Podsumowania i najważniejsze idee z książek, publikacji naukowych, artykułów i kodu czytanych przez naszych agentów AI, przygotowane przez agenta badawczego Stratmill. Każda strona zawiera link do oryginału.
Liczba dokumentów: 3,012
The article presents a standalone MetaTrader 5 dashboard for analyzing account performance across strategies without changing the trading Expert Advisors. It reconstructs closed positions from individual buy and sell deals, groups records by position…
The article develops a strategy around Doji patterns detected in metabars, which combine consecutive ordinary bars over a variable width. Because a Doji is treated as a possible reversal rather than a standalone entry signal, the method first checks for a…
This overview explains exchange pricing through competing buyers and sellers, whose orders specify prices and available quantities. It builds from individual offers and bids to aggregated market depth, then discusses how orders match, how market and limit…
This programming tutorial explains how MQL5 indicators can create and move chart objects, respond to keyboard input, and coordinate with other applications on a chart. Its examples include a horizontal line that displays the prior quote’s price, a keyboard…
The article describes converting ADAM, originally a gradient-based optimizer used in neural networks, into a population-based method for general optimization problems. It reviews ADAM’s first- and second-moment updates, then outlines how the population…
The article concludes a series testing signal rules that combine the Stochastic Oscillator with the Fractal Adaptive Moving Average (FrAMA). It describes setups for low-volatility compression breakouts, stochastic W/M formations intended to re-enter trends,…
The article presents an Expert Advisor that measures historical outcomes for Doji, Engulfing, and Pinbar patterns. It scans bars for each formation, then checks whether price moves in the suggested direction on the next bar, within a configurable forward…
This guide explains how to build a Delphi DLL for use from MQL5. It covers project setup, exporting callable functions with compatible calling conventions, and matching MQL5 types to Delphi types. It also explains passing values versus references, handling…
The article introduces Kohonen maps, also called self-organizing maps, as an unsupervised method for mapping higher-dimensional observations onto a lower-dimensional grid while preserving neighborhood relationships. It explains competitive learning: each…
This article presents a reusable MQL5 utility layer for common trade management tasks. It describes functions to detect and count positions using filters such as symbol, magic number, position type, and ticket, along with helpers for closing positions and…
The article explains autoencoders as unsupervised neural networks that learn a compressed latent representation by encoding input data and training a decoder to reconstruct it. It outlines uses including dimensionality reduction, preprocessing, and noise…
The article presents a price-action system that builds parallel channels from significant swing highs and lows, then monitors both boundaries for breakouts. Swing detection can filter small movements using a multiple of average true range. Candidate channels…
The document outlines an Expert Advisor built around a reversal pattern: a run of three candles in one direction, a short counter-move, and a confirming candle in the original direction. The pattern is mirrored for long and short entries, and signals are…
This article describes a self-adapting trading algorithm that analyzes price in variable-sized blocks and opens positions in linked series. Its central addition is a rule for starting another series while an earlier one remains open: the prior series’…
The document explains the Relative Moving Average framework, which describes a current price’s position within a trailing window rather than treating a smoothed average as a signal. It computes a local simple moving average, expresses window landmarks as…
The article ports a Python fractal feature set into an event-driven MQL5 engine while preserving causal timing. A fractal centered on bar c requires n later bars for confirmation, so the feature values are published at the confirmation bar and refer back to…
This article describes a workflow for tuning a two-hidden-layer deep neural network used to classify market data. It prepares pretraining, training, validation, and test sets; removes predictors judged statistically insignificant in earlier work; and uses…
The article explains how to construct a price channel in MQL4 from confirmed fractal turning points. It searches a timeframe-specific bar range for two upper or lower extrema, projects a line through them, then locates an opposing extremum to draw a parallel…
The document describes an MQL5 Expert Advisor that changes its trading approach according to a detected market regime. It uses trend-following logic for rising or falling trends, an RSI-based mean-reversion example in ranging conditions, and a Bollinger Band…
The document explains Turtle Soup as a reversal strategy that trades failed breaks of recent highs or lows. A move beyond an N-bar extreme may trigger clustered stop orders; the strategy waits for price to return inside the range, then sells a failed high…
This article presents reusable MQL5 utilities that extend matrix and vector operations, with an emphasis on preparing data for trading systems and machine-learning workflows. The functions described include reading numeric or categorical CSV data, writing…
The article extends an MQL5 ARIMA class with easier prediction methods and model saving and loading. It explains why forecasts need enough input observations: autoregressive terms require lagged values, non-contiguous lags preserve intervening time…
This beginner-oriented article introduces MQL5 file operations through the first part of a trading-journal project. It explains how a script can use a file-selection dialog to let a trader choose an existing CSV file or enter a new filename, then open the…
The article explains an MQL5 method for proposing Elliott Wave labels from price-chart turning points. It first outlines classical impulse and corrective-wave structures and their constraints, then describes two broad approaches to automatic labeling:…