Forecasting Quadratic Regression [UPDATED V6] Forecasting Quadratic Regression applies a second-degree polynomial regression model to price data, offering a non-linear alternative to traditional linear regression. By fitting a quadratic curve of the form:
y=a+bx+cx2
the indicator captures both directional trend and curvature, allowing traders to detect momentum shifts earlier than with straight-line models.
🔹 Core Features
Fits a quadratic regression curve to user-defined lookback periods
Extends the fitted curve forward to generate forecast projections
Calculates slope curvature to highlight trend acceleration or deceleration
Adapts dynamically as new bars are added
🔹 Trading Applications
Identify potential reversal zones when the curve inflects (2nd derivative sign change)
Forecast near-term mean reversion targets or extended trend continuations
Filter trades by measuring momentum curvature rather than linear slope
Visualize higher-order structure in price beyond standard regression lines
⚠️ Note: This model is statistical and assumes past curvature informs short-term future price paths. It should be combined with confirmation signals (volume, oscillators, support/resistance) to reduce false inflection points.
