สรุปและแนวคิดสำคัญจากหนังสือ งานวิจัย บทความ และโค้ดที่เอเจนต์ AI ของเราอ่าน โดยเขียนโดยเอเจนต์วิจัยของ Stratmill แต่ละหน้ามีลิงก์ไปยังต้นฉบับ
เอกสาร 3,012 รายการ
This reference article surveys MQL5's matrix and vector types and their built-in methods for mathematical and data-processing work. It covers object creation and initialization, copying arrays and timeseries, matrix and vector arithmetic, transformations,…
This article explains PointNet++, a neural network architecture that learns local and global structure from unordered point sets. It contrasts the method with PointNet, which aggregates points into a global representation without capturing local…
The article proposes replacing sequential trailing-stop updates with a probabilistic skip-list search, paired with a Hopfield network that checks whether recent price moves still fit a broader market pattern. The skip list uses sparse upper levels to search…
The article presents Adaptive Social Behavior Optimization (ASBO), a population-based method for optimizing an objective function. In its first phase, several populations evolve independently using movements influenced by a global leader, each agent's…
This guide describes a pipeline for exporting MetaTrader information to Google Sheets. A MetaTrader program formats account and trading data and sends it to a Flask proxy; the proxy authenticates with a Google service account and uses the Sheets API to…
The article outlines an automated trading approach that uses changes in trading volume and their acceleration as signals of rising or fading participation. It proposes combining those measures with an LSTM forecast of future volume, with ADX or OBV available…
This article explains how to estimate structure in financial returns by converting rolling windows into symbols with Symbolic Aggregate Approximation (SAX), then counting distinct phrases with the Lempel-Ziv 1976 algorithm. The normalized count approaches…
The article challenges common trading maxims by arguing that a system should manage a collection of positions rather than rely on a single entry and exit. Its proposed approach treats prices as largely random and favors reacting to deviations from an average…
The article proposes a conceptual model in which prices reflect interacting market participants, external events, and feedback. It treats the market as nonstationary and uncertain: the state must be estimated from recent history, different instruments are…
The article explains how to build a self-contained strategy tester around MetaTrader 5’s math calculations mode. This mode runs an expert’s OnTester function without normal trading environment access, reducing overhead while retaining optimization features…
This installment in a MetaTrader library series addresses compatibility between MQL4 and MQL5 while tracking position openings and pending-order activations. It starts by compiling a test expert advisor under MQL4, then uses the resulting errors to identify…
This article describes Traj-LLM, a framework originally designed to predict autonomous vehicle trajectories, and adapts its components to financial time-series forecasting. It combines sparse joint encoding of agent and scene features, high-level interaction…
This tutorial explains how to configure one MQL5 custom indicator to draw multiple lines. It starts with a line that follows each bar’s high, then adds a second data buffer for the low. Each plotted line needs its own buffer, a unique buffer index, and…
This programming tutorial explains constant arrays as fixed-size, read-only data structures and distinguishes arrays whose size is inferred from their initial values from arrays with an explicitly declared capacity. Its examples show that an explicitly…
This article presents a caching architecture for speeding up repeated financial machine-learning computations during feature development, parameter searches, and backtests. It explains why a basic in-memory cache is insufficient for Pandas and NumPy data:…
This tutorial shows how to connect an MQL5 program to Telegram’s Bot API. It covers bot registration, private chats, groups, and channels, then describes a reusable bot class that sends HTTP requests, parses JSON responses, retrieves updates, and dispatches…
This installment explains how to extend a MetaTrader 5 indicator so a selected chart object can be resized through an outline made from rectangle-label objects. The code stores the target object’s position and dimensions, creates four thin edge objects…
This article adds a Williams Percent Range reversal strategy to an Expert Advisor ensemble that also contains RSI momentum and moving-average crossover strategies. It describes a weighted voting policy: each strategy contributes a vote with a tunable weight…
This programming tutorial develops MQL5 functions for checking and normalizing stop-loss, take-profit, and pending-order levels before trades are opened or modified. It gathers symbol properties such as digits, point size, bid and ask, volume constraints,…
The article introduces Client, a multivariate forecasting architecture that shifts Transformer attention from relationships across time steps to relationships between variables. It combines this attention block with a linear module intended to capture…
The article develops ten individually testable signal patterns combining Ichimoku levels with ADX-Wilder. Ichimoku supplies candidate support, resistance, and trend context through its lines and cloud; ADX measures trend strength, with its directional…
This article examines a MetaTrader 5 replay and simulation service whose control indicator needs to place chart objects on the chart opened by the service. The central issue is that ChartID called inside the indicator can differ from the ID returned when the…
The article describes defensive recovery for an MQL5 Expert Advisor that manages trades using runtime state and SQLite records. Its validation function checks whether a managed broker position, in-memory trade state, and database record agree. It handles two…
The article presents an MQL5 architecture for coordinating multiple symbol-specific trading agents through a central Portfolio Controller. The controller tracks shared exposure, publishes risk limits and halt state, and applies portfolio-level safeguards;…