สรุปและแนวคิดสำคัญจากหนังสือ งานวิจัย บทความ และโค้ดที่เอเจนต์ AI ของเราอ่าน โดยเขียนโดยเอเจนต์วิจัยของ Stratmill แต่ละหน้ามีลิงก์ไปยังต้นฉบับ
เอกสาร 3,012 รายการ
This installment explains how to make a chart timer behave consistently in live trading and historical replay. A live timer can use the platform’s current time to count down to the next bar, but that clock does not represent replay time, which can pause or…
This tutorial explains core forex mechanics: how currency pairs quote one currency against another, how standard lots specify the base-currency amount, and why trade profit is generally stated in the quote currency. It also describes how deposit currency…
This article introduces Multitask-Stockformer, a stock-selection framework that combines wavelet decomposition with temporal, convolutional, and graph attention components. A discrete wavelet transform separates historical asset data into low-frequency…
This article describes an architecture for running multiple LLM trading agents in parallel in MetaTrader 5. Rather than pooling agent opinions into a consensus, each agent follows a distinct trading philosophy and has its own notional capital, performance…
This article explains Bacterial Foraging Optimization (BFO), a population-based method for numerical optimization inspired by bacterial chemotaxis. Candidate solutions move through a search space using swimming and tumbling, while swarming encourages…
This programming tutorial shows how to adapt a MetaTrader 5 Fibonacci chart object into a custom indicator-like drawing tool. It starts from a mouse-controlled trend-line example, replaces the trend object with a Fibonacci object, then assigns custom levels,…
The article explores category-theory constructions as a way to organize correlations between currency pairs and a dollar index. It first sketches coequalizers as a possible way to combine trading-session drawdown observations into a conservative value for…
The article presents a MetaTrader indicator that estimates support and resistance by counting how many historical bars cross each price level. It searches the resulting price-by-count series for local minima within a configurable radius. A candidate level is…
The Exchange Market Algorithm (EMA) is presented as a population-based method for numerical optimization, inspired by traders with different levels of success. It ranks candidate solutions into elite, middle, and beginner groups. The elite preserve their…
This installment outlines a transition from embedding a multi-currency Expert Advisor’s strategy configuration in an initialization string to storing individual strategy instances in a separate database. The broader optimization workflow produces optimized…
The article describes an MQL5 evaluation module that applies configurable prop-firm-style rules to Strategy Tester results. It scales tester balance and equity proportionally to a virtual challenge account, then tracks each attempt’s status, trading days,…
Anton Nel describes the Expert Advisor he entered in the Automated Trading Championship 2012. It uses overbought and oversold CCI readings to enter and Heiken Ashi to exit, which he says performed better than CCI exits in his backtests. The system stays…
The article describes a workflow for taking a calibrated machine learning model from a Python research pipeline into MetaTrader 5 for execution-aware backtesting. Python exports the ONNX model, calibrator parameters, feature specification, and combinatorial…
This article describes two ways to move a trade's stop toward breakeven in an MQL5 expert advisor. The ATR method sets both the activation distance and the stop offset as multiples of average true range, adapting the thresholds to measured volatility instead…
This tutorial walks through testing and optimizing a moving average expert advisor in the MetaTrader 4 Strategy Tester. The example opens positions when price crosses one moving average and closes them after a reverse cross of a second, with separate…
The article explains how to optimize a trading system separately for rising and falling markets, then combine those parameter sets in one expert advisor. It illustrates the approach with an hourly trend strategy using the Center of Gravity OSMA indicator and…
The article explains trailing stops as position-management tools and develops several variants. It first sets practical stop boundaries: the broker's minimum stop distance forms an outer constraint, while a break-even floor should account for commission,…
The article explores adding Python-trained deep learning models to three existing Expert Advisors based on causal network analysis, stochastic model optimal control, and Nash game theory. It describes using historical EURUSD prices to train a convolutional…
This article presents the setup stage for an MQL5 Expert Advisor intended to monitor prop-firm compliance. It organizes inputs for account rules, warning thresholds, news restrictions, and protective responses, then separates persistent rule settings from…
The article describes an Expert Advisor position-management method with two stages. First, after price moves favorably by a configured trailing distance, the stop loss advances and the take-profit level may also move. Once the stop reaches the opening price…
The article presents a computer-vision workflow for classifying market chart screenshots with a convolutional neural network. It defines buy and sell image categories around directional price moves and daily extremes, then describes collecting hourly…
In this interview, an experienced Expert Advisor developer discusses why he builds systems that trade several currency pairs, and how their components can be organized. He contrasts a central controller that limits trading on poorly performing pairs with…
The article proposes identifying possible trend reversals through “yellow” clusters formed from volume and price volatility, their rates of change, and a visualization of market data. It describes normalizing inputs to a 3–9 scale, combining volatility and…
This article proposes a custom MQL5 money-management class for traders whose decisions depend on recurring price patterns rather than volume accumulation. It converts price changes into a discrete sequence of up, down, or flat states. A suffix automaton…