019,62.51,80.52,69.46,60.19,60.14,58.4,60.07,60.36,60.31,60.14,60.67,60.02,60.31,60.4,60.29,60.26,60.21,
20
+ 18,11/11/2019,63.3,80.49,74.15,62.49,62.55,64.82,62.38,62.65,62.72,62.56,62.7,62.45,62.73,62.82,62.45,62.48,63.45,
21
+ 19,11/18/2019,63.39,80.47,70.57,63.28,63.3,64.1,63.17,63.43,63.46,63.3,64.88,63.2,63.46,63.64,63.43,63.41,63.79,
22
+ 20,11/25/2019,62.43,80.44,73.89,63.37,63.37,63.49,63.27,63.52,63.53,63.38,63.85,63.27,63.53,63.72,63.42,63.52,64.46,
23
+ 21,12/2/2019,64.39,80.41,69.95,62.41,62.39,61.48,62.3,62.57,62.54,62.38,62.02,62.28,62.54,62.69,62.39,62.52,62.42,
24
+ 22,12/9/2019,65.22,80.39,75.31,64.37,64.42,66.36,64.27,64.51,64.57,64.43,64.86,64.33,64.58,64.74,64.37,64.44,64.71,
25
+ 23,12/16/2019,66.14,80.37,71.16,65.21,65.23,66.06,65.11,65.34,65.36,65.23,66.64,65.13,65.37,65.59,65.34,65.38,65.88,
26
+ 24,12/23/2019,68.16,80.34,75.77,66.13,66.15,67.07,66.03,66.25,66.28,66.15,67.02,66.06,66.28,66.53,66.2,66.32,67.38,
27
+ 25,12/30/2019,68.6,80.32,73.38,68.15,68.2,70.19,68.06,68.25,68.31,68.21,69.62,68.13,68.32,68.62,68.26,68.38,69.41,
28
+ 26,1/6/2020,64.98,80.31,75.94,68.59,68.6,69.05,68.51,68.69,68.7,68.6,69.86,68.53,68.71,69.04,68.72,68.89,69.77,
29
+ 27,1/13/2020,64.85,80.28,70.28,64.96,64.87,61.36,64.87,65.1,65,64.86,63.45,64.77,64.98,65.19,64.89,65.18,64.65,
30
+ 28,1/20/2020,60.69,80.26,75.31,64.83,64.83,64.73,64.74,64.97,64.97,64.83,62.93,64.74,64.97,65.05,64.63,64.8,63.67,
31
+ 29,1/27/2020,58.16,80.23,66.89,60.67,60.56,56.53,60.56,60.84,60.72,60.55,58.6,60.44,60.71,60.69,60.55,60.58,58.14,
32
+ 30,2/3/2020,54.47,80.19,72.23,58.13,58.07,55.63,58.01,58.33,58.26,58.06,54.79,57.94,58.25,58.06,57.82,57.8,55.83,
33
+ 31,2/10/2020,57.32,80.16,63.95,54.44,54.34,50.78,54.3,54.66,54.56,54.33,51.38,54.19,54.54,54.24,54.18,53.97,51.04,
34
+ 32,2/17/2020,58.5,80.12,74.07,57.29,57.37,60.18,57.16,57.49,57.59,57.38,56.81,57.25,57.6,57.32,57.16,56.78,56.09,
35
+ 33,2/24/2020,50.52,80.09,65.88,58.48,58.51,59.69,58.35,58.66,58.7,58.51,60.55,58.39,58.71,58.6,58.68,58.25,58.71,
36
+ 34,3/2/2020,45.27,80.04,66.03,50.48,50.28,42.53,50.33,50.74,50.51,50.26,47.24,50.1,50.49,50.24,50.33,50.25,49.34,
37
+ 35,3/9/2020,33.85,79.99,61.05,45.23,45.07,40.02,45.05,45.52,45.36,45.05,38.62,44.87,45.33,44.8,44.63,44.5,41.14,
38
+ 36,3/16/2020,26.98,79.92,55.1,33.79,33.37,22.42,33.57,34.15,33.71,33.31,25.58,33.09,33.64,32.79,32.99,32.6,25.71,
39
+ 37,3/23/2020,24.93,79.84,54.16,26.91,26.62,20.11,25.45,27.29,27.01,26.55,17.76,26.31,26.93,25.66,25.78,25.13,18.98,
40
+ 38,3/30/2020,34.11,79.76,53.07,24.85,24.77,22.88,23.32,25.25,25.18,24.75,20.41,24.49,25.16,23.78,24.27,23.08,18.14,
41
+ 39,4/6/2020,31.48,79.69,62.37,34.05,34.47,43.31,33.8,34.41,34.89,34.52,37.62,34.29,34.95,33.91,34.37,33.09,34.33,
42
+ 40,4/13/2020,28.08,79.61,51.38,31.41,31.29,28.85,31.18,31.79,31.66,31.29,34.9,31.07,31.67,31.24,31.88,30.89,33.24,
43
+ 41,4/20/2020,21.44,79.54,58.23,28.01,27.87,24.68,27.76,28.39,28.26,27.85,25.07,27.61,28.24,27.75,27.71,27.37,28.94,
44
+ 42,4/27/2020,25.29,79.45,45.8,21.36,21.06,14.8,20.39,21.76,21.47,21.02,16.43,20.76,21.42,20.82,20.84,20.47,17.17,
45
+ 43,5/4/2020,30.97,79.37,60.61,25.22,25.39,29.15,24.94,25.61,25.82,25.4,23.83,25.14,25.83,25.13,25.01,24.42,23.18,
46
+ 44,5/11/2020,32.5,79.29,52.18,30.9,31.16,36.67,30.66,31.27,31.57,31.19,35.75,30.96,31.61,31.29,31.39,30.66,32.23,
47
+ 45,5/18/2020,35.13,79.22,61.23,32.44,32.5,34.04,32.2,32.8,32.88,32.52,36.13,32.3,32.91,32.95,32.82,32.49,36.21,
48
+ 46,5/25/2020,35.33,79.16,55.28,35.07,35.19,37.77,34.85,35.42,35.57,35.21,37.22,35,35.59,35.76,35.29,35.28,38.33,
49
+ 47,6/1/2020,42.3,79.09,60.84,35.27,35.28,35.54,35.05,35.62,35.64,35.28,36.76,35.08,35.65,35.95,35.43,35.53,36.8,
50
+ 48,6/8/2020,38.73,79.04,62.06,42.25,42.58,49.29,42.06,42.56,42.93,42.62,45.88,42.44,42.97,43.34,42.61,42.75,45.58,
51
+ 49,6/15/2020,42.19,78.98,57.62,38.68,38.51,35.16,38.48,39,38.84,38.5,40.51,38.32,38.83,39.44,38.92,39.16,40.06,
52
+ 50,6/22/2020,41.02,78.92,64.79,42.14,42.3,45.66,41.95,42.45,42.63,42.31,42.09,42.13,42.64,43.07,42.08,42.52,44.24,
53
+ 51,6/29/2020,43.14,78.87,57.09,40.97,40.92,39.85,40.78,41.28,41.24,40.92,42.21,40.74,41.24,41.75,41.13,41.36,40.78,
54
+ 52,7/6/2020,43.24,78.81,66.03,43.09,43.18,45.27,42.91,43.39,43.5,43.19,43.6,43.02,43.51,43.95,43.12,43.42,44.5,
55
+ 53,7/13/2020,43.14,78.76,57.88,43.19,43.2,43.35,43.02,43.49,43.5,43.2,44.38,43.03,43.51,43.99,43.33,43.54,43.69,
56
+ 54,7/20/2020,43.34,78.71,65.21,43.09,43.09,43.05,42.92,43.39,43.4,43.09,43.15,42.92,43.4,43.83,43.1,43.37,43.79,
57
+ 55,7/27/2020,43.3,78.66,58.62,43.29,43.3,43.55,43.12,43.59,43.61,43.3,43.39,43.14,43.61,44,43.3,43.51,43.41,
58
+ 56,8/3/2020,44.4,78.6,64.57,43.25,43.25,43.27,43.08,43.55,43.56,43.25,43.39,43.09,43.56,43.91,43.27,43.43,43.33,
59
+ 57,8/10/2020,44.8,78.55,60.07,44.36,44.4,45.51,44.18,44.64,44.7,44.41,44.93,44.25,44.71,45.04,44.4,44.53,44.82,
60
+ 58,8/17/2020,44.35,78.5,64.51,44.76,44.77,45.21,44.59,45.04,45.07,44.78,45.56,44.62,45.07,45.43,44.85,44.95,45.33,
61
+ 59,8/24/2020,45.05,78.45,59.97,44.31,44.29,43.91,44.14,44.59,44.58,44.29,44.34,44.13,44.58,44.91,44.31,44.46,44.68,
62
+ 60,8/31/2020,42.66,78.41,64.73,45.01,45.04,45.76,44.84,45.28,45.33,45.04,45.17,44.88,45.33,45.62,45.01,45.14,45.25,
63
+ 61,9/7/2020,39.83,78.35,58.12,42.61,42.52,40.27,42.44,42.91,42.81,42.51,41.85,42.34,42.8,43.07,42.56,42.67,41.98,
64
+ 62,9/14/2020,43.15,78.3,61.53,39.78,39.67,37,39.6,40.09,39.98,39.65,37.22,39.47,39.96,40.07,39.51,39.64,38.23,
65
+ 63,9/21/2020,41.92,78.25,61.39,43.1,43.24,46.48,42.93,43.39,43.56,43.26,43.35,43.09,43.57,43.62,43.08,42.99,42.53,
66
+ 64,9/28/2020,39.27,78.19,60.34,41.87,41.82,40.69,41.7,42.17,42.12,41.82,43.01,41.65,42.12,42.3,42.03,41.88,41.84,
67
+ 65,10/5/2020,42.85,78.14,58.81,39.22,39.12,36.62,39.04,39.53,39.43,39.1,37.34,38.93,39.42,39.51,39.04,39.1,38.96,
68
+ 66,10/12/2020,42.93,78.08,63.45,42.8,42.95,46.44,42.63,43.09,43.26,42.96,43.27,42.8,43.28,43.33,42.8,42.72,42.73,
69
+ 67,10/19/2020,41.77,78.03,59.21,42.88,42.88,43.02,42.72,43.17,43.18,42.89,44.8,42.73,43.19,43.4,43.1,42.97,43.43,
70
+ 68,10/26/2020,37.46,77.98,61.98,41.72,41.68,40.61,41.55,42.02,41.98,41.67,41.24,41.51,41.98,42.16,41.68,41.76,42.52,
71
+ 69,11/2/2020,39.45,77.92,55.42,37.41,37.24,33.15,37.22,37.73,37.56,37.22,34.75,37.04,37.53,37.61,37.16,37.26,35.62,
72
+ 70,11/9/2020,42.78,77.87,63.22,39.4,39.48,41.45,39.21,39.71,39.81,39.49,38.24,39.31,39.82,39.76,39.23,39.18,38.22,
73
+ 71,11/16/2020,44.96,77.82,59.06,42.73,42.86,46.12,42.56,43.02,43.17,42.88,45.44,42.72,43.2,43.3,42.99,42.75,43.29,
74
+ 72,11/23/2020,48.18,77.77,64.83,44.92,45,47.15,44.76,45.19,45.29,45.02,47.73,44.87,45.31,45.58,45.2,45.13,47.5,
75
+ 73,11/30/2020,49.25,77.73,62.44,48.14,48.27,51.41,48,48.39,48.54,48.29,50.89,48.16,48.56,48.94,48.41,48.5,51.08,
76
+ 74,12/7/2020,49.97,77.68,65.58,49.21,49.25,50.33,49.08,49.45,49.5,49.26,51.42,49.14,49.52,50,49.45,49.65,51.44,
77
+ 75,12/14/2020,52.26,77.65,63.32,49.93,49.96,50.7,49.8,50.17,50.21,49.97,50.88,49.84,50.22,50.69,50.03,50.34,51.59,
78
+ 76,12/21/2020,51.29,77.61,67.46,52.23,52.32,54.56,52.1,52.44,52.55,52.34,53.76,52.22,52.57,53.05,52.37,52.65,53.63,
79
+ 77,12/28/2020,51.34,77.57,62.73,51.26,51.21,50.32,51.13,51.48,51.44,51.21,51.98,51.09,51.44,51.94,51.35,51.64,52.01,
80
+ 78,1/4/2021,55.99,77.53,67.08,51.31,51.31,51.4,51.18,51.53,51.54,51.31,50.88,51.19,51.54,51.93,51.25,51.57,51.72,
81
+ 79,1/11/2021,55.1,77.5,67.32,55.96,56.16,60.65,55.85,56.15,56.36,56.18,58.32,56.08,56.39,56.8,56.17,56.33,57.29,
82
+ 80,1/18/2021,55.41,77.47,66.25,55.07,55.03,54.21,54.97,55.26,55.22,55.03,57.03,54.93,55.23,55.77,55.31,55.51,56.48,
83
+ 81,1/25/2021,55.88,77.44,67.48,55.38,55.4,55.73,55.28,55.57,55.59,55.4,55.12,55.3,55.6,56.03,55.35,55.7,56.64,55.13
84
+ 82,2/1/2021,59.34,77.41,66.76,55.85,55.87,56.36,55.75,56.04,56.07,55.88,56.28,55.78,56.07,56.46,55.89,56.13,55.88,55.61
85
+ 83,2/8/2021,62.43,77.38,70.58,59.32,59.46,62.81,59.22,59.47,59.63,59.48,61.3,59.39,59.65,60.06,59.5,59.66,60.78,59.16
86
+ 84,2/15/2021,62.91,77.36,69.89,62.41,62.54,65.53,62.33,62.54,62.68,62.56,65.72,62.49,62.71,63.24,62.75,62.92,64.86,62.39
87
+ 85,2/22/2021,66.13,77.34,70.94,62.89,62.91,63.4,62.82,63.02,63.04,62.92,64.72,62.85,63.05,63.65,63.1,63.43,65.25,62.69
88
+ 86,3/1/2021,69.36,77.33,72.91,66.12,66.25,69.36,66.05,66.21,66.36,66.27,67.97,66.22,66.39,66.96,66.29,66.67,68.35,66.27
89
+ 87,3/8/2021,69.22,77.31,74.05,69.35,69.49,72.6,69.3,69.42,69.57,69.51,72.6,69.47,69.59,70.26,69.69,70.02,71.75,69.48
90
+ 88,3/15/2021,64.53,77.3,72.87,69.21,69.2,69.09,69.17,69.28,69.27,69.21,70.8,69.16,69.28,69.98,69.4,69.85,71.32,68.82
91
+ 89,3/22/2021,64.57,77.29,69.63,64.52,64.31,59.84,64.46,64.63,64.41,64.29,62.14,64.23,64.38,64.91,64.29,64.84,63.89,63.8
92
+ 90,3/29/2021,64.86,77.27,72.62,64.56,64.57,64.62,64.49,64.67,64.68,64.56,62.22,64.5,64.67,64.92,64.29,64.64,62.89,64.43
93
+ 91,4/5/2021,62.95,77.25,70.12,64.85,64.86,65.16,64.78,64.95,64.97,64.86,65.03,64.8,64.97,65.19,64.86,64.92,63.53,64.68
94
+ 92,4/12/2021,66.77,77.23,70.64,62.93,62.85,61.04,62.87,63.06,62.97,62.84,62.15,62.77,62.96,63.14,62.86,62.94,62.42,62.57
95
+ 93,4/19/2021,66.11,77.22,73.66,66.76,66.93,70.6,66.7,66.85,67.03,66.94,67.7,66.89,67.05,67.17,66.82,66.82,67.48,67.02
96
+ 94,4/26/2021,67.25,77.2,70.27,66.1,66.06,65.46,66.04,66.19,66.16,66.07,67.73,66.01,66.16,66.43,66.29,66.27,66.65,65.72
97
+ 95,5/3/2021,68.28,77.19,74.42,67.24,67.29,68.4,67.19,67.33,67.38,67.29,67.49,67.25,67.39,67.6,67.25,67.39,68.59,67.17
98
+ 96,5/10/2021,68.71,77.17,71.54,68.27,68.31,69.32,68.22,68.35,68.39,68.32,69.37,68.28,68.4,68.65,68.38,68.46,68.83,68.14
99
+ 97,5/17/2021,66.44,77.16,74.57,68.7,68.72,69.15,68.66,68.77,68.79,68.72,69.45,68.68,68.8,69.06,68.78,68.91,69.58,68.47
100
+ 98,5/24/2021,69.63,77.15,69.69,66.43,66.33,64.17,66.38,66.52,66.42,66.32,65.54,66.27,66.41,66.63,66.35,66.53,66.15,65.91
101
+ 99,5/31/2021,71.89,77.14,77.09,69.62,69.76,72.83,69.58,69.69,69.84,69.77,70.06,69.73,69.85,69.98,69.63,69.72,70.04,69.87
102
+ 100,6/7/2021,72.69,77.13,72.36,71.89,71.98,74.16,71.85,71.93,72.03,71.99,74.63,71.96,72.05,72.32,72.17,72.16,73.08,71.79
103
+ 101,6/14/2021,73.51,77.12,77.43,72.69,72.72,73.5,72.66,72.72,72.76,72.72,74.24,72.7,72.77,73.1,72.85,73.01,74.76,72.3
104
+ 102,6/21/2021,76.18,77.12,73.52,73.51,73.54,74.34,73.48,73.54,73.57,73.55,74.33,73.52,73.58,73.91,73.59,73.82,74.78,73.12
105
+ 103,6/28/2021,76.17,77.12,79.57,76.18,76.29,78.86,76.16,76.18,76.31,76.31,77.92,76.3,76.32,76.67,76.35,76.55,77.63,76
106
+ 104,7/5/2021,75.55,77.12,74,76.17,76.17,76.17,76.16,76.17,76.17,76.17,77.52,76.16,76.18,76.58,76.33,76.56,77.37,75.39
107
+ 105,7/12/2021,73.59,77.11,78.54,75.55,75.52,74.94,75.54,75.56,75.53,75.52,75.24,75.51,75.53,75.86,75.52,75.83,76.17,74.77
108
+ 106,7/19/2021,74.1,77.11,72.57,73.59,73.51,71.63,73.57,73.62,73.53,73.49,72.31,73.47,73.52,73.75,73.46,73.72,72.71,72.71
109
+ 107,7/26/2021,76.33,77.1,78.52,74.1,74.12,74.62,74.08,74.12,74.15,74.12,73.37,74.1,74.15,74.27,74.01,74.14,73.39,73.69
110
+ 108,8/2/2021,70.7,77.1,75.1,76.33,76.43,78.57,76.32,76.33,76.44,76.44,77.7,76.43,76.45,76.59,76.46,76.46,76.66,76.06
111
+ 109,8/9/2021,70.59,77.09,73.06,70.69,70.46,65.07,70.67,70.75,70.49,70.43,69.05,70.4,70.47,70.62,70.58,70.7,69.75,69.36
112
+ 110,8/16/2021,65.18,77.09,74.82,70.58,70.59,70.49,70.55,70.64,70.65,70.58,67.68,70.55,70.64,70.53,70.26,70.37,69.27,70.34
113
+ 111,8/23/2021,72.7,77.07,68.22,65.17,64.94,59.77,65.12,65.27,65.03,64.92,62.46,64.86,65,64.85,64.93,64.82,61.58,64.32
114
+ 112,8/30/2021,72.61,77.06,81.19,72.7,72.98,80.24,72.66,72.73,73.04,73,73.62,72.98,73.07,72.85,72.66,72.42,73.23,73.74
115
+ 113,9/6/2021,72.92,77.06,69.18,72.61,72.59,72.53,72.58,72.64,72.63,72.6,76.43,72.58,72.64,72.74,73.06,72.71,73.64,71.9
116
+ 114,9/13/2021,75.34,77.05,80.49,72.92,72.93,73.24,72.89,72.95,72.96,72.93,73.03,72.91,72.97,73.05,72.92,73,75.32,72.49
117
+ 115,9/20/2021,78.09,77.05,72.33,75.34,75.43,77.77,75.32,75.35,75.45,75.44,76.69,75.42,75.46,75.58,75.45,75.48,76.24,75.17
118
+ 116,9/27/2021,79.28,77.05,82.35,78.09,78.19,80.85,78.09,78.08,78.19,78.21,80.68,78.2,78.2,78.44,78.35,78.39,79.98,77.76
119
+ 117,10/4/2021,82.39,77.05,74.24,79.29,79.33,80.48,79.28,79.26,79.3,79.34,81.28,79.34,79.31,79.63,79.5,79.66,81.42,78.54
120
+ 118,10/11/2021,84.86,77.06,84.55,82.4,82.52,85.51,82.41,82.34,82.47,82.53,84.53,82.54,82.49,82.85,82.6,82.83,84.71,81.95
121
+ 119,10/18/2021,85.53,77.07,77.36,84.87,84.96,87.34,84.89,84.8,84.89,84.98,87.67,85,84.91,85.37,85.16,85.42,87.18,84.18
122
+ 120,10/25/2021,84.38,77.08,84.58,85.54,85.57,86.21,85.57,85.46,85.48,85.57,87.13,85.6,85.49,85.97,85.72,86.09,87.61,84.55
123
+ 121,11/1/2021,82.74,77.09,76.91,84.39,84.35,83.23,84.41,84.32,84.27,84.34,84.16,84.36,84.26,84.67,84.39,84.81,85,83.14
124
+ 122,11/8/2021,82.17,77.1,82.46,82.75,82.69,81.1,82.77,82.69,82.62,82.68,81.35,82.69,82.61,82.88,82.61,82.98,81.99,81.46
125
+ 123,11/15/2021,78.89,77.11,76.85,82.18,82.16,81.61,82.19,82.13,82.1,82.15,81.06,82.17,82.1,82.25,82.05,82.27,81.04,81.08
126
+ 124,11/22/2021,72.72,77.11,78.99,78.9,78.77,75.61,78.9,78.87,78.74,78.75,76.99,78.75,78.72,78.77,78.72,78.84,77.09,77.46
127
+ 125,11/29/2021,69.88,77.1,71.36,72.72,72.47,66.55,72.7,72.75,72.49,72.43,68.02,72.4,72.44,72.28,72.24,72.34,69.3,71.26
128
+ 126,12/6/2021,75.15,77.09,75.74,69.87,69.76,67.04,69.84,69.94,69.82,69.74,65.34,69.7,69.79,69.36,69.35,69.23,65.7,69.22
129
+ 127,12/13/2021,73.52,77.09,76.55,75.15,75.37,80.43,75.13,75.16,75.4,75.39,76.32,75.38,75.43,75.02,75.21,74.74,74.01,75.69
130
+ 128,12/20/2021,76.85,77.09,74.31,73.52,73.44,71.89,73.5,73.55,73.47,73.44,75.41,73.42,73.47,73.33,73.76,73.35,73.98,72.55
131
+ 129,12/27/2021,79.2,77.09,79.42,76.85,76.99,80.19,76.84,76.85,77,77,77.66,76.99,77.01,76.87,76.89,76.76,79.01,76.84
132
+ 130,1/3/2022,81.75,77.09,76.89,79.21,79.29,81.56,79.2,79.18,79.28,79.31,82.06,79.31,79.3,79.34,79.51,79.34,80.69,78.69
133
+ 131,1/10/2022,86.06,77.1,81.56,81.76,81.86,84.31,81.77,81.71,81.82,81.88,84.21,81.89,81.84,82,82.01,82.03,84.48,81.18
134
+ 132,1/17/2022,87.89,77.11,81.24,86.08,86.25,90.38,86.1,85.98,86.17,86.28,89.49,86.31,86.2,86.49,86.43,86.53,89.15,85.77
135
+ 133,1/24/2022,90.03,77.12,83.23,87.91,87.98,89.73,87.94,87.8,87.87,87.99,90.99,88.03,87.89,88.33,88.26,88.48,90.84,87.12
136
+ 134,1/31/2022,93.27,77.14,83.39,90.05,90.14,92.18,90.09,89.92,90.02,90.15,92.02,90.19,90.03,90.49,90.26,90.64,92.74,89.43
137
+ 135,2/7/2022,94.44,77.16,86.24,93.29,93.43,96.52,93.34,93.14,93.28,93.45,95.96,93.51,93.31,93.81,93.58,93.95,95.69,93.02
138
+ 136,2/14/2022,93.54,77.18,84.72,94.47,94.51,95.62,94.52,94.3,94.34,94.52,96.67,94.58,94.36,94.92,94.73,95.13,96.66,93.97
139
+ 137,2/21/2022,97.93,77.2,85.31,93.56,93.52,92.64,93.62,93.41,93.36,93.52,93.7,93.57,93.35,93.85,93.6,94.08,94.66,92.8
140
+ 138,2/28/2022,118.11,77.23,88.82,97.96,98.15,102.33,98.03,97.77,97.97,98.17,99.64,98.24,97.99,98.4,98.1,98.48,99.44,98.17
141
+ 139,3/7/2022,112.67,77.29,104.19,118.17,119.22,138.32,119.13,117.81,118.92,119.37,130.38,119.52,119.08,119.74,119.58,119.66,126.28,120.47
142
+ 140,3/14/2022,107.93,77.33,85.13,112.72,112.47,107.23,112.86,112.4,112.11,112.48,120.58,112.6,112.12,113.51,113.71,114.38,119.6,112.78
143
+ 141,3/21/2022,120.65,77.37,98.32,107.97,107.78,103.19,108.09,107.69,107.47,107.75,102.84,107.85,107.43,108.28,107.5,108.76,111.07,107.72
144
+ 142,3/28/2022,107.67,77.43,97.94,120.71,121.19,133.39,121.39,120.34,120.85,121.21,124.66,121.37,120.88,121.61,121.01,121.56,121.38,120.87
145
+ 143,4/4/2022,102.78,77.47,86.41,107.71,107.47,94.68,107.84,107.42,107.11,107.45,107.99,107.56,107.08,107.67,108.06,108.83,106.29,107.71
146
+ 144,4/11/2022,111.7,77.5,92.55,102.82,102.7,97.89,102.91,102.57,102.43,102.68,93.75,102.77,102.4,102.47,102.18,102.8,101.48,102.33
147
+ 145,4/18/2022,106.65,77.55,95.15,111.75,111.94,120.64,111.86,111.42,111.65,111.94,113.7,112.06,111.65,111.83,111.82,111.64,108.04,112.44
148
+ 146,4/25/2022,109.34,77.58,88.15,106.69,106.61,101.6,106.8,106.41,106.29,106.6,108.69,106.71,106.29,106.46,106.86,107.03,106.12,106.47
149
+ 147,5/2/2022,112.39,77.62,97.1,109.39,109.42,112.04,109.49,109.08,109.13,109.43,108.11,109.54,109.13,109.25,109.27,109.37,111.87,109.43
150
+ 148,5/9/2022,111.55,77.67,91.72,112.44,112.48,115.45,112.56,112.11,112.16,112.49,115.27,112.61,112.17,112.39,112.56,112.6,112.3,112.4
151
+ 149,5/16/2022,112.55,77.71,95.94,111.6,111.58,110.71,111.72,111.28,111.25,111.58,112.69,111.7,111.25,111.45,111.67,111.89,113.29,111.46
152
+ 150,5/23/2022,119.43,77.76,93.03,112.6,112.61,113.56,112.72,112.27,112.29,112.61,112.63,112.74,112.29,112.45,112.59,112.78,113.73,112.47
153
+ 151,5/30/2022,119.72,77.81,102.09,119.49,119.6,126.32,119.63,119.11,119.24,119.6,123.35,119.75,119.25,119.59,119.62,119.73,121.54,119.29
154
+ 152,6/6/2022,122.01,77.87,94.08,119.78,119.78,120.02,119.93,119.4,119.4,119.78,123.36,119.93,119.4,119.8,119.97,120.36,122.4,119.64
155
+ 153,6/13/2022,113.12,77.92,103.61,122.07,122.11,124.31,122.23,121.68,121.72,122.11,123.3,122.26,121.73,122.12,122.11,122.56,125.4,121.87
156
+ 154,6/20/2022,113.12,77.97,86.71,113.17,113.05,104.22,113.3,112.84,112.67,113.04,109.9,113.17,112.66,112.73,113.11,113.64,111.26,113.2
157
+ 155,6/27/2022,116.26,78.01,102.28,113.17,113.17,113.13,113.29,112.84,112.84,113.17,108.59,113.29,112.83,112.72,112.91,113.02,111.08,112.97
LSTM.csv ADDED
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1
+ ,Interval,Train Split,MSE,MAPE,Time(s)
2
+ 0,WEEKLY,0.800,21.620,0.037,64.472
3
+ 1,WEEKLY,0.500,18.274,0.055,110.962
4
+ 2,WEEKLY,0.600,16.338,0.049,107.289
5
+ 3,DAILY,0.800,5.557,0.017,108.447
6
+ 4,DAILY,0.500,5.753,0.031,82.932
7
+ 5,DAILY,0.600,4.152,0.021,83.907
8
+ 6,QUARTERLY,0.800,446.106,0.161,357.064
9
+ 7,QUARTERLY,0.500,866.302,0.459,484.589
10
+ 8,QUARTERLY,0.600,566.090,0.285,428.251
11
+ 9,MONTHLY,0.800,56.275,0.075,134.905
12
+ 10,MONTHLY,0.500,75.015,0.132,187.441
13
+ 11,MONTHLY,0.600,62.747,0.116,260.177
Slider.jpg ADDED
StandardDeviation.csv ADDED
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1
+ ,Interval,Start Date,Standard Deviation
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+ 0,1wk,2015-06-30,18.155
3
+ 1,1wk,2017-06-30,18.635
4
+ 2,1wk,2019-06-30,23.053
5
+ 3,1wk,2020-06-30,23.627
6
+ 4,1d,2015-06-30,18.016
7
+ 5,1d,2017-06-30,18.462
8
+ 6,1d,2019-06-30,22.748
9
+ 7,1d,2020-06-30,23.113
10
+ 8,3mo,2015-06-30,20.902
11
+ 9,3mo,2017-06-30,21.113
12
+ 10,3mo,2019-06-30,26.860
13
+ 11,3mo,2020-06-30,27.803
14
+ 12,1mo,2015-06-30,17.872
15
+ 13,1mo,2017-06-30,18.260
16
+ 14,1mo,2019-06-30,22.806
17
+ 15,1mo,2020-06-30,22.930
assets/images/Accuracy.png ADDED
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1
+ from statsmodels.tsa.arima_model import ARIMAResults
2
+ import streamlit as st
3
+ import pandas as pd
4
+ import yfinance as yf
5
+ import matplotlib.pyplot as plt
6
+ import numpy as np
7
+ import plotly.express as px
8
+ import joblib
9
+ import math
10
+ from statsmodels.tsa.arima_model import ARIMA
11
+ from sklearn.metrics import mean_absolute_percentage_error, mean_squared_error, mean_absolute_error
12
+ import tensorflow as tf
13
+ from tensorflow import keras
14
+ from keras.models import Sequential
15
+ from keras.layers import Dense, LSTM
16
+ from tensorflow.keras import layers
17
+ from tensorflow.keras.optimizers import Adam
18
+ from tensorflow.keras.callbacks import ModelCheckpoint
19
+
20
+ # page expands to full width
21
+ st.set_page_config(page_title="LSTM vs ARIMA", layout='wide')
22
+
23
+ # PAGE LAYOUT
24
+ # heading
25
+ st.title("Crude Oil Benchmark Stock Price Prediction LSTM and ARIMA Models")
26
+ st.subheader("""Β© Castillon, Ignas, Wong""")
27
+
28
+ # ARIMA PARAMETERS
29
+ pValue = 4
30
+ dValue = 1
31
+ qValue = 0
32
+
33
+
34
+ # sidebar
35
+ # Sidebar - Specify parameter settings
36
+ with st.sidebar.header('Set Data Split'):
37
+ # PARAMETERS min,max,default,skip
38
+ trainData = st.sidebar.slider(
39
+ 'Data split ratio (% for Training Set)', 10, 90, 80, 5)
40
+ # st.write(trainData*.01)
41
+ accuracy = st.sidebar.select_slider(
42
+ 'Performance measure (accuracy Metrics)', options=['both', 'mse', 'mape'])
43
+ # ARIMA PARAMETERS
44
+ pValue = st.sidebar.number_input('P-value:', 0, 100, pValue)
45
+ st.sidebar.write('The current p-Value is ', pValue)
46
+ dValue = st.sidebar.number_input('D-value:', 0, 100, dValue)
47
+ st.sidebar.write('The current d-Value is ', dValue)
48
+ qValue = st.sidebar.number_input('Q-value:', 0, 100, qValue)
49
+ st.sidebar.write('The current q-Value is ', qValue)
50
+
51
+ # download
52
+
53
+ # model selection
54
+ modSelect = st.selectbox("Select Model for Prediction:",
55
+ ("ARIMA & LSTM", "LSTM", "ARIMA"))
56
+
57
+ # //show option selected
58
+ # st.write(modSelect)
59
+
60
+ # select time interval
61
+ interv = st.select_slider('Select Time Series Data Interval for Prediction', options=[
62
+ 'Weekly', 'Monthly', 'Quarterly', 'Yearly'])
63
+
64
+ # st.write(interv[0])
65
+
66
+ # Function to convert time series to interval
67
+
68
+
69
+ def getInterval(argument):
70
+ switcher = {
71
+ "W": "1wk",
72
+ "M": "1mo",
73
+ "Q": "3mo",
74
+ "Y": "1d"
75
+ }
76
+ return switcher.get(argument, "1d")
77
+
78
+
79
+ # show raw data
80
+ st.header("Raw Data")
81
+ # using button
82
+ # if st.button('Press to see Brent Crude Oil Raw Data'):
83
+ df = yf.download('BZ=F', interval=getInterval(interv[0]))
84
+ df
85
+
86
+ # graph visualization
87
+ st.header("Visualizations")
88
+ # LSTM
89
+
90
+
91
+ def df_to_X_y(df, window_size=5):
92
+ df_as_np = df.to_numpy()
93
+ X = []
94
+ y = []
95
+ for i in range(len(df_as_np)-window_size):
96
+ row = [[a] for a in df_as_np[i:i+window_size]]
97
+ X.append(row)
98
+ label = df_as_np[i+window_size]
99
+ y.append(label)
100
+ return np.array(X), np.array(y)
101
+
102
+
103
+ def mse_eval(test, predictions):
104
+ return mean_squared_error(test, predictions)
105
+
106
+
107
+ def mape_eval(test, predictions):
108
+ return mean_absolute_percentage_error(test, predictions)
109
+
110
+
111
+ def evaluate_lstm_model(split):
112
+ WINDOW_SIZE = 3
113
+ X1, y1 = df_to_X_y(df['Close'], WINDOW_SIZE)
114
+
115
+ # preprocessing
116
+ date_train, date_test = df.index[:int(
117
+ df.shape[0]*split)], df.index[int(df.shape[0]*split)+WINDOW_SIZE:]
118
+ X_train1, y_train1 = X1[:int(df.shape[0]*split)
119
+ ], y1[:int(df.shape[0]*split)]
120
+ X_test1, y_test1 = X1[int(df.shape[0]*split):], y1[int(df.shape[0]*split):]
121
+ # X_train1.shape, y_train1.shape, X_test1.shape, y_test1.shape
122
+
123
+ # lstm model
124
+ model = Sequential([layers.Input((3, 1)), layers.LSTM(64), layers.Dense(
125
+ 32, activation='relu'), layers.Dense(32, activation='relu'), layers.Dense(1)])
126
+ cp1 = ModelCheckpoint('model1/', save_best_only=True)
127
+ model.compile(loss='mse', optimizer=Adam(learning_rate=0.001),
128
+ metrics=['mean_absolute_percentage_error'])
129
+ model.fit(X_train1, y_train1, epochs=100, callbacks=[cp1])
130
+ model.summary()
131
+ # train predictions
132
+ train_predictions = model.predict(X_train1).flatten()
133
+ train_results = pd.DataFrame(
134
+ data={'Date': date_train, 'Close Prices': y_train1, 'Train Predictions': train_predictions})
135
+ # train_results
136
+
137
+ # test predictions
138
+ test_predictions = model.predict(X_test1).flatten()
139
+ test_results = pd.DataFrame(
140
+ data={'Date': date_test, 'Close Prices': y_test1, 'LSTM Predictions': test_predictions})
141
+ # test_results
142
+
143
+ # evaluate model
144
+ mse = mse_eval(test_results['Close Prices'],
145
+ test_results['LSTM Predictions'])
146
+ mape = mape_eval(test_results['Close Prices'],
147
+ test_results['LSTM Predictions'])
148
+ print(mse)
149
+ print(mape)
150
+ # # save to csv
151
+ # # csv file
152
+ # current_name_model = str('LSTM_'+str(split*100))
153
+ # predict = '/home/janna/1thesis/testingthesis/CSVPREDICTIONS_' + \
154
+ # current_name_model + '.csv'
155
+ # test_results.to_csv(predict, float_format='%.2f')
156
+
157
+ # plot orig price and predicted price
158
+ fig = px.line(test_results, x=test_results['Date'], y=["Close Prices", "LSTM Predictions"],
159
+ title="LSTM PREDICTED BRENT CRUDE OIL PRICES", width=1000)
160
+ st.plotly_chart(fig, use_container_width=True)
161
+ # VISUALIZE DATA
162
+ plt.figure(figsize=(24, 24))
163
+ plt.grid(True)
164
+ return test_results
165
+
166
+
167
+ results = evaluate_lstm_model(trainData*.01)
168
+ results
169
+ # # model
170
+
171
+ # ARIMA MODEL
172
+ # TRAIN,TEST,&SPLIT DATA
173
+
174
+ # split data
175
+ row = int(len(df)*(trainData*.01)) # 80% testing
176
+
177
+ trainingData = list(df[0:row]['Close'])
178
+ # len(trainingData)
179
+ testingData = list(df[row:]['Close'])
180
+ # len(testingData)
181
+ # using historical data to predict future data
182
+
183
+ predictions = []
184
+ nObservations = len(testingData)
185
+
186
+ for i in range(nObservations):
187
+ model = ARIMA(trainingData, order=(pValue, dValue, qValue)) # p,d,q
188
+ # model = sm.tsa.arima.ARIMA(trainingData, order=(4,1,0)) #p,d,q
189
+ model_fit = model.fit()
190
+ output = model_fit.forecast()
191
+ yhat = list(output[0])[0]
192
+ predictions.append(yhat)
193
+ actualTestValue = testingData[i]
194
+ # update training set
195
+ trainingData.append(actualTestValue)
196
+ # print(output)
197
+ # break
198
+
199
+ # print summary
200
+ details = st.checkbox('Details')
201
+
202
+ arimamodsum = model_fit.summary()
203
+ if details:
204
+ st.write(arimamodsum)
205
+
206
+ # st.write(predictions)
207
+ predictionss = pd.DataFrame(predictions)
208
+ # df['ARIMApredictions'] = predictions
209
+
210
+ # df = pd.insert([predictionss])
211
+
212
+ # st.write(predictionss)
213
+ # df
214
+
215
+ testingSet = pd.DataFrame(testingData)
216
+ testingSet['ARIMApredictions'] = predictions
217
+ testingSet.columns = ['Close Prices', 'ARIMA Predictions']
218
+ testingSet
219
+
220
+ results["ARIMA Predictions"] = testingSet["ARIMA Predictions"]
221
+ results
222
+
223
+ # # plot orig price and predicted price
224
+ # fig = px.line(testingSet, x=testingSet.index, y=["Close Prices","ARIMA Predictions"],
225
+ # title="ARIMA PREDICTED BRENT CRUDE OIL PRICES", width=1000)
226
+ # st.plotly_chart(fig, use_container_width=True)
227
+
228
+ # plot orig price and predicted price
229
+ fig = px.line(results, x=results["Date"], y=["Close Prices", "ARIMA Predictions", "LSTM Predictions"],
230
+ title="BOTH PREDICTED BRENT CRUDE OIL PRICES", width=1000)
231
+ st.plotly_chart(fig, use_container_width=True)
232
+
233
+ # #VISUALIZE DATA
234
+ # plt.figure(figsize=(24,24))
235
+ # plt.grid(True)
236
+
237
+ # dateRange = df[row:].index
238
+
239
+ # plt.plot(dateRange, predictions, color='blue', marker = 'o', linestyle ='dashed', label='Predicted Brent Price')
240
+ # plt.plot(dateRange, testingData, color='red', label='Original Brent Price')
241
+
242
+ # plt.title(" ARIMA BRENT PRICE PREDICTION")
243
+ # plt.xlabel('Date')
244
+ # plt.ylabel('Price')
245
+ # plt.legend()
246
+ # plt.show()
247
+
248
+ mape = np.mean(np.abs(np.array(predictions) -
249
+ np.array(testingData))/np.abs(testingData))
250
+ mse = np.square(np.subtract(testingData, predictions)).mean()
251
+ MSE = mean_squared_error(testingData, predictions)
252
+ MAPE = mean_absolute_percentage_error(testingData, predictions)
253
+ MAE = mean_absolute_error(testingData, predictions)
254
+
255
+ st.write("MAPE: " + str(mape)) # Mean absolute Percentage Error
256
+ st.write("MAPE: " + str(MAPE)) # Mean absolute Percentage Error
257
+ st.write("MSE: " + str(mse)) # MSE
258
+ st.write("MSE: " + str(MSE)) # MSE
259
+
260
+ accTable = pd.DataFrame()
261
+ accTable['MAPE'] = [mape]
262
+ accTable['MSE'] = [mse]
263
+ accTable['Improved'] = [2200]
264
+
265
+ # accuracy metrics
266
+ st.header("Accuracy Metrics")
267
+
268
+ st.table(accTable)
269
+
270
+ # ______________________________________________________
271
+ # sample read from local file!!!
272
+ readfile = pd.read_csv('ARIMA/Sheets/ARIMA-WEEKLY.csv')
273
+ readfile
274
+
275
+ # load csv
276
+ # file = pd.read_csv('./PREDICTIONS_ARIMA_80.0.csv')
277
+ file = pd.read_csv('./PREDICTIONS_ARIMA_80.0_(4,2,2).csv')
278
+ file
279
+ # load model
280
+ # loaded = ARIMAResults.load('ARIMA_80.0.pkl')
281
+ loaded = ARIMAResults.load('ARIMA_80.0_(4, 2, 2).pkl')
282
+ st.write(loaded.summary())
283
+
284
+ # file['ARIMA Predictions']
285
+ # file['Close Prices']
286
+
287
+ # # evaluate model
288
+ # mse = float(mse_eval(file['Close Prices'],file['ARIMA Predictions']))
289
+ # mape = mape_eval(file['Close Prices'],file['ARIMA Predictions'])
290
+ # print("MSE: "+ str(mse))
291
+ # print("MAPE: "+ str(mape))
bestDaily.csv ADDED
@@ -0,0 +1,1851 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Date,Close Prices,"ARIMA_50.0_(0, 1, 0)_Predictions",LSTM_60.0_Predictions
2
+ 2/18/2015,60.53,62.52,
3
+ 2/19/2015,60.21,60.52,
4
+ 2/20/2015,60.22,60.2,
5
+ 2/23/2015,58.9,60.21,
6
+ 2/24/2015,58.66,58.89,
7
+ 2/25/2015,61.63,58.65,
8
+ 2/26/2015,60.05,61.62,
9
+ 2/27/2015,62.58,60.04,
10
+ 3/2/2015,59.54,62.57,
11
+ 3/3/2015,61.02,59.53,
12
+ 3/4/2015,60.55,61.01,
13
+ 3/5/2015,60.48,60.54,
14
+ 3/6/2015,59.73,60.47,
15
+ 3/9/2015,58.53,59.72,
16
+ 3/10/2015,56.39,58.52,
17
+ 3/11/2015,57.54,56.38,
18
+ 3/12/2015,57.08,57.53,
19
+ 3/13/2015,54.67,57.07,
20
+ 3/16/2015,53.44,54.66,
21
+ 3/17/2015,53.43,53.43,
22
+ 3/18/2015,55.91,53.42,
23
+ 3/19/2015,54.43,55.9,
24
+ 3/20/2015,55.32,54.42,
25
+ 3/23/2015,55.92,55.31,
26
+ 3/24/2015,55.11,55.91,
27
+ 3/25/2015,56.48,55.1,
28
+ 3/26/2015,59.19,56.47,
29
+ 3/27/2015,56.41,59.18,
30
+ 3/30/2015,56.29,56.4,
31
+ 3/31/2015,55.11,56.28,
32
+ 4/1/2015,57.1,55.1,
33
+ 4/2/2015,54.95,57.09,
34
+ 4/6/2015,58.12,54.94,
35
+ 4/7/2015,59.1,58.11,
36
+ 4/8/2015,55.55,59.09,
37
+ 4/9/2015,56.57,55.54,
38
+ 4/10/2015,57.87,56.56,
39
+ 4/13/2015,57.93,57.86,
40
+ 4/14/2015,58.43,57.92,
41
+ 4/15/2015,60.32,58.42,
42
+ 4/16/2015,60.4,60.31,
43
+ 4/17/2015,63.45,60.39,
44
+ 4/20/2015,63.45,63.44,
45
+ 4/21/2015,62.08,63.44,
46
+ 4/22/2015,62.73,62.07,
47
+ 4/23/2015,64.85,62.72,
48
+ 4/24/2015,65.28,64.84,
49
+ 4/27/2015,64.83,65.27,
50
+ 4/28/2015,64.64,64.82,
51
+ 4/29/2015,65.84,64.63,
52
+ 4/30/2015,66.78,65.83,
53
+ 5/1/2015,66.46,66.78,
54
+ 5/4/2015,66.45,66.46,
55
+ 5/5/2015,67.52,66.45,
56
+ 5/6/2015,67.77,67.52,
57
+ 5/7/2015,65.54,67.77,
58
+ 5/8/2015,65.39,65.53,
59
+ 5/11/2015,64.91,65.38,
60
+ 5/12/2015,66.86,64.9,
61
+ 5/13/2015,66.81,66.86,
62
+ 5/14/2015,66.59,66.81,
63
+ 5/15/2015,66.57,66.59,
64
+ 5/18/2015,66.27,66.57,
65
+ 5/19/2015,64.02,66.27,
66
+ 5/20/2015,65.03,64.01,
67
+ 5/21/2015,66.54,65.02,
68
+ 5/22/2015,65.37,66.54,
69
+ 5/26/2015,63.72,65.36,
70
+ 5/27/2015,62.06,63.71,
71
+ 5/28/2015,62.58,62.05,
72
+ 5/29/2015,65.56,62.57,
73
+ 6/1/2015,64.88,65.55,
74
+ 6/2/2015,65.49,64.87,
75
+ 6/3/2015,63.8,65.48,
76
+ 6/4/2015,62.03,63.79,
77
+ 6/5/2015,63.31,62.02,
78
+ 6/8/2015,62.69,63.3,
79
+ 6/9/2015,64.88,62.68,
80
+ 6/10/2015,65.7,64.87,
81
+ 6/11/2015,65.11,65.69,
82
+ 6/12/2015,63.87,65.1,
83
+ 6/15/2015,62.61,63.86,
84
+ 6/16/2015,62.63,62.6,
85
+ 6/17/2015,63.87,62.62,
86
+ 6/18/2015,64.26,63.86,
87
+ 6/19/2015,63.02,64.25,
88
+ 6/22/2015,63.34,63.01,
89
+ 6/23/2015,64.45,63.33,
90
+ 6/24/2015,63.49,64.44,
91
+ 6/25/2015,63.2,63.48,
92
+ 6/26/2015,63.26,63.19,
93
+ 6/29/2015,62.01,63.25,
94
+ 6/30/2015,63.59,62,
95
+ 7/1/2015,62.01,63.58,
96
+ 7/2/2015,62.07,62,
97
+ 7/6/2015,56.54,62.06,
98
+ 7/7/2015,56.85,56.53,
99
+ 7/8/2015,57.05,56.84,
100
+ 7/9/2015,58.61,57.04,
101
+ 7/10/2015,58.73,58.6,
102
+ 7/13/2015,57.85,58.72,
103
+ 7/14/2015,58.51,57.84,
104
+ 7/15/2015,57.05,58.5,
105
+ 7/16/2015,57.51,57.04,
106
+ 7/17/2015,57.52,57.5,
107
+ 7/20/2015,56.65,57.51,
108
+ 7/21/2015,57.04,56.64,
109
+ 7/22/2015,56.13,57.03,
110
+ 7/23/2015,55.27,56.12,
111
+ 7/24/2015,54.62,55.26,
112
+ 7/27/2015,53.47,54.61,
113
+ 7/28/2015,53.3,53.46,
114
+ 7/29/2015,53.38,53.29,
115
+ 7/30/2015,53.31,53.37,
116
+ 7/31/2015,52.21,53.3,
117
+ 8/3/2015,49.52,52.2,
118
+ 8/4/2015,49.99,49.51,
119
+ 8/5/2015,49.59,49.98,
120
+ 8/6/2015,49.52,49.58,
121
+ 8/7/2015,48.61,49.51,
122
+ 8/10/2015,50.41,48.6,
123
+ 8/11/2015,49.18,50.4,
124
+ 8/12/2015,49.66,49.17,
125
+ 8/13/2015,49.22,49.65,
126
+ 8/14/2015,49.03,49.21,
127
+ 8/17/2015,49.03,49.02,
128
+ 8/18/2015,48.81,49.02,
129
+ 8/19/2015,47.16,48.8,
130
+ 8/20/2015,46.62,47.15,
131
+ 8/21/2015,45.46,46.61,
132
+ 8/24/2015,42.69,45.44,
133
+ 8/25/2015,43.21,42.67,
134
+ 8/26/2015,43.14,43.19,
135
+ 8/27/2015,47.56,43.12,
136
+ 8/28/2015,50.05,47.55,
137
+ 8/31/2015,54.15,50.04,
138
+ 9/1/2015,49.56,54.14,
139
+ 9/2/2015,50.5,49.55,
140
+ 9/3/2015,50.68,50.49,
141
+ 9/4/2015,49.61,50.67,
142
+ 9/8/2015,49.52,49.6,
143
+ 9/9/2015,47.58,49.51,
144
+ 9/10/2015,48.89,47.57,
145
+ 9/11/2015,48.14,48.88,
146
+ 9/14/2015,46.37,48.13,
147
+ 9/15/2015,46.63,46.36,
148
+ 9/16/2015,46.61,46.62,
149
+ 9/17/2015,49.08,46.6,
150
+ 9/18/2015,47.47,49.07,
151
+ 9/21/2015,48.92,47.46,
152
+ 9/22/2015,49.08,48.91,
153
+ 9/23/2015,47.75,49.07,
154
+ 9/24/2015,48.17,47.74,
155
+ 9/25/2015,48.6,48.16,
156
+ 9/28/2015,47.34,48.59,
157
+ 9/29/2015,48.23,47.33,
158
+ 9/30/2015,48.37,48.22,
159
+ 10/1/2015,47.69,48.36,
160
+ 10/2/2015,48.13,47.68,
161
+ 10/5/2015,49.25,48.12,
162
+ 10/6/2015,51.92,49.24,
163
+ 10/7/2015,51.33,51.91,
164
+ 10/8/2015,53.05,51.32,
165
+ 10/9/2015,52.65,53.04,
166
+ 10/12/2015,49.86,52.64,
167
+ 10/13/2015,49.24,49.85,
168
+ 10/14/2015,49.15,49.23,
169
+ 10/15/2015,48.71,49.14,
170
+ 10/16/2015,48.73,48.7,
171
+ 10/19/2015,48.61,48.72,
172
+ 10/20/2015,48.71,48.6,
173
+ 10/21/2015,47.85,48.7,
174
+ 10/22/2015,48.08,47.84,
175
+ 10/23/2015,47.99,48.07,
176
+ 10/26/2015,47.54,47.98,
177
+ 10/27/2015,46.81,47.53,
178
+ 10/28/2015,49.05,46.8,
179
+ 10/29/2015,48.8,49.04,
180
+ 10/30/2015,49.56,48.79,
181
+ 11/2/2015,48.79,49.55,
182
+ 11/3/2015,50.54,48.78,
183
+ 11/4/2015,48.58,50.53,
184
+ 11/5/2015,47.98,48.57,
185
+ 11/6/2015,47.42,47.97,
186
+ 11/9/2015,47.19,47.41,
187
+ 11/10/2015,47.44,47.18,
188
+ 11/11/2015,45.81,47.43,
189
+ 11/12/2015,44.06,45.8,
190
+ 11/13/2015,43.61,44.04,
191
+ 11/16/2015,43.58,43.59,
192
+ 11/17/2015,43.57,43.56,
193
+ 11/18/2015,44.14,43.55,
194
+ 11/19/2015,44.18,44.12,
195
+ 11/20/2015,44.66,44.16,
196
+ 11/23/2015,44.83,44.64,
197
+ 11/24/2015,46.12,44.81,
198
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1696
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1697
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1698
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1699
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1700
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1701
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1702
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1703
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1704
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1705
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1706
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1707
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1708
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1709
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1710
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1711
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1712
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1713
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1714
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1715
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1716
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1717
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1718
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1719
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1720
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1721
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1722
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1723
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1724
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1725
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1726
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1727
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1728
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1729
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1730
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1731
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1732
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1733
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1734
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1735
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1736
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1737
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1738
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1739
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1740
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1741
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1742
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1743
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1744
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1745
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1746
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1747
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1748
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1749
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1750
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1751
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1752
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1753
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1754
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1755
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1756
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1757
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1758
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1759
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1760
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1761
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1762
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1763
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1764
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1765
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1766
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1767
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1768
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1769
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1770
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1771
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1772
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1773
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1774
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1775
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1776
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1777
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1778
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1779
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1780
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1781
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1782
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1783
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1784
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1785
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1786
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1787
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1788
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1789
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1790
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1791
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1792
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1793
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1794
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1795
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1796
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1797
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1798
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1799
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1800
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1801
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1802
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1803
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1804
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1805
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1806
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1807
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1808
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1809
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1810
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1811
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1812
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1813
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1814
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1815
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1816
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1817
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1818
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1819
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1820
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1821
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1822
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1823
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1824
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1825
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1826
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1827
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1828
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1829
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1830
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1831
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1832
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1833
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1834
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1835
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1836
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1837
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1838
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1839
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1840
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1841
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1842
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1843
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1844
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1845
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1846
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1847
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1848
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1849
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1850
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1851
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bestMonthly.csv ADDED
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1
+ Date,Close Prices,"ARIMA_60.0_(0, 1, 1)_Predictions",LSTM_80.0_Predictions
2
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3
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4
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5
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6
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7
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8
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9
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10
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11
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12
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13
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14
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15
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16
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17
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18
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19
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20
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21
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22
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23
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24
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25
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26
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27
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28
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29
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30
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31
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32
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33
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34
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35
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36
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37
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38
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39
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40
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41
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42
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43
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44
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45
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46
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47
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48
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49
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50
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51
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52
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53
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54
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55
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56
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57
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58
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59
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60
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61
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62
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63
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bestQuarterly.csv ADDED
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1
+ Date,Close Prices,"ARIMA_50.0_(0, 1, 0)_Predictions",LSTM_80.0_Predictions
2
+ 1/1/2015,55.11,55.87,
3
+ 4/1/2015,63.59,53.62,
4
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5
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6
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7
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8
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9
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10
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11
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12
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13
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14
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15
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16
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17
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18
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19
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20
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21
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22
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23
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24
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25
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26
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27
+ 4/1/2022,114.81,108.19,89.6
bestWeekly.csv ADDED
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1
+ Date,Close Prices,"ARIMA_50.0_(1, 0, 0)_Predictions",LSTM_80.0_Predictions
2
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3
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4
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5
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6
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7
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8
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9
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10
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11
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12
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13
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14
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15
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16
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17
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18
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19
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20
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21
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22
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23
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24
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25
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26
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27
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28
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29
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30
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31
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32
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33
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34
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35
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36
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37
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38
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39
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40
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41
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42
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43
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44
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45
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46
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47
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48
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49
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50
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51
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52
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53
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54
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55
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56
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57
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58
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59
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60
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61
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62
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63
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64
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65
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66
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67
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68
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69
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70
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71
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72
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73
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74
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75
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76
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77
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78
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79
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80
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81
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82
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83
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84
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85
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86
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87
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88
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89
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90
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91
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92
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93
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94
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95
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96
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97
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98
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99
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100
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101
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102
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103
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104
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105
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106
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107
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108
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110
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111
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112
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113
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114
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115
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116
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117
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118
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120
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121
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122
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123
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124
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125
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126
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127
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128
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129
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130
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131
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132
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133
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134
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135
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136
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137
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138
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139
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140
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141
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142
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143
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144
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145
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146
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147
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148
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149
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150
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151
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152
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153
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154
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155
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156
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157
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158
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159
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160
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161
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162
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163
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164
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165
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166
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167
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168
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169
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170
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171
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172
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173
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174
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175
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176
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177
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178
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179
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180
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181
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182
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183
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184
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185
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186
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187
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188
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189
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190
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191
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192
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193
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194
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195
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196
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197
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198
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199
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200
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201
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202
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203
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205
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207
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208
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209
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210
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211
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212
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213
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214
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215
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216
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217
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218
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220
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221
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222
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223
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224
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225
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226
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227
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228
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229
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230
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231
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232
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233
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234
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235
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236
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238
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240
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241
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244
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245
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246
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248
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252
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253
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255
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260
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261
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262
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263
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264
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265
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266
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268
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269
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270
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271
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272
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273
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275
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277
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280
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281
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282
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285
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286
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287
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288
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290
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291
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292
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293
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294
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295
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296
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297
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298
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300
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301
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302
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303
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304
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305
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306
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309
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310
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311
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312
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313
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315
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316
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317
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318
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319
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320
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321
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322
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323
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324
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325
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326
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327
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328
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329
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330
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331
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332
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333
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334
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335
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336
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337
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338
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339
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340
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341
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342
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343
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344
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345
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346
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347
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348
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349
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350
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351
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352
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353
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354
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355
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356
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357
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358
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359
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360
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361
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362
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363
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364
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365
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366
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367
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368
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369
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370
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371
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372
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373
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374
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375
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376
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377
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378
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379
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380
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381
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383
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384
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385
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386
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387
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388
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389
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390
+ 6/27/2022,116.26,112.84,112.97
pages/1_πŸ”Ž_About.py ADDED
@@ -0,0 +1,155 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import streamlit as st
2
+ from PIL import Image
3
+ import base64
4
+
5
+ # function play gif
6
+
7
+
8
+ def gif(location):
9
+ """### gif from local file"""
10
+ file_ = open(location, "rb")
11
+ contents = file_.read()
12
+ data_url = base64.b64encode(contents).decode("utf-8")
13
+ file_.close()
14
+
15
+ # return (st.markdown(
16
+ # f'<img src="data:image/gif;base64,{data_url}" alt="instructions gif">',
17
+ # unsafe_allow_html=True,
18
+ # ))
19
+ return (st.markdown(
20
+ f'<img src="data:image/gif;base64,{data_url}" alt="instructions gif" width="100%">',
21
+ unsafe_allow_html=True,
22
+ ))
23
+
24
+
25
+ hide_menu_style = """
26
+ <style>
27
+ #MainMenu{visibility: hidden;}
28
+ footer{visibility:hidden;}
29
+ </style>
30
+ """
31
+ # page expands to full width
32
+ st.set_page_config(page_title="Predicta.oil | About", layout='wide', page_icon="β›½")
33
+ st.markdown(hide_menu_style, unsafe_allow_html=True)
34
+ st.title('About the Research')
35
+
36
+ # a. how the thing works
37
+ st.header('How It Works')
38
+ st.markdown('<strong>Welcome!</strong> This is a fully interactive, multi-page web app through the Python library Streamlit that allows users to explore the same models used in the study. Aside from learning about study findings, play with parameters, create your own models, conduct your own comparisions and make your own analyses! Read further to learn how to use the <em>Explore</em> and <em>Make Your Own Model</em> tabs.', unsafe_allow_html=True)
39
+
40
+ # a.1 How to use the explore tab
41
+ st.markdown('### How to use the <a href="/Explore" target="_self" style="text-decoration:none; color: tomato;">πŸ“ˆ Explore</a>' ' tab', unsafe_allow_html=True)
42
+ # st.subheader("How to use the 'Explore' tab")
43
+ st.markdown('<p> The Explore tab allows you to <strong>select different models</strong> based on time intervals and test-train split data. <br> </p>', unsafe_allow_html=True)
44
+
45
+ st.markdown(
46
+ '<p> Use the slider to select whether or not you would like to see monthly, weekly, daily, or quarterly data being used. </p>', unsafe_allow_html=True)
47
+ gif('assets/images/Slider1.gif')
48
+
49
+
50
+ st.markdown('<p> Then, use the dropdown to select your split. </p>',
51
+ unsafe_allow_html=True)
52
+ gif('assets/images/Split1.gif')
53
+ # split = Image.open('assets/images/Split.jpg')
54
+ # st.image(split, caption='Explore Split')
55
+
56
+ st.markdown('<p> Afterwards, you can use the select tool to compare as many ARIMA models as you like, either against each other or against an LSTM model! </p>', unsafe_allow_html=True)
57
+ # select = Image.open('assets/images/Select.jpg')
58
+ # st.image(select, caption='Explore Select')
59
+ gif('assets/images/Select1.gif')
60
+
61
+
62
+ # a.2 How to use the Make a model tab
63
+ st.markdown('### How to use the <a href="Make_a_Model" target="_self" style="text-decoration:none; color: tomato;">πŸ“Š Make a Model</a>' ' tab', unsafe_allow_html=True)
64
+ st.markdown('<p> The Make a Model tab lets you <strong>create your own model</strong>! Choose the different parameters and test-train splits to your liking for an interactive experience with our time series models. <br> </p>', unsafe_allow_html=True)
65
+
66
+ st.markdown('<p> Use the slider to select your preferred time interval. You can also download the full raw data in CSV format by clicking the button below! </p>', unsafe_allow_html=True)
67
+ gif('assets/images/Slider1.gif')
68
+ gif('assets/images/Download_CSV.gif')
69
+
70
+ st.markdown('<p> Get acquanited with all the controls on the page by starting with the side menu. Here, you can adjust the train-test split and ARIMA p, d, and q values as you like! </p>', unsafe_allow_html=True)
71
+ # gif('assets/images/Set_pdq_values.gif')
72
+
73
+ st.markdown('<p> Check the "Details" box to expand the page for more information, and press the button to generate your model! </p>', unsafe_allow_html=True)
74
+ gif('assets/images/pdq.gif')
75
+
76
+ st.markdown('<p> You can view how your model fares against the original close prices on the chart, and even see how the model you made stacks up to accuracy metrics! </p>', unsafe_allow_html=True)
77
+ accuracy = Image.open('assets/images/make.png')
78
+ st.image(accuracy, caption='Visualization')
79
+
80
+ # b. snippets of the paper
81
+
82
+ st.markdown('<h1>Conclusions and Recommendations</h1> <p>The full documentation of this project can be accessed through this link: [] </p><h2>Conclusions</h2> <h3>Price Movement Volatility Trends</h3> <p> Price movement volatility refers to how much a set of prices changes over time and how erratic those changes are. In crude oil prices, unless there are spikes or drops due to unforeseen or anomalous circumstances, these trends tend to stray away from erratic highs and lows especially over short periods of time. It must be reiterated that this study does not take into account these anomalies, but focuses on what would be the natural, steady trend of Brent crude oil prices. That being said, the conduction of the study simply paints a clear picture of the behavior of asset prices and how the value of volatility changes over spans of time. </p> <p> In order to quantify volatility, the standard deviation between the actual close prices (prices from the yfinance dataset) and the predicted prices are computed. From this part of the experiment, it was found that volatility is more likely to be present over longer periods of time. Additionally, it can be observed that volatility is also contingent on anomalous or external factors.</p> <p>It was found that Brent crude oil in particular shows the highest volatility trend over quarterly prices.</p>', unsafe_allow_html=True)
83
+
84
+ st.markdown('<h3>Model Accuracy</h3> <p> Model accuracy is quantified through the use of accuracy metrics, specifically MAPE and MSE. These subsections are partitioned in accordance to the time interval of the raw data used, that being daily, weekly, monthly, and quarterly close prices.</p> <h4>Daily Interval Data</h4> <p>It was found that 96 of 102 or 94.12% ARIMA models and 3 of 3 or 100.00% LSTM models were able to attain a MAPE percentage below 10% and 96 of 102 or 94.12% ARIMA models and 3 of 3 or 100.00% LSTM models were able to attain a MSE percentage close to 0 or less than 0.1 using daily interval data.</p> <h4>Weekly Interval Data</h4> <p>It was found that 42 of 48 or 87.50% ARIMA models and 0 of 3 or 0.00% LSTM models were able to attain a MAPE percentage below 10% and 22 of 48 or 45.83% ARIMA models and 0 of 3 or 0.00% LSTM models were able to attain a MSE percentage close to 0 or less than 0.1 using weekly interval data.</p> <h4>Monthly Interval Data</h4> <p>It was found that 62 of 160 or 38.75% ARIMA model and 1 of 3 or 33.33% LSTM models were able to attain a MAPE percentage below 10% and 0 of 160 or 0.00% ARIMA models and 0 of 3 or 0.00% LSTM models were able to attain a MSE percentage close to 0 or less than 0.1 using monthly interval data. </p> <h4>Quarterly Interval Data</h4> <p>It was found that 0 of 77 or 0.00% ARIMA models and 0 of 3 or 0.00% LSTM models were able to attain a MAPE percentage below 10% and 0 of 77 or 0.00% ARIMA models and 0 of 3 or 0.00% LSTM models were able to attain a MSE percentage close to 0 or less than 0.1 using quarterly interval data.</p>', unsafe_allow_html=True)
85
+
86
+ st.markdown('<h3>Conclusion</h3> <p>It must be noted that despite most models falling short of the standards established, these standards are the most ideal values for MSE and MAPE that indicate the near-perfectness of a model. It must also be noted that the use of parameter grid search for the p, d, and q values of ARIMA effect the amounts of total ARIMA models. </p> <p> When presented with the entirety of both cumulative ARIMA and LSTM predictions against the entirely of close prices, it can be observed that closer intervals like daily and weekly render closer predictions than that of monthly and quarterly predictions. This can be attributed to the fact that within a pool of raw, close price data from 2007 to 2022, there is more data to work with given daily prices, 365 days a year, as opposed to monthly or quarterly prices that only account for 12 months and 3 months a year, respectively. This reflects in the aforementioned results of the MSE and MAPE, whose results act as supplementary metrics for accuracy comparison. </p>', unsafe_allow_html=True)
87
+
88
+ st.markdown('<h3>Model Comparison</h3> <p>Between the two models, the most accurate one will have the lowest percentage of models that have a MAPE percentage close to or less than 10\%, and MSE percentage close to 0, and the quickest runtimes. The quantification of performance is very reliant on the runtime as well. </p> <p> In terms of MSE accuracy and performance, it was found that ARIMA produced the highest percentage of most accurate models consistently throughout the four time intervals, in comparison to LSTM. On the other hand, in terms of MAPE accuracy and performance, ARIMA still proved to produce the highest percentage of outcomes over the time intervals as opposed to LSTM. The best ARIMA model rendered was through a 50% test-train split, completed with a run time of 18.755 milliseconds and parameters of (0,1,0).</p> <p> For daily close prices, ARIMA, with 94.12% of models accurate, fell short to LSTM which had 100.00% models accurate for MAPE. MSE rendered the same results for both model types. Weekly close prices had ARIMA boasting a 87.50% percentage in MAPE while LSTM rendered 0.00%. ARIMA scored a 45.83% for MSE while LSTM retained the same value of 0.00%. Monthly interval data returned 38.75% of ARIMA models and 33.33% of LSTM models for MAPE. MSE sae 0.00% for both ARIMA and LSTM. Lastly, quarterly close prices returned 0.00% for both models across both LSTM and ARIMA. </p> <p> From this comparison, it can be concluded that ARIMA is more consistent in having better accuracy than LSTM through these accuracy metrics. It can be also inferred that both LSTM and ARIMA fare better given closer time intervals, and in turn when there is more raw data to work with.</p> While the overall proximity to accuracy of either model was discussed, it can be noted that that there are model results that stand out from each model type. This is important as even though the best model might be from a certain model type, it does not effect the overall performance of the model. It can, however, illustrate how well either model can process data over specific intervals of time.<p> For reference, the best models of ARIMA and LSTM are presented. The best daily ARIMA model renders an MSE of 2.427 and a MAPE of 0.017 while the LSTM model renders 4.152 for MSE and 0.021 for MAPE; making ARIMA the best for daily. For weekly, ARIMA still performs better. However a shift becomes apparent for the best MAPE models for monthly and quarterly intervals. In terms of splits, 50 splits for ARIMA and 80 splits for LSTM made up most of the best models.</p><p> </p><p> In conclusion, the ARIMA model proves itself to be more accurate and more efficient. However, if individual accuracy metric outcomes are to be considered, the best metric for ARIMA is MSE and MAPE for daily, weekly, monthly, and quarterly prices, while the best metric for LSTM is MAPE for long term intervals like monthly and quarterly. In terms of split, ARIME needed less training time while LSTM required more training. </p>', unsafe_allow_html=True)
89
+
90
+ st.markdown('<h2>Recommendations</h2> <p>With the utilization of Google Colab in implementing the LSTM and ARIMA models, its collaboration-friendly environment and dedicated cloud storage service are good features for this study. However, the notebook has a disadvantage of having only a maximum of 12 hours runtime for each execution which is below the runtime of ARIMA models for the daily intervals, thus resulting to cutting off outputs. With this, the researchers recommend to run the models in local IDEs and saving the outputs in CSV to local storage as well. Moreover, for a more organized and secured compilation of output data, connection to a database is highly recommended to the future researchers adapting this study.</p> <p>Furthermore, the researchers observed the great amount of time needed to be invested in running the models in the Google Colab due to its heavy load of data available from 2007. Hence, it is recommended to allot ample time for more variations of testing and training to further evaluate the best model/s when running models with different intervals, train-test split, and parameters. In addition, the researchers have initially assessed through previous studies that MSE and MAPE are the two most common accuracy metrics used for time series data. The researchers further suggest to expand the options for accuracy metrics in order to develop more non-biased evaluations on the best models for specified time intervals and have a more detailed comparison between accuracy metrics.</p> <p>To further relate the accuracy of the models, it is also recommended to also focus on adding future predictions of the Brent Crude Oil Prices. These will be a significant information for stakeholders especially with the constant shifts of economy disposition in the country. Lastly, as much as Brent Crude Oil is a relevant commodity to focus on this kind of prediction study with its massive increase in price in the past few months, the researchers also encourage to try the LSTM and ARIMA models to other valuable stocks and assets available in the industry. The researchers have discovered the importance of Philippine economy-related studies most especially to investors, economics professionals, and policymakers in taking a course of action towards economic progression.</p>', unsafe_allow_html=True)
91
+
92
+
93
+ # # sample text
94
+ # st.markdown('Here are some code snippets!')
95
+ # st.markdown('Here are some code snippets that illustrate the saving and evaluation of the ARIMA and LSTM models in Google Colab')
96
+
97
+ # # sample add code snippet
98
+
99
+ # code = '''# evaluate combinations of p, d and q values for an ARIMA model
100
+ # # prepare training dataset
101
+ # train_size = int(len(X) * split)
102
+ # train, test = X[0:train_size], X[train_size:]
103
+ # history = [x for x in train]
104
+ # predset = pd.DataFrame(test)
105
+
106
+ # # make predictions
107
+ # predictions = list()
108
+ # for t in range(len(test)):
109
+ # model = ARIMA(history, order=arima_order)
110
+ # model_fit = model.fit()
111
+ # yhat = model_fit.forecast()[0]
112
+ # predictions.append(*yhat)
113
+ # history.append(test[t])'''
114
+ # st.code(code, language='python')
115
+ # code = '''p_values = range(0, 3)
116
+ # d_values = range(0, 3)
117
+ # q_values = range(0, 2)
118
+ # split_values = [0.8, 0.5, 0.6]
119
+ # warnings.filterwarnings("ignore")
120
+ # df1 = evaluate_models(df.Close, p_values, d_values, q_values,split_values)'''
121
+ # st.code(code, language='python')
122
+ # # LSTM
123
+ # code = '''# LSTM Model
124
+ # # preprocessing
125
+ # date_train, date_val, date_test = df.index[:int(df.shape[0]*split)],df.index[int(df.shape[0]*split):int(df.shape[0]*val_split)], df.index[int(df.shape[0]*val_split)+WINDOW_SIZE:]
126
+ # X_train1, y_train1 = X1[:int(df.shape[0]*split)], y1[:int(df.shape[0]*split)]
127
+ # X_val, y_val = X1[int(df.shape[0]*split):int(df.shape[0]*val_split)], y1[int(df.shape[0]*split):int(df.shape[0]*val_split)]
128
+ # X_test1, y_test1 = X1[int(df.shape[0]*val_split):], y1[int(df.shape[0]*val_split):]
129
+
130
+ # # X_train1.shape, y_train1.shape, X_test1.shape, y_test1.shape
131
+
132
+ # # lstm model
133
+ # model = Sequential([layers.Input((3,1)),layers.LSTM(64),layers.Dense(32, activation='relu'),layers.Dense(32, activation='relu'), layers.Dense(1)])
134
+ # cp1 = ModelCheckpoint('model1/', save_best_only=True)
135
+ # model.compile(loss='mse', optimizer=Adam(learning_rate=0.001), metrics=['mean_absolute_percentage_error'])
136
+ # model.fit(X_train1, y_train1,validation_data=(X_val, y_val), epochs=100, callbacks=[cp1])
137
+ # # model.summary()
138
+ # '''
139
+ # st.code(code, language='python')
140
+
141
+
142
+ # # code = '''def hello():
143
+ # # print("Hello, Streamlit!")'''
144
+ # # st.code(code, language='python')
145
+
146
+ # # sample add latex or formulas
147
+ # st.latex(r'''
148
+ # a + ar + a r^2 + a r^3 + \cdots + a r^{n-1} =
149
+ # \sum_{k=0}^{n-1} ar^k =
150
+ # a \left(\frac{1-r^{n}}{1-r}\right)
151
+ # ''')
152
+
153
+ # c. about us creators
154
+ st.header('About the Authors')
155
+ st.markdown('The authors, Janna Rizza Wong, Stephanie Lorraine Ignas, and Alyanna Angela Castillon, are all university seniors taking Bachelor of Science in Computer Science in Ateneo de Davao University, Philippines.')
pages/2_πŸ“ˆ_Explore.py ADDED
@@ -0,0 +1,78 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # TODO: add descriptions on how to use
2
+
3
+ import streamlit as st
4
+ import pandas as pd
5
+ import plotly.graph_objects as go
6
+ import yfinance as yf
7
+ import matplotlib.pyplot as plt
8
+ # import numpy as np
9
+ import plotly.express as px
10
+ from st_aggrid import GridOptionsBuilder, AgGrid
11
+ hide_menu_style = """
12
+ <style>
13
+ #MainMenu{visibility: hidden;}
14
+ footer{visibility:hidden;}
15
+ </style>
16
+ """
17
+ # page expands to full width
18
+ st.set_page_config(page_title="Predicta.oil | Explore", layout='wide', page_icon="β›½")
19
+ st.markdown(hide_menu_style, unsafe_allow_html=True)
20
+ st.title("Explore Models")
21
+
22
+ # ARIMA
23
+ # slider interval
24
+ interv = st.select_slider('Select Time Series Data Interval for Prediction', options=[
25
+ 'Weekly', 'Monthly', 'Quarterly', 'Daily'], value='Weekly')
26
+
27
+ # dropdown 50 60 80
28
+ st.write("Select Split")
29
+ intervals = st.selectbox(
30
+ "Select Interval:", ('80', '60', '50'))
31
+
32
+ # read file from select interval and dropdown split
33
+
34
+
35
+ def get_location(interv, intervals):
36
+ # location = 'Explore/ARIMA/' + interv + '/' + intervals + '.csv'
37
+ location = 'Explore/PREDICTIONS/' + interv + '/' + intervals + '.csv'
38
+ return location
39
+
40
+
41
+ location = get_location(interv, intervals)
42
+
43
+ # pagination function for aggrid
44
+
45
+
46
+ def pagination(df):
47
+ gb = GridOptionsBuilder.from_dataframe(df)
48
+ gb.configure_pagination(paginationAutoPageSize=True)
49
+ return gb.build()
50
+
51
+
52
+ # read file
53
+ file = pd.read_csv(get_location(interv, intervals))
54
+ page = pagination(file)
55
+ file.drop("Unnamed: 0", axis=1, inplace=True)
56
+
57
+ # select columns
58
+ columns = file.columns.to_list()
59
+ # st.write(columns)
60
+ selectedCols = st.multiselect("Select models", columns, default=[
61
+ "Date", "Close Prices"])
62
+ df = file[selectedCols]
63
+ st.dataframe(df)
64
+
65
+ # print(df.columns.values)
66
+
67
+
68
+ fig = go.Figure()
69
+ for idx, col in enumerate(df.columns, 0):
70
+ # print(df.iloc[1:,idx])
71
+ if col != 'Date':
72
+ fig.add_trace(go.Scatter(
73
+ x=file['Date'], y=df.iloc[1:, idx], mode='lines', name=col))
74
+
75
+
76
+ st.plotly_chart(fig, use_container_width=True)
77
+
78
+ # LSTM
pages/3_πŸ“Š_Make_a_Model.py ADDED
@@ -0,0 +1,249 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from statsmodels.tsa.arima_model import ARIMAResults
2
+ import streamlit as st
3
+ import pandas as pd
4
+ import yfinance as yf
5
+ import matplotlib.pyplot as plt
6
+ import numpy as np
7
+ import plotly.express as px
8
+ import time
9
+ from statsmodels.tsa.arima_model import ARIMA
10
+ from sklearn.metrics import mean_absolute_percentage_error, mean_squared_error, mean_absolute_error
11
+ import tensorflow as tf
12
+ from tensorflow import keras
13
+ from keras.models import Sequential
14
+ from keras.layers import Dense, LSTM
15
+ from keras import layers
16
+ from keras import wrappers
17
+ from tensorflow.keras.optimizers import Adam
18
+ from tensorflow.keras.callbacks import ModelCheckpoint
19
+ from st_aggrid import GridOptionsBuilder, AgGrid
20
+
21
+ hide_menu_style = """
22
+ <style>
23
+ #MainMenu{visibility: hidden;}
24
+ footer{visibility:hidden;}
25
+ </style>
26
+ """
27
+ # page expands to full width
28
+ st.set_page_config(page_title="Predicta.oil | Make a Model", layout='wide', page_icon="β›½")
29
+ st.markdown(hide_menu_style, unsafe_allow_html=True)
30
+ # ag grid pagination
31
+
32
+
33
+ def pagination(df):
34
+ gb = GridOptionsBuilder.from_dataframe(df)
35
+ gb.configure_pagination(paginationAutoPageSize=True)
36
+ return gb.build()
37
+
38
+
39
+ # PAGE LAYOUT
40
+ # heading
41
+ st.title("Make a Model")
42
+
43
+ # ARIMA PARAMETERS
44
+ pValue = 4
45
+ dValue = 1
46
+ qValue = 0
47
+
48
+ # show raw data
49
+ st.header("Raw Data")
50
+ # sidebar
51
+ # Sidebar - Specify parameter settings
52
+ with st.sidebar.header('Set Data Split'):
53
+ # PARAMETERS min,max,default,skip
54
+ trainData = st.sidebar.slider(
55
+ 'Data split ratio (% for Training Set)', 10, 90, 80, 5)
56
+ # ARIMA PARAMETERS
57
+ pValue = st.sidebar.number_input('P-value:', 0, 100, pValue)
58
+ st.sidebar.write('The current p-Value is ', pValue)
59
+ dValue = st.sidebar.number_input('D-value:', 0, 100, dValue)
60
+ st.sidebar.write('The current d-Value is ', dValue)
61
+ qValue = st.sidebar.number_input('Q-value:', 0, 100, qValue)
62
+ st.sidebar.write('The current q-Value is ', qValue)
63
+ details = st.sidebar.checkbox('Show Details')
64
+ runModels = st.sidebar.button('Test Models')
65
+
66
+
67
+ # select time interval
68
+ interv = st.select_slider('Select Time Series Data Interval for Prediction', options=[
69
+ 'Weekly', 'Monthly', 'Quarterly', 'Daily'])
70
+
71
+
72
+ @st.cache
73
+ def getInterval(argument):
74
+ switcher = {
75
+ "W": "1wk",
76
+ "M": "1mo",
77
+ "Q": "3mo",
78
+ "D": "1d"
79
+ }
80
+ return switcher.get(argument, "1d")
81
+
82
+
83
+ df = yf.download('BZ=F', interval=getInterval(interv[0]))
84
+ st.table(df.head())
85
+ # download full data
86
+
87
+
88
+ @st.cache
89
+ def convert_df(df):
90
+ # IMPORTANT: Cache the conversion to prevent computation on every rerun
91
+ return df.to_csv().encode('utf-8')
92
+
93
+
94
+ csv = convert_df(df)
95
+ # download full data
96
+ st.download_button(
97
+ label="Download data as CSV",
98
+ data=csv,
99
+ file_name='Brent Oil Prices.csv',
100
+ mime='text/csv',
101
+ )
102
+
103
+
104
+
105
+ # graph visualization
106
+ st.header("Visualizations")
107
+
108
+ # LSTM
109
+
110
+
111
+ def df_to_X_y(df, window_size=5):
112
+ df_as_np = df.to_numpy()
113
+ X = []
114
+ y = []
115
+ for i in range(len(df_as_np)-window_size):
116
+ row = [[a] for a in df_as_np[i:i+window_size]]
117
+ X.append(row)
118
+ label = df_as_np[i+window_size]
119
+ y.append(label)
120
+ return np.array(X), np.array(y)
121
+
122
+
123
+ def mse_eval(test, predictions):
124
+ return mean_squared_error(test, predictions)
125
+
126
+
127
+ def mape_eval(test, predictions):
128
+ return mean_absolute_percentage_error(test, predictions)
129
+
130
+ def evaluate_lstm_model(split):
131
+ global lstmModel
132
+ WINDOW_SIZE = 3
133
+ X1, y1 = df_to_X_y(df['Close'], WINDOW_SIZE)
134
+
135
+ # preprocessing
136
+ date_train, date_test = df.index[:int(
137
+ df.shape[0]*split)], df.index[int(df.shape[0]*split)+WINDOW_SIZE:]
138
+ X_train1, y_train1 = X1[:int(df.shape[0]*split)
139
+ ], y1[:int(df.shape[0]*split)]
140
+ X_test1, y_test1 = X1[int(df.shape[0]*split)
141
+ :], y1[int(df.shape[0]*split):]
142
+
143
+ # lstm model
144
+ with st.spinner('LSTM Model...'):
145
+ model = Sequential([layers.Input((3, 1)), layers.LSTM(64), layers.Dense(
146
+ 32, activation='relu'), layers.Dense(32, activation='relu'), layers.Dense(1)])
147
+ cp1 = ModelCheckpoint('model1/', save_best_only=True)
148
+ model.compile(loss='mse', optimizer=Adam(learning_rate=0.001),
149
+ metrics=['mean_absolute_percentage_error'])
150
+ model.fit(X_train1, y_train1, epochs=100)
151
+
152
+ lstmModel = model.summary()
153
+ # train predictions
154
+ train_predictions = model.predict(X_train1).flatten()
155
+ train_results = pd.DataFrame(
156
+ data={'Date': date_train, 'Close Prices': y_train1, 'Train Predictions': train_predictions})
157
+ # train_results
158
+
159
+ # test predictions
160
+ test_predictions = model.predict(X_test1).flatten()
161
+ test_results = pd.DataFrame(
162
+ data={'Date': date_test, 'Close Prices': y_test1, 'LSTM Predictions': test_predictions})
163
+ # test_results
164
+
165
+ # evaluate model
166
+ mse = mse_eval(test_results['Close Prices'],
167
+ test_results['LSTM Predictions'])
168
+ mape = mape_eval(test_results['Close Prices'],
169
+ test_results['LSTM Predictions'])
170
+ print(mse)
171
+ print(mape)
172
+
173
+ return test_results, mse, mape
174
+ global results
175
+
176
+
177
+ # ARIMA MODEL
178
+ def evaluate_arima_model(df, trainData):
179
+ global arimamodsum
180
+ try:
181
+ with st.spinner('ARIMA Model...'):
182
+ row = int(len(df)*(trainData*.01)) # 80% testing
183
+ trainingData = list(df[0:row]['Close'])
184
+ testingData = list(df[row:]['Close'])
185
+ predictions = []
186
+ nObservations = len(testingData)
187
+
188
+ for i in range(nObservations):
189
+ model = ARIMA(trainingData, order=(
190
+ pValue, dValue, qValue)) # p,d,q
191
+ model_fit = model.fit()
192
+ output = model_fit.forecast()
193
+ yhat = list(output[0])[0]
194
+ predictions.append(yhat)
195
+ actualTestValue = testingData[i]
196
+ trainingData.append(actualTestValue)
197
+
198
+ arimamodsum = model_fit.summary()
199
+
200
+ # st.write(predictions)
201
+ testingSet = pd.DataFrame(testingData)
202
+ testingSet['ARIMApredictions'] = predictions
203
+ testingSet.columns = ['Close Prices', 'ARIMA Predictions']
204
+ results["ARIMA Predictions"] = testingSet["ARIMA Predictions"]
205
+ MSE = mean_squared_error(testingData, predictions)
206
+ MAPE = mean_absolute_percentage_error(testingData, predictions)
207
+
208
+ return MSE, MAPE
209
+ except:
210
+ st.error('Please select other ARIMA values as this is not possible.')
211
+ st.stop()
212
+ return()
213
+
214
+
215
+ # run models
216
+ # plot all results
217
+ if runModels:
218
+ results, lstmMse, lstmMape = evaluate_lstm_model(trainData*.01)
219
+ arimaMSE, arimaMAPE = evaluate_arima_model(df, trainData)
220
+
221
+ # plot orig price and predicted price
222
+ fig = px.line(results, x=results["Date"], y=["Close Prices", "ARIMA Predictions", "LSTM Predictions"],
223
+ title="BOTH PREDICTED BRENT CRUDE OIL PRICES", width=1000)
224
+ st.plotly_chart(fig, use_container_width=True)
225
+
226
+ # print(arimamodsum)
227
+
228
+ # initialize session state
229
+ if 'details_state' not in st.session_state:
230
+ st.session_state.details_state = False
231
+ # st.write(details)
232
+ if details or st.session_state.details_state:
233
+ st.session_state.details_state = True
234
+ page = pagination(results)
235
+ AgGrid(results, key='dailyCombined', fit_columns_on_grid_load=True,
236
+ enable_enterprise_modules=True, theme='streamlit', gridOptions=page)
237
+ st.write(arimamodsum)
238
+
239
+ # ACCURACY METRICS
240
+ accTable = pd.DataFrame()
241
+ accTable['ARIMA-MAPE'] = [arimaMAPE]
242
+ accTable['LSTM-MAPE'] = [lstmMape]
243
+ accTable['ARIMA-MSE'] = [arimaMSE]
244
+ accTable['LSTM-MSE'] = [lstmMse]
245
+
246
+ # accuracy metrics
247
+ st.header("Accuracy Metrics")
248
+
249
+ st.table(accTable)
requirements.txt ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ streamlit==1.11.0
2
+ pandas==1.3.5
3
+ base58==2.0.1
4
+ numpy==1.23
5
+ Pillow>=9.0.1
6
+ plotly==5.6.0
7
+ scikit-learn==0.24
8
+ click==8.0.4
9
+ yfinance==0.1.70
10
+ matplotlib==3.5.1
11
+ cufflinks==0.17.3
12
+ statsmodels==0.10.2
13
+ cython==0.29.30
14
+ scipy==1.8.1
15
+ patsy==0.5.2
16
+ cvxopt==1.2.7
17
+ joblib==1.1.0
18
+ tensorflow==2.8.2
19
+ streamlit-aggrid == 0.2.3
20
+
🏠_Home.py ADDED
@@ -0,0 +1,231 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import streamlit as st
2
+ import pandas as pd
3
+ import yfinance as yf
4
+ import matplotlib.pyplot as plt
5
+ # import numpy as np
6
+ import plotly.express as px
7
+ from st_aggrid import GridOptionsBuilder, AgGrid
8
+ import plotly.graph_objects as go
9
+
10
+ hide_menu_style = """
11
+ <style>
12
+ #MainMenu{visibility: hidden;}
13
+ footer{visibility:hidden;}
14
+ </style>
15
+ """
16
+
17
+ # page expands to full width
18
+ st.set_page_config(page_title="Predicta.oil | Home", layout='wide', page_icon="β›½")
19
+ st.markdown(hide_menu_style, unsafe_allow_html=True)
20
+ # PAGE LAYOUT
21
+ # heading
22
+ st.title("Crude Oil Benchmark Stock Price Prediction LSTM and ARIMA Models")
23
+ st.subheader("""Β© Castillon, Ignas, Wong""")
24
+
25
+ st.header("Raw Data")
26
+
27
+ # select time interval
28
+ interv = st.select_slider('Select Time Series Data Interval for Prediction', options=[
29
+ 'Weekly', 'Monthly', 'Quarterly', 'Daily'])
30
+
31
+ # st.write(interv[0])
32
+
33
+ # Function to convert time series to interval
34
+
35
+
36
+ @st.cache(persist=True, allow_output_mutation=True)
37
+ def getInterval(argument):
38
+ switcher = {
39
+ "W": "1wk",
40
+ "M": "1mo",
41
+ "Q": "3mo",
42
+ "D": "1d"
43
+ }
44
+ return switcher.get(argument, "1wk")
45
+
46
+
47
+ # show raw data
48
+ # st.header("Raw Data")
49
+ # using button
50
+ # if st.button('Press to see Brent Crude Oil Raw Data'):
51
+
52
+
53
+ df = yf.download('BZ=F', interval=getInterval(interv[0]))
54
+
55
+ # st.dataframe(df.head())
56
+ df = df.reset_index()
57
+
58
+
59
+ def pagination(df):
60
+ gb = GridOptionsBuilder.from_dataframe(df)
61
+ gb.configure_pagination(paginationAutoPageSize=True)
62
+ return gb.build()
63
+
64
+
65
+ # enable enterprise modules for trial only
66
+ # raw data
67
+ page = pagination(df)
68
+ # AgGrid(df, enable_enterprise_modules=True,
69
+ # theme='streamlit', gridOptions=page, fit_columns_on_grid_load=True, key='data')
70
+ # st.dataframe(df, width=2000, height=600)
71
+ # st.write(df)
72
+ st.table(df.head())
73
+ # download full data
74
+
75
+
76
+ @st.cache
77
+ def convert_df(df):
78
+ # IMPORTANT: Cache the conversion to prevent computation on every rerun
79
+ return df.to_csv().encode('utf-8')
80
+
81
+
82
+ csv = convert_df(df)
83
+
84
+ st.download_button(
85
+ label="Download data as CSV",
86
+ data=csv,
87
+ file_name='Brent Oil Prices.csv',
88
+ mime='text/csv',
89
+ )
90
+
91
+
92
+ st.header("Standard Deviation")
93
+ sd = pd.read_csv('StandardDeviation.csv')
94
+ sd.drop("Unnamed: 0", axis=1, inplace=True)
95
+ sd = sd.reset_index()
96
+
97
+ AgGrid(sd, key='SD1', enable_enterprise_modules=True,
98
+ fit_columns_on_grid_load=True, theme='streamlit')
99
+
100
+ sd = sd.pivot(index='Start Date', columns='Interval',
101
+ values='Standard Deviation')
102
+ sd = sd.reset_index()
103
+ # table
104
+ # AgGrid(sd, key='SD', enable_enterprise_modules=True,
105
+ # fit_columns_on_grid_load=True, domLayout='autoHeight', theme='streamlit')
106
+
107
+ # visualization
108
+ fig = px.line(sd, x=sd.index, y=['1d', '1wk', '1mo', '3mo'],
109
+ title="STANDARD DEVIATION OF BRENT CRUDE OIL PRICES", width=1000)
110
+ st.plotly_chart(fig, use_container_width=True)
111
+
112
+
113
+ # accuracy metrics
114
+ st.header("Accuracy Metric Comparison")
115
+ intervals = st.selectbox(
116
+ "Select Interval:", ('Weekly', 'Monthly', 'Quarterly', 'Daily'), key='metricKey')
117
+ with st.container():
118
+ col1, col2 = st.columns(2)
119
+
120
+ # LSTM METRICS
121
+ # st.write("LSTM Metrics")
122
+
123
+
124
+ readfile = pd.read_csv('LSTM.csv')
125
+ # readfile = readfile[readfile['Interval'] == intervals.upper()]
126
+ readfile = readfile[readfile['Interval']== st.session_state.metricKey.upper()]
127
+ # readfile[readfile['Interval'] == intervals.upper()]
128
+ # readfile = updatefile(readfile)
129
+ readfile.drop("Unnamed: 0", axis=1, inplace=True)
130
+ with col1:
131
+ st.write("LSTM Metrics")
132
+ AgGrid(readfile, key=st.session_state.metricKey, fit_columns_on_grid_load=True,
133
+ enable_enterprise_modules=True, theme='streamlit')
134
+
135
+
136
+ # st.write(st.session_state.metricKey)
137
+
138
+ # ARIMA METRICS
139
+ # st.write("ARIMA Metrics")
140
+ # intervals = st.selectbox(
141
+ # "Select Interval:", ('Weekly', 'Monthly', 'Quarterly', 'Daily'))
142
+
143
+ if intervals == 'Weekly':
144
+ file = pd.read_csv('ARIMAMetrics/ARIMA-WEEKLY.csv')
145
+ file.drop("Unnamed: 0", axis=1, inplace=True)
146
+ page = pagination(file)
147
+ with col2:
148
+ st.write("ARIMA Metrics")
149
+ AgGrid(file, width='100%', theme='streamlit', enable_enterprise_modules=True,
150
+ fit_columns_on_grid_load=True, key='weeklyMetric', gridOptions=page)
151
+
152
+ elif intervals == 'Monthly':
153
+ file = pd.read_csv('ARIMAMetrics/ARIMA-MONTHLY.csv')
154
+ file.drop("Unnamed: 0", axis=1, inplace=True)
155
+ page = pagination(file)
156
+ with col2:
157
+ st.write("ARIMA Metrics")
158
+ AgGrid(file, key='monthlyMetric', fit_columns_on_grid_load=True,
159
+ enable_enterprise_modules=True, theme='streamlit', gridOptions=page)
160
+
161
+ elif intervals == 'Quarterly':
162
+ file = pd.read_csv('ARIMAMetrics/ARIMA-QUARTERLY.csv')
163
+ file.drop("Unnamed: 0", axis=1, inplace=True)
164
+ page = pagination(file)
165
+ with col2:
166
+ st.write("ARIMA Metrics")
167
+ AgGrid(file, key='quarterlyMetric', fit_columns_on_grid_load=True,
168
+ enable_enterprise_modules=True, theme='streamlit', gridOptions=page)
169
+
170
+ elif intervals == 'Daily':
171
+ file = pd.read_csv('ARIMAMetrics/ARIMA-DAILY.csv')
172
+ file.drop("Unnamed: 0", axis=1, inplace=True)
173
+ page = pagination(file)
174
+ with col2:
175
+ st.write("ARIMA Metrics")
176
+ AgGrid(file, key='dailyMetric', width='100%', fit_columns_on_grid_load=True,
177
+ enable_enterprise_modules=True, theme='streamlit', gridOptions=page)
178
+
179
+ # MODEL OUTPUT TABLE
180
+ st.header("Model Output (Close Prices vs. Predicted Prices)")
181
+
182
+ interval = st.selectbox("Select Interval:", ('Weekly',
183
+ 'Monthly', 'Quarterly', 'Daily'), key='bestmodels')
184
+
185
+ if interval == 'Weekly':
186
+ file = pd.read_csv('bestWeekly.csv')
187
+ page = pagination(file)
188
+ AgGrid(file, key='weeklycombined', fit_columns_on_grid_load=True,
189
+ enable_enterprise_modules=True, theme='streamlit', gridOptions=page)
190
+
191
+ # Visualization
192
+ st.header("Visualization")
193
+ fig = px.line(file, x=file["Date"], y=["Close Prices", "ARIMA_50.0_(1, 0, 0)_Predictions",
194
+ "LSTM_80.0_Predictions"], title="BOTH PREDICTED BRENT CRUDE OIL PRICES", width=1000)
195
+ st.plotly_chart(fig, use_container_width=True)
196
+
197
+
198
+ elif interval == 'Monthly':
199
+ file = pd.read_csv('bestMonthly.csv')
200
+ page = pagination(file)
201
+ AgGrid(file, key='monthlyCombined', fit_columns_on_grid_load=True,
202
+ enable_enterprise_modules=True, theme='streamlit', gridOptions=page)
203
+ # Visualization
204
+ st.header("Visualization")
205
+ fig = px.line(file, x=file["Date"], y=["Close Prices", "ARIMA_60.0_(0, 1, 1)_Predictions", # find file
206
+ "LSTM_80.0_Predictions"], title="BOTH PREDICTED BRENT CRUDE OIL PRICES", width=1000)
207
+ st.plotly_chart(fig, use_container_width=True)
208
+
209
+
210
+ elif interval == 'Quarterly':
211
+ file = pd.read_csv('bestQuarterly.csv')
212
+ page = pagination(file)
213
+ AgGrid(file, key='quarterlyCombined', fit_columns_on_grid_load=True,
214
+ enable_enterprise_modules=True, theme='streamlit', gridOptions=page)
215
+ # Visualization
216
+ st.header("Visualization")
217
+ fig = px.line(file, x=file["Date"], y=["Close Prices", "ARIMA_50.0_(0, 1, 0)_Predictions", # find file
218
+ "LSTM_80.0_Predictions"], title="BOTH PREDICTED BRENT CRUDE OIL PRICES", width=1000)
219
+ st.plotly_chart(fig, use_container_width=True)
220
+
221
+
222
+ elif interval == 'Daily':
223
+ file = pd.read_csv('bestDaily.csv')
224
+
225
+ AgGrid(file, key='dailyCombined', fit_columns_on_grid_load=True,
226
+ enable_enterprise_modules=True, theme='streamlit', gridOptions=page)
227
+ # Visualization
228
+ st.header("Visualization")
229
+ fig = px.line(file, x=file["Date"], y=["Close Prices", "ARIMA_50.0_(0, 1, 0)_Predictions", # find file
230
+ "LSTM_60.0_Predictions"], title="BOTH PREDICTED BRENT CRUDE OIL PRICES", width=1000)
231
+ st.plotly_chart(fig, use_container_width=True)