Automating Trading Strategies in MQL5 (Part 52): The tCISD Model with SSMT and Quarterly Theory
We build a tCISD program in MQL5 that pairs Quarterly Theory cycles anchored to New York time with a correlated-symbol SSMT divergence to time reversals. The article shows how to map cycles and quarters, detect the cross-symbol sweep disagreement, and derive the tCISD level whose break confirms the change in delivery. You will get a working entry logic that arms on divergence and executes on a confirmation close or a retest.
From Novice to Expert: Systematic Profit Conservation Using Candle Range Theory
A hybrid exit engine for MQL5 replaces static TPs with CRT-derived structural levels. The CRT_ProfitConserve class secures a partial at the first level and then trails the remaining position by structural anchors rather than fixed pips. The article walks through the class API, essential methods, and example usage in EAs, providing a clear path to embed CRT-based exits into existing strategies.
Designing a Unified Order Execution Gateway Class in MQL5
This class provides one point of contact for trade operations in MQL5. It rounds and clamps lot sizes, validates SL/TP against the broker's minimum distance, resolves a compatible filling policy, and applies bounded retries for transient retcodes. Calls return a structured CGatewayResult instead of raw retcodes, simplifying error handling and maintenance across strategies.
Unified Multi-Timeframe Renko: Synthesizing the Market's Temporal Dimensions
The article presents an innovative concept for a multi-timeframe Renko chart that combines signals from four timeframes (M5, M15, H1, H4) into a unified synthetic instrument. The system creates a virtual symbol in MetaTrader 5 by using the EMA of each timeframe to generate a composite signal through three methods: simple average, weighted average, and consensus. The implementation includes ATR-based adaptive brick sizing, real-time operation, and full integration with MetaTrader 5.
Elite Crystal Evolution Algorithm (CEO-inspired): Theory
A new original population-based algorithm, ECEA, is presented. Inspired by the process of water freezing, it adapts ideas from the Crystal Energy Optimizer (CEO) algorithm, which uses graph-based search, for general optimization problems. The algorithm uses a dynamic elite group, three search strategies, and a periodic diversification mechanism.
Neural Networks in Trading: An Intelligent Forecast Pipeline (Sparse Mixture of experts)
We invite you to explore the practical implementation of a sparse mixture of experts block for time series in the OpenCL computing environment. This article provides a step-by-step explanation of how masked multi-window convolution works, as well as how gradient-based training is organized in the presence of multiple information streams.