Stratmill tyrimų agento parengtos knygų, straipsnių, mokslinių darbų ir kodo, kuriuos skaito mūsų DI agentai, santraukos ir pagrindinės mintys. Kiekviename puslapyje pateikiama nuoroda į originalą.
3,012 dokumentų
This article explains polynomial regression as linear regression on features formed by raising inputs to different powers. That lets a model fit curved relationships while remaining linear in its coefficients. It walks through forming the normal-equation…
This article introduces conformal prediction and MAPIE as tools for adding uncertainty estimates to existing machine-learning forecasts. A model is trained on one dataset, then conformity scores from a separate calibration set are used to form prediction…
The article presents an automated volume-profile approach built around the Point of Control, high- and low-volume nodes, and the Value Area. It treats high-volume regions as areas where price may meet support or resistance, low-volume regions as possible…
This article explains how to organize an MQL5 expert advisor around the platform’s event model instead of placing all work in OnTick. It assigns market updates, periodic background tasks, user-interface actions, trade lifecycle changes, and order-book…
This article experimentally examines ways to improve bagged neural-network classifiers built from market data. It prepares indicator and OHLC-derived predictors, ranks features, and compares three treatments for noisy training examples: correcting their…
The article argues that limited market history can leave a trading system exposed to only one realized path, then proposes generating synthetic price series to examine a rebuy algorithm across many independent instruments. Its price model uses discrete…
The article adapts the immune-inspired Dendritic Cell Algorithm (DCA), originally developed for anomaly detection, into a population-based optimization method. It maps candidate fitness to danger and safety signals, which dendritic cells accumulate over…
This installment explains why a basic Python echo server accepts only one client and why blocking socket calls can make Excel unresponsive when Python runs through Excel. It introduces threads as a way to handle client connections concurrently, with each…
This tutorial outlines an MQL5 Expert Advisor that detects standard and inverse Head and Shoulders formations, marks their swing points on a chart, and places trades after a neckline breakout is confirmed by a candle close. For an inverse setup, the…
This article refines a symbolic candlestick classification system by splitting previously unclassified candles into bullish and bearish categories. It retains symbols for several candle shapes and assigns a direction-specific fallback when a candle matches…
This article explains how to build an MQL5 script that reconstructs closed trades from deal history and displays them in their original chart context. Entry and exit times, stop-loss and take-profit levels, and a trade annotation are drawn as chart objects.…
This article describes a MetaTrader 5 indicator that combines multiple built-in oscillators behind a chart-based graphical interface. The interface lets a trader switch indicators and adjust the selected indicator’s parameters while viewing the result,…
The document explains how Heikin Ashi candles smooth traditional OHLC data to make trends easier to inspect. The close is the average of the current bar’s open, high, low, and close; the open is derived from the prior Heikin Ashi open and close. High and low…
The article reframes technical analysis as a control problem in which analysis and position management operate together. Rather than focusing mainly on predicting turning points, it asks how positions should change as market conditions and the account’s…
This article describes a MetaTrader 5 market replay design that separates one-minute bar construction from the expert advisor. A service reads tick data and updates a custom symbol, while a script starts the service and an EA is intended for later simulation…
This article presents a UT Bot indicator and an automated trading implementation aimed at quick entries and exits. The indicator calculates a volatility-adjusted trailing stop using average true range, then tracks whether price is above or below that stop.…
This implementation guide describes a MetaTrader 5 Expert Advisor that combines a short-period RSI with a simple moving average to generate buy and sell decisions. The moving average is used as a trend filter, while RSI thresholds indicate potential…
This article outlines an enhanced Chaos Optimization Algorithm intended to search complex, multimodal objective functions. Its three phases combine a broad search driven by chaotic maps, a weighted-gradient search that accounts for constraints, and a local…
The article presents a file-based method for passing bar data between MetaTrader 4 and MATLAB. An MT4 indicator writes recent OHLCV bars to a semicolon-separated file when a new bar arrives. MATLAB monitors the file’s modification time, reads and processes…
This implementation guide shows how to bundle sound files inside a MetaTrader 5 Expert Advisor and play them for selected events. It distinguishes terminal alerts, which use configured sounds and display a message, from custom playback through PlaySound. The…
The article describes a unidirectional gold trading workflow that combines K-Means clustering with CatBoost classifiers. Rolling standard deviations of closing prices form both the main model’s features and separate meta-features used to identify market…
The article explains how to use MQL5’s Alglib classes to build a basic perceptron for testing trading ideas in an Expert Advisor. It outlines the roles of network setup, training data, training routines and forward processing, and describes normalizing input…
This article presents a MetaTrader indicator for examining a trading signal’s historical deals across the symbols it traded. Its goals include comparing activity by symbol, estimating simultaneous exposure, distinguishing overlapping positions that hedge…
The article describes the Artificial Searching Swarm Algorithm (ASSA), a population-based method for optimizing difficult, potentially discontinuous or mixed-type objective functions. Each agent can move toward a recently improved agent in response to a…