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.