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Least Squares Regression Line

by QuantShare, 2490 days ago
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The least squares regression line is a line in the form of "y = a + b * x" that best fits a data set (time series).

The least squares regression is the most used modeling technique. It is mainly used to predict the future value of the analyzed time series.

Example:
a = RegLineLeastSquares(close,20);

The above instruction calculates, for each trading bar, the least squares regression line of the close series based on the previous 20 bars.

Note that this function allows you to use dynamic lookback period.

b = barssince(cross(close, sma(30)));
a = RegLineLeastSquares(close, b);

Calculates the least squares regression line using data starting from bar where the close price crossed above its 30-bar simple moving average.


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Type: Trading Indicator

Object ID: 1207


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Trading financial instruments, including foreign exchange on margin, carries a high level of risk and is not suitable for all investors. The high degree of leverage can work against you as well as for you. Before deciding to invest in financial instruments or foreign exchange you should carefully consider your investment objectives, level of experience, and risk appetite. The possibility exists that you could sustain a loss of some or all of your initial investment and therefore you should not invest money that you cannot afford to lose. You should be aware of all the risks associated with trading and seek advice from an independent financial advisor if you have any doubts.