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.
4,574 documents
This article presents an MQL5 forex strategy that combines a higher-timeframe directional view with lower-timeframe technical confirmation. The fundamental framing treats long-run currency movements and possible policy constraints as context for market…
The article shows how to create a MATLAB graphical interface that receives live quote updates from MetaTrader 4 through Dynamic Data Exchange. It outlines the client-server roles, the advisory-link method used by MT4, and a GUI for selecting a currency pair,…
This article explains how to extend a MetaTrader 5 news-trading Expert Advisor so manual trade controls can act on several selected symbols from a single chart. A reusable trading-buttons class combines chart controls, symbol checkboxes, order functions, and…
The article teaches how to build an MQL5 indicator that draws pattern structures with chart objects rather than relying on indicator buffers and plots. Its example locates alternating swing highs and lows to form XABCD points, connects and labels those…
The article examines a simple strategy that trades reversals near the edges of an overnight range, focusing on currency pairs that may be relatively quiet during Pacific and Asian hours. It estimates the range from the highs and lows of the two bars before…
The article develops an MQL5 chart indicator for finding bullish and bearish Oops gap reversals. It defines a gap as an open beyond the previous bar’s low or high by at least a configurable minimum, then confirms the reversal when a completed bar closes back…
The article describes extending a MetaTrader strategy tester EA so it can replay real account deals while applying alternative StopLoss, TakeProfit, and trailing-stop rules. It discusses Parabolic SAR and moving-average trailing approaches, then adapts…
The article introduces category theory equalizers as a way to identify input cases where two mappings agree, then applies the idea to forecasting changes in bar range from changes in ATR. It normalizes both series as percentage changes, groups them into…
The article introduces the Mask-Attention-Free Transformer (MATF), originally developed for 3D point-cloud segmentation, and describes an interpretation for trading models. MATF addresses slow Transformer training attributed to poor initial object masks by…
The article turns Larry Williams’ Hidden Smash Day idea into explicit rules for an automated strategy. A bullish setup is an up-closing bar whose close lies in the bottom quarter of its own range; a bearish setup is the inverse, with the close in the top…
The article describes a high-throughput way to search for trading rules using tick histories rather than bars and indicators. It uses MetaTrader 5’s strategy tester, custom tick symbols, and a fast Expert Advisor that reacts to each tick. To reduce…
The article tests whether forecasting performance differs across 11 EURUSD time frames, using equal-sized samples of historical and future closing prices and a 20-step forecast horizon. It reports that models had lower errors on monthly and hourly data than…
The article describes an MQL5 expert advisor that manages trades across 30 forex and metal symbols from one chart. Traders can select which pairs to trade, add broker-specific symbol prefixes or suffixes, and restrict activity to a chosen trading session.…
This article presents an iterative pattern-search tool for trading, including a finite, modified Fourier-series polynomial as an alternative family of functions for describing price behavior. Its coefficients are generated through several random schemes, and…
The study examines why a moving average crossover system’s performance changes over time, using sixteen years of M15 EURUSD and GBPUSD data. It compares periods of strategy returns with ATR, Bollinger Band spread, and autocorrelation of bar price changes.…
The article presents a MetaTrader 5 system that combines Renko direction and EMA information from M5, M15, H1, and H4 into a synthetic symbol. It describes three signal-combination approaches: an equal average, a timeframe-weighted average, and a consensus…
The article examines whether apparent market randomness hides recurring hourly structure. It contrasts conventional autocorrelation of hourly price differences with seasonal autocorrelation, calculated after retaining observations from selected hours across…
This article explains disagreement-based exploration in reinforcement learning. An ensemble of forward dynamics models predicts the next environment state from the current state and action. The variance among their predictions becomes an intrinsic reward:…
The article outlines a discretionary-to-automated approach that uses monthly, weekly, and daily charts to set directional bias and identify potential long-term trades. Traders mark prior highs and lows, equal highs and lows, and other reaction areas such as…
The article shows how Numba just-in-time compilation can accelerate computationally intensive Python tasks while keeping a Python-based workflow. It explains that code intended for Numba’s fast nopython mode should avoid unsupported objects such as Pandas…
The article presents a spreadsheet sandbox that simulates random trades and displays common MetaTrader performance measures, including profit factor, relative drawdown, return, and winning or losing streaks. Users can vary starting capital, stop and…
The article introduces k-means clustering and contrasts it with hierarchical clustering and alternatives such as k-medians, k-medoids, Jenks natural breaks, and fuzzy clustering. It focuses on k-means++ initialization, which chooses initial centers in a more…
The article explains the Alligator indicator as three smoothed moving averages, called the Jaws, Teeth, and Lips, whose spacing and order are used to interpret market phases. Lines close together suggest consolidation; separation can mark a developing trend;…
This article compares a EURGBP daily moving-average crossover system with an AI-assisted version. The baseline combines exponential moving averages, a stochastic oscillator, and ATR-based exits. The proposed method trains models on earlier data to estimate…