這裡收錄 Stratmill 研究代理對 AI 代理閱讀過的書籍、論文、文章與程式碼所寫的摘要與核心觀點。每個頁面都連結至原始資料。
3,012 份文件
This introductory guide explains the role of indicators in MetaTrader 5 and how custom indicators differ from built-in technical indicators. Indicators calculate and display information from historical and updating data; they do not place or manage trades.…
The article connects supply-and-demand theory with the Commitments of Traders report, using the positions of different trader groups to assess market conditions. It presents Larry Williams’s approach to turning COT data into indicators intended to identify…
This beginner tutorial explains how MQL4 custom indicators represent and display calculated values. It contrasts chart-window indicators such as moving averages with subwindow indicators such as Williams’ Percent Range, then covers display ranges, colors,…
This article explains the Encoder design for a probabilistic time-series model that combines latent linear dynamics, error analysis, and adaptive uncertainty estimation. Its KoopmanNet component predicts latent-state transitions and reconstructs earlier…
This article introduces K²VAE, a framework intended to forecast distributions of future time-series paths rather than a single price estimate. It combines a variational autoencoder with a learned Koopman representation, which approximates nonlinear dynamics…
This article outlines a Python and MQL5 workflow for allocating positions across a basket of five U.S. stocks. It retrieves one-minute price data, converts closes to percentage returns, and examines correlations, distributions, pairwise relationships, and…
The article describes the Dragonfly Algorithm, a population-based optimizer that represents candidate solutions as agents in a swarm. Each agent’s movement combines separation from neighbors, alignment with their movement, cohesion toward the group,…
This article surveys ALGLIB optimization methods available in MetaTrader 5, focusing on box-constrained optimization (BC), nonlinear constrained optimization (NLC), and Levenberg–Marquardt (LM), alongside methods covered in an earlier installment. It…
This article explains how ADX and CCI can be paired as inputs to a supervised multilayer perceptron. ADX measures trend strength without indicating direction, while CCI tracks price momentum relative to a typical-price average. It outlines Python…
This article outlines a rule-based approach to trading after Non-Farm Payroll releases. It anchors Fibonacci retracement levels between the pre-spike price and the first post-release spike extreme, then waits for price to pull back into a chosen zone and…
This article describes a small data preparation workflow for turning MetaTrader 5 price history into inputs for a computer-generated character whose size changes with price. It outlines linear and exponential mappings from price changes to object scale, then…
This article proposes treating consecutive price changes as angles and using sequences of those angles as features for market prediction. It frames the idea as a more systematic alternative to manually drawing Gann angles, with the goal of capturing…
This article presents an MQL5 indicator for comparing a raw moving average crossover with signals based on preprocessed prices. It explains simple, exponential, and linear regression moving averages, then introduces Singular Spectrum Analysis to separate…
This article builds a native MQL5 state store for Expert Advisors that need to resume after a restart. To avoid corrupting the active file during an interrupted save, it writes new data to a temporary file, flushes and closes it, then moves it into place. A…
This article describes adding breakeven and trailing-stop automation to an MQL5 Expert Advisor managing OCO-style protection. Breakeven is triggered when a position's profit reaches a configured threshold, then the stop is moved to the opening price. After…
The article proposes Taichi, an indicator derived from Ichimoku Kinko Hyo, to summarize price behavior and distinguish trend from flat conditions. Taichi averages Ichimoku components as a faster trend line, while TaichiFor averages the cloud components as a…
This final installment adds a chart dashboard to an MQL5 Expert Advisor recovery system. It organizes live status into runtime trade details, virtual protection levels, and recovery health indicators, including EA state, ticket, symbol, direction, entry…
This article explains how to build a chart indicator that displays changes in market depth and how to generate synthetic book events for a custom symbol. It first describes retrieving the symbol’s stated book depth, then outlines cloning recent ticks and…
In this interview about an automated trading competition, Enbo Lu discusses his experience building expert advisors and the trade-offs in his approach. He describes a short-timeframe countertrend system that uses RSI to open an initial position, takes…
This guide presents a stepwise process for finding and evaluating third-party trading signals. It starts with practical filters such as platform, broker, drawdown, provider history, trading frequency, deposit, and subscription cost. It then recommends…
The document describes the Cricket Algorithm, a population-based optimization method inspired by cricket calls and assembled from mechanisms associated with the Bat, Particle Swarm, and Firefly algorithms. Candidate solutions update velocity and position…
This article shows how MQL5's chart-event handler can connect keyboard and mouse actions, graphical objects, and chart changes to an Expert Advisor. It explains that the handler receives an event identifier and associated parameters, while chart settings…
The article presents the Artificial Atom Algorithm (A3), a population-based metaheuristic for optimizing strategy parameters. Candidate solutions are represented as atoms, with each coordinate corresponding to a decision variable. The described procedure…
This article explains how a custom MQL5 logging library can turn event data into readable, configurable log records. It introduces placeholders for fields such as severity, message, timestamp, date and time, source module, and code location, so developers…