Kalman Filter Forecasting

  • Utilities
  • Christian Stern
    Christian Stern
    As CEO of a Switzerland-based specialist company, I combine many years of experience in banking with deep expertise in developing high-quality MQL5 solutions. Our focus is on programming statistical tools for financial analysis and time-series evaluation that unite methodological precision with
  • Version: 2.10
  • Updated: 14 June 2026

Kalman Forecast Helper is an advanced MQL5 Expert Advisor component designed to generate adaptive market forecasts, trend predictions, and trading signals for FX and other financial time series.

Powered by a proprietary Kalman filtering engine, the helper continuously analyzes incoming market data and delivers actionable forecast information that can be integrated directly into Expert Advisors, indicators, or quantitative trading systems.

After each update, the helper provides:

  • Multi-horizon forecasts (1 to 3 bars ahead)

  • Trend direction predictions

  • Confidence bands

  • Trading signals {-1, 0, +1}

  • Forecast quality ratings (A–F)

  • Internal model quality ratings (A–F)

Key Features

  • Adaptive forecasting for changing market conditions

  • Designed specifically for noisy and highly dynamic financial time series

  • Automatic confidence assessment for every forecast

  • Volatility-aware signal generation

  • Built-in trend detection and direction analysis

  • Multi-timeframe support

  • Self-monitoring model health and forecast reliability

  • Robust handling of outliers and market anomalies

Reliability & Stability

The helper incorporates multiple layers of numerical and statistical protection to maintain stable operation during periods of elevated volatility and rapidly changing market conditions.

Features include:

  • Adaptive noise estimation

  • Outlier detection and filtering

  • Automatic model recovery mechanisms

  • Forecast consistency monitoring

  • Dynamic confidence adjustment

  • Advanced numerical stability safeguards

Typical Applications

  • Expert Advisors

  • Algorithmic trading systems

  • Signal generation

  • Trend-following strategies

  • Market regime detection

  • Quantitative research

The forecasting engine used by this helper is based on the proprietary CKalmanFilter technology. Developers interested in licensing the standalone CKalmanFilter library for custom projects may request separate licensing information.


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CRingBuffer
Christian Stern
CRingBuffer - Numeric ring buffer with lightweight high-performance statistics engine CRingBuffer is a powerful MQL5 library for numeric rolling-window analysis. After each insertion it immediately provides mean, variance, standard deviation, percentiles, z-scores, min/max tracking and normalized values - all in O(1) to O(n log n). Table of contents: Application area Two operating modes Basic statistics Welford statistics (numerically stable, recommended for large price levels) Percentiles Z-s
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This pivot scanner implements five industry-standard pivot methodologies: Classic Pivot (HLC/3) Fibonacci Pivot (0.382 / 0.618 / 1.000 levels) Camarilla Pivot Woodie Pivot DeMark Pivot The scanner can operate with a fixed user-selected method or in adaptive mode, where the most suitable pivot model is selected automatically based on observed market behavior and historical performance. Designed as a fully configurable analysis and observation tool, the EA performs historical warmup, executes scan
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