Analyzing trading signals on a 15-minute chart involves integrating multiple indicators for precision. The MACD serves to give an early direction indication. A primary signal depends on the Parabolic SAR, signaling buy or sell moments. A buy signal emerges if the third candle ago was below the SMA, with a subsequent candle closing above the SMA, and the SAR switches below the price. Complementarily, if the MACD indicates a bullish move while the SAR flips below the price, but close[1] hasn’t closed above the SMA, wait for up to 5 candles for confirmation.

Conversely, a bearish signal appears when a candle closes below the SMA after a 3-candle sequence, with the SAR transitioning above the price. Aligning such strategies leverages simultaneous or prior MACD confirmation of the trend direction.

👉 Read | CodeBase | @mql5dev

#MQL4 #MT4 #Strategy

In the current phase of our statistical arbitrage project, we focus on integrating the stability of portfolio weights and time to mean reversion. The previous analysis relied on liquidity and cointegration strength but omitted these key aspects. We intend to enhance the scoring system by including these metrics.

Stability of portfolio weights is crucial as dynamic changes in financial markets can destabilize weights, risking a breakdown in mean reversion. Regular testing for weight stability prevents strategy pitfalls and adapts to market shifts. Additionally, the half-life of mean reversion quantifies the time expected for spread deviations to halve, influencing position management and risk exposure. A shorter half-life indicates more frequent trading opportunities with lower capital risk. Understanding and incorporating these factors will refine o...

👉 Read | Calendar | @mql5dev

#MQL5 #MT5 #Strategy

In Part 10 of our series on MQL5 for Expert Advisors, we introduce a strategy tracker system that enhances real-time performance monitoring. This system is capable of detecting moving average crossover signals filtered by a long-term moving average, and visualizes trade actions on the chart. It provides a comprehensive dashboard with performance metrics, including total signals, wins/losses, profit points, and success rates.

Implementation involves creating enumerations, input parameters, global variables, and helper functions for visualization. We leverage the MQL5 environment to handle moving averages, signal detection, and position tracking. Key features include modular dashboard creation, signal visualization, and both virtual and real trade simulations. This tool supports strategy evaluation, allowing for dynamic adjustments based on detailed f...

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#MQL5 #MT5 #Strategy

Explore the power of time-filtered trading within the MQL5 framework, where precision meets discipline. Using modular components such as the TimeFilter layer and SessionVisualizer, we can define specific trading windows, ensuring trades execute only during optimal market conditions. This approach minimizes noise and leverages session-based volatility, providing clarity and adaptability in trading strategies. By combining clock, session, and event-driven controls, traders and developers can create sophisticated automated systems that respond not just to price signals, but aligned with the market's temporal rhythm, enhancing decision accuracy and strategic performance in algorithmic trading environments.

👉 Read | Docs | @mql5dev

#MQL5 #MT5 #Strategy

The application of one-position-type strategies in live market environments presents an analysis based on Nvidia Corp’s stock (NVDA). Training and testing were conducted over distinct time periods, utilizing signals derived from multiple oscillator integrations, specifically RSI and DeMarker. Each pattern analyzes specific market movements, aiming to optimize entry and exit points across varying market conditions.

Pattern-5 focuses on slope confluence with range expansion, where synchronized momentum and price movements are logged. The buy signals are derived when RSI and DeMarker conditions align, demonstrating increased trader activity and potential market volatility.

Forward testing of Pattern-6 capitalizes on leading price movements with lagging indicators, identifying pullback entries for order continuation. The setup confirms trend strength w...

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#MQL5 #MT5 #Strategy

Enhancing black-box models for trading strategy selection presents complex challenges. Traditional metrics like RMSE often mislead due to sensitivity to scale and lack of comparability across regression targets. Mutual Information (MI) offers a more robust alternative. Its nonparametric nature and unitless measurement provide a consistent comparison across targets, helping identify the most informative strategies.

Empirical results demonstrate MI's superiority. Models predicting changes in the Stochastic oscillator show marked improvements, reflecting market width better than others. Visual analysis through scatterplots and bar plots further validate these findings, reinforcing MI's reliability.

In application, a neural network model, backed by ONNX, enables real-time strategy execution in MQL5, leveraging newfound insights for improved decision-ma...

👉 Read | AlgoBook | @mql5dev

#MQL5 #MT5 #Strategy

In Part 42, a customizable Session-Based Opening Range Breakout (ORB) system is developed in MQL5. The system captures true high and low during defined session times and identifies breakouts with multi-bar confirmation to minimize false signals. Trades are executed in the breakout direction with configurable stop-loss and take-profit options. The system incorporates dynamic or static risk-reward management and can utilize trailing stops upon reaching a profit threshold. Visualizations include range markers and entry signals for clarity. Implementation involves defining session times, range calculation, breakout identification, and position management, ensuring adaptability for various market sessions.

👉 Read | Docs | @mql5dev

#MQL5 #MT5 #Strategy