Newsgroup: it.economia.borsa.trading-online
Titolo: scusate...ultima domanda..linear regression indicator

Non riesco a capire la differenza (in metastock) tra la linear regression
indicator e la linear regression slope. Potete aiutarmi?
Grazie
--------------------------------
Inviato via 
http://arianna.libero.it/usenet/


it.economia.analisi-tecn

ciao
Linear regression Indicator:
The Linear Regression indicator is based on the trend of a security's price
over a specified time period.  The trend is determined by calculating a
linear regression trendline using the "least squares fit" method.  The least
squares fit technique fits a trendline to the data in the chart by
minimizing the distance between the data points and the linear regression
trendline.
Any point along the Linear Regression indicator is equal to the ending value
of a Linear Regression trendline.  For example, the ending value of a Linear
Regression trendline that covers 10 days will have the same value as a
10-day Linear Regression indicator.  This differs slightly from the Time
Series Forecast indicator (see Time Series Forecast) in that the TSF adds
the slope to the ending value of the regression line.  This makes the TSF a
bit more responsive to short term price changes.  If you plot the TSF and
the Linear Regression indicator side-by-side, you'll notice that the TSF
hugs the prices more closely than the Linear Regression indicator.
Rather than plotting a straight Linear Regression trendline, the Linear
Regression indicator plots the ending values of multiple Linear Regression
trendlines.
See Plotting an Indicator for more information on plotting indicators.  See
Linear Regression Indicator for more information on the Linear Regression
indicator parameters.
The interpretation of a Linear Regression indicator is similar to a moving
average.  However, the Linear Regression indicator has two advantages over
moving averages.
Unlike a moving average, a Linear Regression indicator does not exhibit as
much "delay."  Since the indicator is "fitting" a line to the data points
rather than averaging them, the Linear Regression line is more responsive to
price changes.
The indicator is actually a forecast of the next periods (tomorrow's) price
plotted today.  The Forecast Oscillator plots the percentage difference
between the forecast price and the actual price.  Tushar Chande suggests
that when prices are persistently above or below the forecast price, prices
can be expected to snap back to more realistic levels.  In other words the
Linear Regression indicator shows where prices should be trading on a
statistical basis.  Any excessive deviation from the regression line should
be short-lived.
Linear Regression Slope:
The Linear Regression method provides several useful outputs for technical
analysts, including the Slope.  The Slope shows how much prices are expected
to change per unit of time.  Some may remember this as "rise over run."
See Plotting an Indicator for more information on plotting indicators.  See
Linear Regression Slope for more information on the Linear Regression Slope
parameters.
It is helpful to consider Slope in relation to r-squared (see r-squared).
While Slope gives you the general direction of the trend (positive or
negative), r-squared gives you the strength of the trend.  A high r-squared
value can be associated with a high positive or negative Slope.
When the Slope of the trend first becomes significantly positive, you could
open a long position.  You could sell, or open a short position when the
Slope first becomes significantly negative.  You should refer to the table
below to determine when a trend is deemed "significant."  For example, if
the 14-period Slope has recently turned from negative to positive (i.e.,
crossed above zero), you may consider buying when r-squared crosses above
the 0.27 level.
To determine if the trend is statistically significant for a given x-period
linear regression line, plot the r-squared indicator and refer to the
following table.  This table shows the values of r-squared required for 95%
confidence level at various time periods.  If the value is less than the
critical values shown, you should assume that prices show no statistically
significant trend.
Number ofPeriods r-squaredCritical Value(95%confidence)
5 0.77
10 0.40
14 0.27
20 0.20
25 0.16
30 0.13
50 0.08
60 0.06
120 0.03
You may even consider opening a short-term position opposite the prevailing
trend when you observe the Slope rounding off at extreme levels.  For
example, if the Slope is at a relatively high level and begins to turn down,
you may consider selling or opening a short position.
There are numerous ways to use the linear regression outputs of Slope and
r-squared in trading systems.  For more detailed coverage, refer to the book
The New Technical Trader by Tushar Chande and Stanley Kroll.

indicator e la linear regression slope. Potete aiutarmi?
Ciao,
solitamente portiamo pazienza sui messaggi che possono riguardare
anche solo marginalmente il trading on line, ma le tue domande sono
prettamente da it.economa.analisi-tech, oltre tutto la precente l'hai
postata sia di qua sia di la', questo comporta anche un disturbo per
chi ti volesse eventualmente rispondere.
Quindi per il futuro cerca di evitare, grazie.
A presto
--
Stefano Orsi
Email: *Attenzione: non sempre rispondo alle email* :-)
http://biv2533.supereva.it

 Probabilmente ho sbagliato qualcosa, se è cosi e ho dato fastidio a
qualcuno, chiedo scusa. Chiedo conferma al moderatore del mio errore.
Scusate ancora.
Ciarletto
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