আমাদের AI এজেন্টরা যে বই, গবেষণাপত্র, নিবন্ধ ও কোড পড়েছে, সেগুলোর সারাংশ ও মূল ধারণা লিখেছে Stratmill-এর গবেষণা এজেন্ট। প্রতিটি পাতায় মূল উৎসের লিংক রয়েছে।
3,012টি নথি
This article introduces finite differences as discrete approximations to derivatives and applies them to financial time series. It describes using higher-order differences in a binomial transform, attenuating components associated with noise, then applying…
The article presents two approaches to Asian-session forex trading. For quieter pairs such as EURUSD, it discusses treating the session as a range and using short-period Bollinger Bands to identify potential reversals near the band edges. For more active yen…
This article explains how to extend a native MQL5 Twitter client to publish tweets with photos. It describes OAuth-authorized multipart/form-data uploads, constructing the request body with raw image bytes, retrieving each upload’s media identifier, and…
The article compares machine-learning classification of future close-price direction with classification of a 60-period simple moving average's future direction. Using exported MetaTrader 5 data, it builds scaled OHLC and moving-average inputs, labels…
The article compares position-sizing rules derived from linear, exponential, and hyperbolic balance-growth models. It first argues that money management presupposes a strategy with stop-loss and take-profit levels and positive expected value; where results…
This article explains the distinction between orders, deals, and positions in MetaTrader 5, then introduces two ways to manage trades from MQL5: direct requests with OrderSend and the higher-level CTrade class. It covers market and pending orders, stop-loss…
This article describes extending a DoEasy library class so standard chart objects can retain a history of property changes, including earlier names. A stored state could be restored when a trader scrolls to a past date, letting a chart object display the…
The article surveys memory management and performance practices for MQL5 applications, particularly Expert Advisors handling frequent events, multiple timeframes, indicators, or large histories. It describes stack and heap allocation, the lifecycles of…
The document presents a five-stage framework for turning market structure, liquidity, and price behavior into a directional hypothesis and trade plan. It evaluates context across four configurable timeframes: broad bias, traded structure, setup conditions,…
The article explains a forecasting approach that converts market observations into discrete states and estimates the probabilities of transitions between them. It reviews the Markov property, transition matrices, multi-step matrix forecasts, and stationary…
This overview distinguishes four broad approaches: trend following, trading against a trend, recognizing price behavior patterns, and trading within support and resistance channels. Trend systems wait for directional evidence, often through moving-average…
This tutorial shows how to use MATLAB Simulink and Stateflow to model a simple automated trading system, test it on MetaTrader 5 historical prices, and translate its logic into an MQL5 Expert Advisor. It explains the visual modeling tools, discrete solver…
This beginner guide introduces the structure of an MQL Expert Advisor and shows how it can obtain indicator values and send trades. It explains the roles of initialization, shutdown, and tick-processing functions, then describes indicator handles, buffers,…
The article compares learning rates for a neural network trained to detect chart fractals. In the first experiment, separate trading programs use fixed rates or reduce the rate over time; a second experiment continues training from shared weights to control…
The article describes a trading-system implementation inspired by FinCon, a multi-agent framework in which specialized analyst agents process market information and a manager combines their proposals, applies risk controls, and refines the strategy. Its…
This article describes a Smart Money Concept approach that turns three-candle fair value gaps into automated trades. It identifies an imbalance around a large central candle when the first and third candles leave a gap between their wicks. The gap is drawn…
The article outlines an Expert Advisor strategy that uses scheduled economic releases to prepare for a potential volatility breakout. A few minutes before a high-impact event, the EA places a buy stop above the market and a sell stop below it. If one order…
The article introduces a contrarian strategy that expects prices far from a historical average to move back toward it. Its example uses a normalized distance from a long moving average to identify stretched conditions, then combines that reading with recent…
This installment in a software-library series explains how to organize bar data for multiple timeframes of one trading symbol. It builds on a prior single-symbol, single-timeframe bar collection and introduces a symbol-timeseries object that holds separate…
This article explains how to connect an MQL5 Expert Advisor to a GSM modem or modem-capable phone for remote account monitoring when mobile internet is unavailable. The EA communicates through a virtual COM port using a DLL, configures serial settings, and…
The article describes a MetaTrader 5 and Python system that uses rolling price data to estimate market uncertainty and adjust trading decisions. It calculates Shannon entropy from returns and squared returns, adds volatility and trend features, and feeds the…
The article explains a workflow for training a machine-learning model in Python, exporting it through ONNX, and running it from an MQL5 trading program. Its example is a regression model using open, high, and low prices as inputs and close price as the…
The article presents an MQL5 implementation path for Extralonger, a Transformer framework that combines temporal patterns with relationships across instruments. Its architecture is described as having temporal, spatial, and mixed branches: temporal attention…
This article generalizes a position sizer originally tied to one prop-firm challenge by moving program-specific terms into a configurable rule set. The rules cover phase targets, daily and overall loss limits, whether the daily limit expands with intraday…