Charts
Linear regression is a statistical tool usedto help predict future values from past values. It is commonly usedas a quantitative way to determine the underlying trend and whenprices are overextended. A linear regression trendline uses theleast squares method to plot a straight line through prices so asto minimize the distances between the prices and the resulting trendline.This linear regression indicator plots the trendline value for eachdata point.
Configuration Options
- Period: Number of bars to use in the calculations.
- Field: Price or combination of prices to use as the base for average calculations. Possible values include:
- Open
- High
- Low
- Close
- Adjusted Close
- HL/2 \( \left ( \frac{High + Low}{2} \right ) \)
- HLC/3 \( \left ( \frac{High + Low + Close}{3} \right ) \)
- HLCC/4 \( \left ( \frac{High + Low + Close + Close}{4} \right ) \)
- OHLC/4 \( \left ( \frac{Open + High + Low + Close}{4} \right ) \)
- Color Selectors: Colors to use for graph elements.
- Display Axis Label: Whether to display the most recent value on the Y axis.
Formula
The best fit line associated with the n points(x1, y1), (x2, y2), . . . , (xn, yn) has theform y = mx + b
\[slope\;=\;m\;=\;\frac{\sum_{i=1}^{n}(x_{i} - \bar{x})(y_{i} - \bar{y})}{\sum_{i=1}^{n}(x_{i} - \bar{x})^{2}}\]
\[intercept\;=\;b\;=\;\bar{y} - m\bar{x}\]
