Time series classification for stock market

kwladyka: <p>I am looking a solution for predicting if price will go up / down on stock market.</p>
<p>Is it better to use PyTorch or <a href="https://github.com/timeseriesAI/tsai" class="inline-onebox" rel="noopener nofollow ugc">GitHub - timeseriesAI/tsai: Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai</a> or <a href="https://unit8co.github.io/darts/" class="inline-onebox" rel="noopener nofollow ugc">Time Series Made Easy in Python — darts documentation</a> or other tool? The point is I need it for time series for 100%.</p>
<p>I don’t know any of this tool. I just started to learn, so it is hard to understand which one I should choose. Can you recommend the right tool or explain when use which one?</p>

tom: <p>I think you first need to think about the methodology and only then the tools.<br>
Conventional wisdom is that you cannot predict if prices will go up / down on the stock market other than that in the long run it has kept going up for the stock market as a whole so far.</p>
<p>Best regards</p>
<p>Thomas</p>

kwladyka: <blockquote>
<p>think about the methodology</p>
</blockquote>
<p>Can you precise what information I should add to my question to let you answer which tool I should use?</p>
<p>The assumption is I don’t know what will work if any.</p>
<blockquote>
<p>Conventional wisdom is that you cannot predict if prices will go up / down on the stock market other than that in the long run it has kept going up for the stock market as a whole so far.</p>
</blockquote>
<p>Probably, then I will prove it doesn’t work <img src="https://discuss.pytorch.org/images/emoji/apple/slight_smile.png?v=12" title=":slight_smile:" class="emoji" alt=":slight_smile:" loading="lazy" width="20" height="20"> But maybe there are some situations to detect like panic, correlation with delay between others instruments etc.</p>

kwladyka: <p>I have DataSet like this for each pair of crypto. Of course <code>output</code> can be modified to find the one which will perform well. So for example it can be 4 categories like <code>up</code> / <code>down</code> / <code>very up</code> / <code>very down</code> or number if it will work better.</p>
<div class="md-table">
<table>
<thead>
<tr>
<th></th>
<th>b_open</th>
<th>b_close</th>
<th>b_min</th>
<th>b_max</th>
<th>trades</th>
<th>a_volume</th>
<th>b_volume</th>
<th>taker_buy_a_volume</th>
<th>taker_buy_b_volume</th>
<th>output</th>
</tr>
</thead>
<tbody>
<tr>
<td>open_time</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<td>2019-09-19 10:02:00+00:00</td>
<td>9881.43</td>
<td>9881.43</td>
<td>9881.43</td>
<td>9881.43</td>
<td>1.0</td>
<td>0.001113</td>
<td>1.099803e+01</td>
<td>0.001113</td>
<td>10.998032</td>
<td>up</td>
</tr>
<tr>
<td>2019-09-19 10:03:00+00:00</td>
<td>9881.43</td>
<td>9881.43</td>
<td>9881.43</td>
<td>9881.43</td>
<td>0.0</td>
<td>0.000000</td>
<td>0.000000e+00</td>
<td>0.000000</td>
<td>0.000000</td>
<td>down</td>
</tr>
<tr>
<td>2019-09-19 10:04:00+00:00</td>
<td>9878.36</td>
<td>9878.36</td>
<td>9878.36</td>
<td>9878.36</td>
<td>1.0</td>
<td>0.012940</td>
<td>1.278260e+02</td>
<td>0.012940</td>
<td>127.825978</td>
<td>up</td>
</tr>
<tr>
<td>2019-09-19 10:05:00+00:00</td>
<td>9878.36</td>
<td>9878.36</td>
<td>9878.36</td>
<td>9878.36</td>
<td>0.0</td>
<td>0.000000</td>
<td>0.000000e+00</td>
<td>0.000000</td>
<td>0.000000</td>
<td>up</td>
</tr>
<tr>
<td>2019-09-19 10:06:00+00:00</td>
<td>9878.36</td>
<td>9878.36</td>
<td>9878.36</td>
<td>9878.36</td>
<td>0.0</td>
<td>0.000000</td>
<td>0.000000e+00</td>
<td>0.000000</td>
<td>0.000000</td>
<td>up</td>
</tr>
<tr>
<td>…</td>
<td>…</td>
<td>…</td>
<td>…</td>
<td>…</td>
<td>…</td>
<td>…</td>
<td>…</td>
<td>…</td>
<td>…</td>
<td>…</td>
</tr>
<tr>
<td>2022-08-20 23:54:00+00:00</td>
<td>21163.60</td>
<td>21163.15</td>
<td>21157.75</td>
<td>21165.00</td>
<td>232.0</td>
<td>7.238290</td>
<td>1.531763e+05</td>
<td>3.244370</td>
<td>68659.152854</td>
<td>down</td>
</tr>
<tr>
<td>2022-08-20 23:55:00+00:00</td>
<td>21163.30</td>
<td>21153.18</td>
<td>21148.72</td>
<td>21163.80</td>
<td>376.0</td>
<td>21.761410</td>
<td>4.603385e+05</td>
<td>10.989020</td>
<td>232455.859014</td>
<td>down</td>
</tr>
<tr>
<td>2022-08-20 23:56:00+00:00</td>
<td>21153.00</td>
<td>21152.26</td>
<td>21147.74</td>
<td>21155.00</td>
<td>280.0</td>
<td>17.670890</td>
<td>3.737588e+05</td>
<td>8.656380</td>
<td>183098.366984</td>
<td>down</td>
</tr>
<tr>
<td>2022-08-20 23:57:00+00:00</td>
<td>21152.40</td>
<td>21150.93</td>
<td>21147.74</td>
<td>21155.48</td>
<td>408.0</td>
<td>30.842110</td>
<td>6.523626e+05</td>
<td>14.203100</td>
<td>300419.935757</td>
<td>down</td>
</tr>
<tr>
<td>2022-08-20 23:58:00+00:00</td>
<td>21150.23</td>
<td>21133.44</td>
<td>21131.23</td>
<td>21155.63</td>
<td>586.0</td>
<td>47.517780</td>
<td>1.004668e+06</td>
<td>24.207030</td>
<td>511790.728087</td>
<td>up</td>
</tr>
</tbody>
</table>
</div><p>PS Of course I can and probably I will convert them to represent the change of the values instead of the raw value. The table is representation of from what I am starting.</p>