MQL5 Programs Market

This article introduces a frequency-analysis framework for encoded candlestick patterns in MQL5. By transforming candlesticks into alphabetic symbols, historical price action can be analyzed as a statistical sequence rather than a visual chart. Using GBPUSD and Gold across multiple timeframes, the study examines the occurrence frequency of individual candlestick types, identifies dominant market structures, and reveals the symmetry between bullish and bearish price movements. The results establish a quantitative foundation for pattern discovery and prepare the way for analyzing multi-candlestick sequences and their predictive potential in algorithmic trading systems.

This article describes a live data export framework for MetaTrader 5 built around a decoupled, three‑layer design. The MQL5 component batches bar and tick records via a write buffer and rotates CSV files daily; a Python daemon tails the stream, renders a live dashboard, and flags anomaly thresholds. The demo indicator illustrates integration points, enabling real‑time monitoring and auditability during trading sessions.

In the previous article, I showed how to proceed in order to add a query mechanism. This was needed so that, inside MQL5 code, you could fully use SQL and retrieve results when executing a SQL SELECT ... FROM query. But there is still one last function we need to implement. This is the DatabaseReadBind function. Since understanding it properly requires a slightly more detailed explanation, it was decided to cover it not in the previous article, but in today's article. So, since the topic will be fairly extensive, let us proceed directly to the next section.

In this article, we will look at how the last three types of events generated by an object work. Understanding this will be very interesting, because in the end we will do something that may seem crazy to many people, but it is entirely possible and produces a very surprising result.

This article adds six order-flow functions and a new OrderFlowAnalysis struct to MicroStructureFoundation.mqh: VPINOHLC, signed flow imbalance, trade intensity versus a 20-session baseline, a late-minus-early smart-money index, flow momentum, and a wrapper that outputs a confidence weight. Flow confidence is gated by noise and jump intensity from Parts 5 and 4. Calibrated on 602 NQ M1 NY sessions, it provides ready-to-use intraday flow signals with documented thresholds.