Question 1

What is Linear Regression?

Accepted Answer

The Linear Regression indicator fits a least-squares straight line through the last N closing prices and returns the endpoint value of that line. It projects where the trend "should" be based on the statistical best fit, effectively acting as a forward-looking moving average.

Question 2

How it works

Accepted Answer

``` LinReg(N) = a + b × N where b = (N × Sum(i×Close_i) - Sum(i) × Sum(Close_i)) / (N × Sum(i^2) - Sum(i)^2) a = (Sum(Close_i) - b × Sum(i)) / N ``` The indicator outputs the regression value at the current bar (the right edge of the window).

Question 3

Key features

Accepted Answer

- **Predictive element** — unlike MA which averages past data, LinReg extends the best-fit line to the current point. - **Less lag** — tends to lead price during steady trends because the slope projects forward. - **Slope = trend strength** — steep positive slope means strong uptrend, steep negative means strong downtrend.

Question 4

Trend direction

Accepted Answer

- LinReg rising — uptrend. - LinReg falling — downtrend.

Question 5

Price vs. LinReg

Accepted Answer

- Price above LinReg — price is outperforming the statistical trend (bullish momentum). - Price below LinReg — price is underperforming (bearish momentum or reversion expected).

Question 6

Parameters

Accepted Answer

| Parameter | Default | Description | |-----------|---------|-------------| | Period | 14 | Number of bars for the regression calculation |

Question 7

Example conditions

Accepted Answer

| Condition | Meaning | |-----------|---------| | `close > LINEARREG(14)` | Price above regression line — bullish | | `close cross_over LINEARREG(20)` | Price reclaims regression — potential reversal | | `LINEARREG(14) > LINEARREG(50)` | Short-term trend steeper than long-term — momentum building |

Question 8

Interpreting the Slope

Accepted Answer

The slope of the regression line (coefficient `b`) tells you the trend speed: | Slope | Interpretation | |-------|---------------| | Steep positive | Strong uptrend — price gaining fast | | Gentle positive | Moderate uptrend — steady climb | | Near zero | No trend — consolidation or range | | Gentle negative | Moderate downtrend — gradual decline | | Steep negative | Strong downtrend — price falling fast | A change in slope direction often precedes a change in price direction, making LinReg a le

Question 9

Regression Channel Strategy

Accepted Answer

Combine LinReg with standard deviation bands to create a regression channel: - **Upper band** = LinReg + 2 × StdDev(N) — overbought zone - **Lower band** = LinReg - 2 × StdDev(N) — oversold zone - Enter long when price touches lower band and slope is positive - Enter short when price touches upper band and slope is negative This creates a powerful mean-reversion setup that adapts to the current trend direction.

Question 10

Tips

Accepted Answer

- LinReg works well for mean-reversion strategies — if price deviates far from LinReg, expect a pullback. - Combine with standard deviation bands around LinReg for a regression channel. - Short periods (5-14) are popular for intraday; longer (20-50) for swing. - LinReg is especially useful on assets with steady trends (indices, blue-chip stocks).