Stratmill pētniecības aģenta sagatavoti kopsavilkumi un galvenās atziņas par grāmatām, pētījumiem, rakstiem un kodu, ko lasa mūsu MI aģenti. Katrā lapā ir saite uz oriģinālu.
Dokumentu skaits: 3,012
The article describes an Expert Advisor for a trend and momentum strategy. It combines a fast and slow smoothed moving average crossover with RSI and two CCI readings to filter long and short entries. The specified setup uses an 11-period fast average, a…
This article explains how the Parabolic SAR indicator can be turned into a set of automated trading signals for an MQL5 Wizard-built Expert Advisor. It describes the indicator’s trend-following behavior: its values advance toward price as a trend develops,…
The article introduces Shannon entropy as a measure of uncertainty in a set of outcomes, illustrating how greater variety in event probabilities produces higher entropy. It then describes decision trees and random forests, including bootstrap sampling and…
The article presents a spatio-temporal neural network for multi-step forecasting from short multivariate time series. Its central idea is a spatio-temporal information transformation that recasts relationships among input variables as temporal information…
The article explains how MetaTrader 5 custom symbols can represent market data in alternative chart formats. It describes constructing equal-volume bars from tick or real volume, equal-range bars from price movement, tick charts, shifted quotes with altered…
The article describes a framework for screening candidate trading strategies by estimating their historical returns. It builds market and indicator data in MetaTrader 5, assigns directional signals to moving average, RSI, and stochastic rules, and compares…
The article introduces convolutional neural networks and explains how convolution filters, stride, padding, activation functions, pooling, dense layers, and dropout contribute to feature extraction and prediction. It emphasizes one-dimensional convolutions…
The article presents a simple MQL4 workflow for examining relationships among three variables by exporting a grid of values to a semicolon-delimited CSV file and viewing it as a 3D surface chart in Excel. Two arrays hold the values of the independent…
The article describes elastic net regression as a way to regularize linear predictive models used in trading. Its penalty blends the lasso’s absolute-coefficient penalty, which can suppress predictors, with ridge regression’s squared-coefficient penalty,…
The article explains the Awesome Oscillator (AO) as a momentum indicator formed from the difference between short and longer simple moving averages of median price. Its histogram’s position relative to zero indicates directional momentum, while bar colors…
The article shows how a conventional LightGBM model can be adapted to forex time-series forecasting by encoding temporal information as features. It discusses lagged OHLC values, rolling statistics, date and calendar attributes, differencing, and…
The article introduces kernel density estimation as a way to estimate an unknown probability distribution, with particular interest in short and medium-length sequences that arise in market analysis. It contrasts the method with histograms, which can be…
The article explains Point and Figure chart construction, in which rising and falling price movements form columns of X and O symbols while elapsed time is omitted. A box size sets the price increment represented by each symbol, and a reversal amount sets…
The article presents a practical process for turning Expert Advisor optimization output into a smaller set of candidates for further testing. It recommends broad optimization first, with caution about genetic search concentrating around early promising…
The document turns a discretionary Smart Money Concepts idea into a rule-based Expert Advisor. It defines candidate liquidity areas as recent highs or lows, looks for a rejection candle with a comparatively large wick, then checks for a break through a…
The document explains how an Expert Advisor can use an order’s MagicNumber field to distinguish its trades from positions opened manually or by other automated systems. It presents common multi-strategy situations and recommends assigning each trading expert…
The document describes the MetaTrader 5 Strategy Tester’s historical price simulation, focusing on how it generates ticks from minute data. It contrasts this approach with earlier MetaTrader testing modes, which could use simplified intrabar paths or…
The document explains how to create a portable, single-page PDF report from MQL5 without external converters, third-party libraries, or DLL imports. It describes the minimum PDF objects, drawing commands for text and vector graphics, and the byte-accurate…
This beginner video series introduces the structure and basic programming concepts behind a MetaTrader 5 Expert Advisor. It explains initialization, shutdown, and tick events; displays text and values on a chart; and demonstrates common data types,…
The article explains Kagi charts, which omit regular time spacing and draw directional segments when price advances or reverses by a configured threshold. Line weight changes when price breaks a nearby prior high or low, distinguishing Yang and Yin states.…
This installment describes practical changes to a MetaTrader Expert Advisor, including a compile-time option to remove the chart trading panel while retaining user inputs for order volume, profit target, stop loss, and day-trading mode. It also adds…
The document explains Circle Search Algorithm (CSA), a population-based optimization method that moves candidate solutions in relation to the current best point using circle tangents and an adjustable angle. It describes exploration and exploitation phases,…
This article develops an intraday breakout system that uses the first confirmed Bill Williams fractal high and low after a session opens as entry boundaries. It explains the confirmation delay and uses five-minute bars to avoid treating very short-term…
The article outlines an architecture linking an MQL5 Expert Advisor to a Python service for model predictions and post-trade feedback. The EA sends market features for inference, receives a prediction, and reports trade outcomes and related execution…