# Logistic Signal Calibration Logistic Signal Calibration is an indicator on [Vela](https://vela.luxalgo.com/chart), our next-generation charting platform, written in Pine Script®. Logistic Signal Calibration fuses three z-scored features - momentum (14), trend (50) and volume flow (20) - through a logistic model into a 0-to-1 probability-style score with decision thresholds at 0.7 and 0.3. A reliability dashboard grades each score against its 10-bar outcome, tracking hit rate, average confidence, Brier score and overconfidence. - Indicator in the LuxAlgo Library, by LuxAlgo, published Mar 8, 2026. - Access: free. - Concepts: [Logistic Signal Calibration](https://www.luxalgo.com/library/concept/logistic-signal-calibration/) (primary) - Open on Vela: https://vela.luxalgo.com/chart?pineScriptCodeId=zn0u6unrtozbz4k7t9pte0z3 - Page: https://www.luxalgo.com/library/indicator/logistic-signal-calibration/ **Logistic Signal Calibration** implements [logistic signal calibration](https://www.luxalgo.com/library/concept/logistic-signal-calibration/) as a transparent on-chart model: momentum, trend and volume-flow features are standardized to z-scores, weighted by coefficients set directly in the inputs, summed with an intercept into log-odds, and mapped through the sigmoid into a 0-to-1 score. The pane plots the calibrated probability against decision thresholds, and a reliability dashboard grades every score once its horizon resolves. ## How to Trade the Logistic Signal Calibration? - **Score above the Bullish threshold**: the long filter passes - marginal readings near 0.5 are skipped by construction. - **Score below the Bearish threshold**: the short mirror; between the two is the no-edge, stand-aside band. - **Overconfidence highlights**: bins where claimed probability exceeds observed frequency beyond one standard error turn orange. - **Brier score above 0.25**: worse than a constant always-0.5 forecast; a calibration-decay alert fires on the cross. Per-feature contributions stream to the data window, keeping every reading decomposable. ## Logistic Signal Calibration Settings - **Source** (default close). - **Momentum** (default 14), **Trend** (default 50), **Volume** (default 20): the feature lookbacks, each paired with its logistic coefficient (default 1; 0 removes a feature, negative flips it). - **Intercept (Bias)** (default 0): baseline log-odds - 0 rests the score at 0.5. - **Normalization Window** (default 100): trailing z-score window for the features. - **Bullish** (default 0.7) / **Bearish** (default 0.3): decision thresholds. - **Prediction Horizon** (default 10): bars until each score resolves. - **Evaluation Window** (default 200): resolved scores in the rolling calibration sample. - **Show Calibration Dashboard** (default on); style toggles cover gradient fill, cross markers and line width. ## Frequently Asked Questions ### Are the scores real win probabilities? Treat them as ranked confidence: calibration is measured on past data and erodes as conditions drift. The hit-rate-versus-confidence row and the Brier baseline continuously test whether the numbers still mean what they claim. ### How does this differ from a Bayesian classifier? [Bayesian Classifiers](https://www.luxalgo.com/library/indicator/bayesian-classifiers/) multiply per-feature likelihoods and grow overconfident when features overlap; the logistic form combines features additively in log-odds and stays auditable input by input. ### Why are the weights manual rather than fitted? Transparency: fitted coefficients come from regression on labeled history and change with every refit. Setting them directly keeps cause and effect visible - and the dashboard still reports honestly how the chosen weights perform. ## Related indicators - [Recursive Least Squares Forecast](https://www.luxalgo.com/library/indicator/recursive-least-squares-forecast/) (Online/incremental Learning): markdown at https://www.luxalgo.com/library/indicator/recursive-least-squares-forecast.md - [SuperTrend AI (Clustering)](https://www.luxalgo.com/library/indicator/supertrend-ai-clustering/) (Machine Learning): markdown at https://www.luxalgo.com/library/indicator/supertrend-ai-clustering.md - [KNN Supertrend Horizon](https://www.luxalgo.com/library/indicator/knn-supertrend-horizon/) (Machine Learning): markdown at https://www.luxalgo.com/library/indicator/knn-supertrend-horizon.md - [Nadaraya-Watson Envelope](https://www.luxalgo.com/library/indicator/nadaraya-watson-envelope/) (Machine Learning): markdown at https://www.luxalgo.com/library/indicator/nadaraya-watson-envelope.md - [kNN Market Architecture](https://www.luxalgo.com/library/indicator/knn-market-architecture/) (Machine Learning): markdown at https://www.luxalgo.com/library/indicator/knn-market-architecture.md - [Dynamic Time Warping Similarity](https://www.luxalgo.com/library/indicator/dynamic-time-warping-similarity/) (Machine Learning): markdown at https://www.luxalgo.com/library/indicator/dynamic-time-warping-similarity.md - [Machine Learning Moving Average](https://www.luxalgo.com/library/indicator/machine-learning-moving-average/) (Machine Learning): markdown at https://www.luxalgo.com/library/indicator/machine-learning-moving-average.md - [Nadaraya-Watson Smoothers](https://www.luxalgo.com/library/indicator/nadaraya-watson-smoothers/) (Machine Learning): markdown at https://www.luxalgo.com/library/indicator/nadaraya-watson-smoothers.md --- Source: https://www.luxalgo.com/library/indicator/logistic-signal-calibration/ (LuxAlgo Library). Free to use with attribution: https://www.luxalgo.com/library/license/