Linear Regression

For swing trading, 50 periods is a good starting point. Shorter periods (20-30) are more responsive but noisier; longer periods (75-100) are smoother but slower. Test what works best for your instrument and trading style.

A moving average simply averages prices over a period. Linear regression finds the best-fit straight line through prices, which can show trend direction and project forward. Regression also provides R-squared to measure trend reliability.

Price above the regression line means the current price is higher than the statistical 'fair value.' This could indicate bullish momentum or potential overextension. How far above (measured in standard deviations) indicates degree of overextension.

Yes, but use shorter periods (10-20 bars) on intraday charts. The principles are the same: slope direction for trend, channels for overextension. Be aware that shorter periods are noisier and require faster decision-making.

A regression channel adds bands above and below the regression line, typically at ±2 standard deviations. About 95% of prices stay within these bands. Touching the upper band suggests overbought; touching lower suggests oversold.

Wait for price to reach a channel boundary (e.g., lower channel at -2 StdDev) while the slope still supports your direction (positive for longs). Enter expecting price to revert toward the regression line. Exit at or near the regression line.

Use mean reversion when R² is high (>0.8) and price is at channel extremes - price reliably follows the regression, so reversion is probable. Use trend following when slope is strong and consistent - enter in trend direction on pullbacks.

Require R² above a threshold (typically 0.7) before trading regression signals. High R² means price follows the regression line reliably. Low R² means price moves randomly - regression signals are unreliable.

Slope flattening (slope moving toward zero) indicates the trend is weakening. In an uptrend, declining slope is an early warning. If slope approaches zero, the trend may be ending. Consider tightening stops or taking profits.

Using multiple periods (e.g., 20, 50, 100) shows trend alignment across timeframes. When all are positive, the trend is strong. Divergence (short negative, long positive) warns of potential reversal. It's similar to multiple moving average analysis.

Slope acceleration is the change in slope over time: Current Slope - Previous Slope. Positive acceleration means the trend is strengthening; negative means weakening. This is the 'second derivative' of the regression and provides early warning of trend changes.

Use regression line as reference for ATM strikes. Use channels for spread short strikes (e.g., sell calls at upper channel level). Match strategy to R²: high R² = directional plays; low R² = neutral strategies. Use slope direction for delta bias.

Standard deviation measures price volatility; standard error measures how well prices fit the regression line. Low standard error means high prediction accuracy. Both create bands, but standard error is specifically about regression fit quality.

Test periods from 20-100, channel widths from 1.5-3 StdDev, and R² filters from 0.5-0.8. Look for robust zones where neighboring parameters perform similarly. Walk-forward validate to prevent overfitting.

Regression fails when: (1) Trend changes faster than regression adapts, (2) Market becomes range-bound (low R²), (3) Volatility expands beyond channels, (4) Gap events distort statistics. Use R² filter and monitor slope changes for early warning.