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 a local voice interface for a MetaTrader Expert Advisor. A Python listener uses offline speech recognition to detect a wake phrase, recognize a limited set of trading commands, and expose the latest parsed command through a local HTTP…
The article outlines a EURUSD mean-reversion system that uses weekly moving averages of highs and lows to form a channel. A move above the upper average is treated as an overbought condition and a short candidate; a move below the lower average is treated as…
The article surveys five routes to automated trading: mathematical modeling, manual study of market behavior, neural-network “black boxes,” programming infrastructure before developing a strategy, and buying an existing robot. It recommends that beginners…
The article explores three changes to the Commodity Channel Index. First, it replaces the usual division by standard deviation with multiplication, then sets positive and negative signal levels separately from the observed frequency of indicator values.…
This technical strategy combines 5-period and 14-period stochastic oscillators with a 200-period moving average. A long setup requires both oscillators to reach oversold territory, rebound, and revisit that area while price is above the moving average. The…
The article presents a workflow for connecting MetaTrader 5 to the ENCOG machine-learning framework through a C# bridge. Its example uses a feedforward neural network trained with resilient propagation to forecast financial time series. Stochastic %K,…
This article outlines an automated MQL5 system that combines Envelopes and RSI signals with zone recovery. It describes entering around a trend bounce when price reaches an Envelopes boundary with supporting momentum, then opening counter-trades if price…
This article presents a single rule set intended to adapt a moving-average strategy to both trending and range-bound conditions. Its baseline buys when price closes above a 100-period moving average and sells below it, with fixed stop-loss and take-profit…
The article explains how to adapt an Expert Advisor generated by the MQL5 Wizard so its pending orders can be placed at a price calculated by the trading system. The standard setup uses a fixed price offset from the current market. The proposed modification…
The article develops a machine learning mean reversion system for EURGBP, covering trade labeling, market regime identification, model training, and deployment in MetaTrader 5. It contrasts random horizon labels with labels based on how far prices deviate…
The article presents a workflow for mining associations in hourly data for four major currency pairs. It exports historical bars, calculates returns and technical features such as moving averages, RSI, MACD, volatility, Bollinger bands, and candle patterns,…
The article introduces procedural and functional programming concepts through a MetaTrader 5 expert advisor. Its example buys when the latest closed candle is bullish and entirely above an exponential moving average, and sells when a bearish candle is…
The article describes an MQL5 canvas tool for plotting paired symbol prices as scatter points, fitting a linear regression line, and displaying slope, intercept, correlation, and R-squared. It explains correlation as a measure of direction and strength of…
The article explains a MetaTrader 5 Expert Advisor that monitors account activity and displays a daily drawdown dashboard. Its approach derives the day's starting balance from the current balance and that day's closed deal profit, commission, and swap, then…
The article walks through adapting a supervised PatchTST time-series model for use from an MQL5 expert advisor. It explains the model’s use of reversible instance normalization to normalize inputs and restore forecast scale, decomposition into trend and…
The article explains money management as control over the loss a trade can incur, rather than as a formula that scales lots only with account balance. It argues that strategy performance depends on win rate, average win, and average loss, and that losses…
This article extends a Strategy Builder based on Merrill patterns with additional testing and reporting options. The prior version summarized results in points; the update lets users measure profit in points or account currency, set an initial deposit, and…
The article explains SARSA, an on-policy reinforcement-learning method, and describes using it as an independent signal model in an MQL5 Expert Advisor. Its Q-value update uses the action actually selected in the next state under the agent’s current policy,…
The article outlines a pipeline for characterizing multifractality in EURUSD five-minute returns. Starting from partition-function slopes calculated in an earlier installment, it extracts the scaling function tau(q), estimates the Hurst exponent using…
This article describes changes needed to add a SimpleCandles strategy to a modular, multi-currency Expert Advisor project and its automated optimization workflow. It emphasizes keeping reusable library code independent from project-specific logic, then…
The article describes an ensemble for a moving average channel Expert Advisor. The channel uses moving averages of high and low prices to generate breakout signals, while a Ridge Regression model uses the same technical indicators. Trades are allowed only…
This article refines a symbolic candlestick classification system by splitting previously unclassified candles into bullish and bearish categories. It retains symbols for several candle shapes and assigns a direction-specific fallback when a candle matches…
This implementation guide describes a MetaTrader 5 Expert Advisor that combines a short-period RSI with a simple moving average to generate buy and sell decisions. The moving average is used as a trend filter, while RSI thresholds indicate potential…
This article presents a MetaTrader indicator for examining a trading signal’s historical deals across the symbols it traded. Its goals include comparing activity by symbol, estimating simultaneous exposure, distinguishing overlapping positions that hedge…