Information on Using Linear Regression in Stock Trading
Linear regression analysis is used in technical analysis and is more commonly referred to as the "time series forecast indicator." Learn important tips on how to use this indicator for day trading strategies.
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Future Price and Volume Movements
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Technical analysis tries to predict future movements in the market based on a historical trend in price and volume movements. The best way to visualize these movements is by charting the market's movement over time.
Time Series Forecast Indicator
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The time series forecast indicator uses a multilinear regression trend line to provide support and resistance levels for comparing volume and price levels over time.
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Multilinear Regression Lines
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Determine the trend by calculating a linear regression trend-line using the "least squares fit" methodology. This method minimizes the distance between data points and the trend-line established by the linear regression. Rather than using a straight linear regression line, however, it is best to use multiple linear regression trend lines. These multiple possibilities represent a moving average; that is, an average that continues to evolve with the next data point. Moving averages can be over 5 days or 200 days.
Support and Resistance
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A support level is a bottom price the stock appears to be "stuck" at. A resistance level is a top price the stock appears to be "stuck" at. One represents a bottom and one represents the top of a stock's price range.
Trend Lines
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Linear regression lines are used in day trading to know when to buy or short a stock. The trend line can help you to identify support and resistance levels more accurately. Use breakout points for entry points. Breakout points are where a stock "breaks-out" of support or resistance levels. The point where this occurs is called the breakout point. See Resources for an example of a Breakout chart.
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References
Resources
- Photo Credit Image by Flickr.com, courtesy of kevinzhengli
