Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
3,012 documents
This installment of an MQL5 Economic Calendar series describes making a chart dashboard movable and adding hover feedback to its controls. The approach detects pointer coordinates over the header and buttons, changes colors on hover, and treats header…
This article explains how an MQL5 Expert Advisor can send trade events to a local HTTP server through WinINet. OnTradeTransaction serializes opens and closes as JSON and places them in an in-memory queue; a timer callback attempts delivery separately so…
This MQL5 tutorial adapts an existing expert advisor into a framework for a Triple Screen system. It uses moving averages on three configurable timeframes, with example defaults of weekly, daily, and four-hour screens. Each screen can be disabled by setting…
The article outlines a multi-symbol expert advisor that tracks a two-hour price range for each selected instrument, from 10:00 to 12:00 UTC+2. After the range closes, an upside break can trigger a buy when the Stochastic reading is at or below 20; a downside…
This guide explains how to prepare a requirements specification for a custom trading indicator. It recommends defining the indicator’s purpose first, then describing its calculations and behavior as an ordered sequence of steps. Terms should be explicitly…
The article shows how to move repeated order lookup and state management out of an expert advisor and into reusable functions. For a single position, the example scans open orders for a matching symbol and magic number, then stores the selected order’s…
The article proposes a nonlinear regression equation for forecasting prices from two prior observations. Its seven terms combine linear and squared price inputs, a difference representing momentum, a sine component intended to capture cycles, and a constant.…
The article outlines a multi-symbol Expert Advisor that evaluates mean-reversion and momentum signals separately for each instrument. It calculates a Z-score from price relative to a moving average and standard deviation, and measures momentum as a price…
The article describes a MetaTrader Expert Advisor for finding and marking common single, double, and triple candlestick patterns. Users can search for one named formation or scan all supported patterns over a selected historical window. A chart panel…
The article explains how the Goertzel algorithm computes selected discrete Fourier transform frequencies efficiently, making it an option when only a limited range of cycle periods is of interest. It describes a class that scans periods, returns real and…
The article presents a Python-to-MQL5 workflow for selecting technical indicators using FXI, an ETF tracking large-cap Chinese equities. It segments four-hour price history into quarterly windows to compare candidate indicators across changing volatility,…
The article describes an MQL5 Expert Advisor for a session range breakout strategy. It defines the range using the high and low from midnight to 6 AM, then looks for a breakout during a later time window. A Break of Structure confirmation, based on price…
The document presents a way to make trading forecasts more interpretable by translating fitted machine-learning models into algebraic expressions. Its example uses technical features derived from price bars, including returns, volatility, RSI, MACD, and…
This article describes incorporating an adapter-tuned GPT-2 model into a MetaTrader Expert Advisor for trading decisions. It compares three deployment approaches: converting the model to ONNX for in-platform inference, launching Python scripts from the EA,…
The document explains a MetaTrader indicator design for keeping chart drawings consistent across multiple windows of the same symbol. A user selects a base timeframe, and the system assigns other open charts to a predefined set of timeframes. Chart events…
The document describes an MQL5 chart indicator that combines two WaveTrend oscillator configurations. A faster setup detects crossovers for potential buy or sell signals, while a slower setup indicates the broader trend and can filter out signals that run…
This programming tutorial develops MQL5 array concepts through examples involving memory use, enumerations, and data representation. It explains that the number of array elements differs from the memory footprint when element types occupy more than one byte,…
The document explains Artificial Cooperative Search, a population-based optimization method inspired by cooperative and predator–prey interactions. It maintains two candidate populations, selects one as predators and another as prey, shuffles prey solutions,…
The document describes an MQL5 Expert Advisor that uses automatically detected swing highs and lows to calculate Fibonacci retracement levels and projected extension targets. It focuses on a retracement entry, typically at 61.8%, and uses swing structure to…
This article develops code and a visual test bench for generating and inspecting random values from uniform, Gaussian, power-law, and Lévy-style distributions. Its focus is how distribution shape, finite bounds, and a selected center affect the likelihood of…
The article presents a MetaTrader 5 dashboard that combines structural direction from several timeframes into a normalized Harmony Index ranging from bearish to bullish. Each enabled timeframe receives a bias based on a three-bar staircase rule, with…
This installment extends a MetaTrader 5 library that stores historical timeseries for multiple symbols and periods. Its central problem is keeping non-chart symbols current without repeatedly refreshing every series on a timer, which wastes work when no…
The article describes a Python library that mirrors several MQL5 Standard Library trade classes for use with the MetaTrader 5 Python package. It outlines wrappers for account, symbol, order, history, position, deal, and terminal information, along with a…
The article describes a chart tool for manually marking swing points and automatically drawing related Wolfe Wave guides. In the example buy setup, the trader identifies points 1 through 4, checks their relative positions, and projects a possible fifth point…