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.
2,013 documents
The article describes a universal MetaTrader 4 and 5 template that runs robots for multiple symbols from one chart. It explains the motivation: simplify setup, reduce the load of many chart instances, and evaluate a combined multi-instrument equity curve.…
The article introduces principal component analysis as a way to reduce the dimensions of data while retaining directions that explain much of its variance. It reviews eigenvectors and eigenvalues, compares PCA with singular value decomposition and power…
This tutorial develops multivariate probability concepts for analyzing how market variables behave together. It defines joint cumulative distributions and densities, explains how marginal distributions are derived, and distinguishes independence from…
The article describes extending the DoEasy library so a custom indicator can display a standard indicator calculated for a different symbol and timeframe. Its example uses the Accelerator Oscillator, with buffer properties recording indicator identity,…
The article explains how to build a MetaTrader 5 dashboard that compares relationships among selected instruments. It computes simple returns from recent closing prices, calculates pairwise Pearson correlation coefficients, then presents the values in a…
In this interview, Automated Trading Championship participant Alexandr Artapov discusses the design and operation of a multicurrency Expert Advisor. He describes applying a common indicator-based strategy across selected currency pairs, grouping symbols into…
This article outlines a Python and MetaTrader 5 architecture in which agents analyze different instruments and share signals through a coordination layer. It describes role-based agents, shared portfolio context, and a service that sends structured signals…
The document explains Hierarchical Risk Parity (HRP), a portfolio allocation method that uses asset similarity and risk rather than directly optimizing expected returns. It outlines the process: estimate returns, covariance and correlation; cluster assets by…
This article describes automating the second stage of a multi-currency Expert Advisor optimization workflow: selecting groups of individually optimized strategy instances whose combined behavior may improve drawdown or balance-curve smoothness. Instead of…
This article turns the eigenvalue spectrum of a portfolio covariance matrix into a normalized diversification measure. It computes log returns for the instruments, builds a covariance matrix, extracts and sorts its eigenvalues, and converts them into shares…
This article extends a MetaTrader 5 history navigator with named bookmarks that preserve a chart’s symbol, timeframe, timestamp, and optional notes. It describes how these records let traders return to notable historical patterns, reversals, breakouts,…
This installment covers operational safeguards for moving a multi-currency Expert Advisor from testing toward live accounts. It describes configurable symbol-name mappings for broker-specific prefixes, suffixes, or other naming differences; a mode that stops…
This programming article describes a reusable MQL5 wrapper around the platform’s WebRequest function, modeled on Python’s Requests library. Its goal is to simplify HTTP communication from MetaTrader, including sending GET, POST, PUT, and other request types,…
This overview explains how MetaTrader 5 expands on MetaTrader 4 for automated trading across exchange-traded instruments as well as forex. It highlights MQL5’s faster execution ambitions, object-oriented and procedural programming, event handling, and…
This document describes an MQL5 dashboard that organizes symbols by rows and timeframes by columns, displaying a color-coded score for each combination. The score combines a linear trend slope, price-change momentum, and price volatility using configurable…
This article explains how MQL5 represents colored indicator plots when an indicator handles multiple symbols and timeframes. A plotted series may need one or more data arrays, depending on its drawing style, plus a separate color-index array for colored…
This installment describes the foundation of a reusable MQL5 symbol object for gathering and comparing instrument data. It proposes symbol categories such as major and exotic forex, metals, indices, cryptocurrencies, commodities, exchange-traded products,…
This article critiques conventional ZigZag indicators for their dependence on timeframe and price-excursion settings, and for frequently revising the most recent swing. It presents a custom fractal-based indicator designed to mark turning points using…
This article describes an MQL5 chart tool that scrolls information for several symbols, including bid and ask prices, spreads, and daily percentage changes. Its architecture stores symbol names and price state in arrays and a structure, then uses timed…
The document introduces SAGDFN, a graph neural network framework for forecasting multivariate time series when relationships among assets change over time. It describes learning connections from data and using Significant Neighbors Sampling to focus on a…
The document presents a method for aligning bar data across instruments before portfolio analysis or trading. It uses one instrument’s bar opening times as a reference, matches other symbols to those timestamps, fills missing bars, and trims excess history…
This article describes a chart-panel indicator that summarizes market conditions across a higher timeframe and two lower timeframes. It uses an exponential moving average to estimate higher-timeframe bias, swing highs and lows to classify lower-timeframe…
The article explains how to combine several strategies and symbols in one MetaTrader 5 Expert Advisor (EA) to assess their performance together. It organizes each strategy’s symbol-specific settings and indicator handles in arrays, then processes them in…
The article explains how to reuse selected MQL5 Standard Library components in expert advisors that must compile under both MQL4 and MQL5. Its approach is to copy the relevant MQL5 headers, place them in an organized MQL4 library folder, and add shared…