Skip to content

Knowledge library

Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.

Quant Q&A
20,364 documents
SuperMind
12,226 documents
OKX Learn
8,431 documents
Strategy library
7,910 documents
MQL5 code base
7,090 documents
BigQuant
3,481 documents
Bitget Academy
3,298 documents
MQL5 articles
3,012 documents
TradingView scripts
1,976 documents
ProRealCode
1,507 documents
Deribit Insights
1,232 documents
Machine Learning for Trading
1,124 documents
arXiv papers
1,033 documents
Amberdata research
766 documents
FMZ forum
682 documents
FMZ digest
662 documents
vn.py community
560 documents
QuantInsti blog
511 documents
Galaxy Research
340 documents
QuantStart
246 documents
Stratmill research code
219 documents
Robot Wealth
195 documents
NautilusTrader
191 documents
Hummingbot docs
181 documents
Paradigm research
175 documents
Lumibot
164 documents
Kraken Learn
163 documents
Quant course library
157 documents
OctoBot
152 documents
Cryptohopper blog
144 documents
Systematic trading blog (Rob Carver)
132 documents
Qlib
116 documents
TqSdk
86 documents
Quantpedia
86 documents
Hyperliquid docs
79 documents
Freqtrade
68 documents
Hudson & Thames
62 documents
Awesome Systematic Trading
61 documents
backtrader
54 documents
vn.py
50 documents
Binance API docs
45 documents
Quantopian lectures
45 documents
FMZ guides
38 documents
pysystemtrade
34 documents
Freqtrade docs
32 documents
quant-trading
31 documents
FinRL
28 documents
Zipline
22 documents
FMZ live strategies
21 documents
Jesse
17 documents
pyfolio
16 documents
Alphalens
14 documents
WonderTrader
14 documents
backtesting.py
11 documents
Technical Analysis
9 documents
QTPyLib
8 documents
QuantRocket
7 documents
Lumibot strategies
7 documents
Awesome Quant
1 documents

Search the library

3,012 documents

MQL5 articles

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…

Machine learningStatisticsBacktesting
MQL5 articles

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…

Machine learningStatisticsRisk management
MQL5 articles

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…

Mean reversionBreakoutMarket microstructureRisk management
MQL5 articles

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…

Event-drivenExecutionMarket microstructure
MQL5 articles

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…

Machine learningStatisticsBacktesting
MQL5 articles

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…

Multi-assetMean reversionVolatilityBacktesting
MQL5 articles

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…

StatisticsMachine learningBacktesting
MQL5 articles

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…

ExecutionMarket microstructure
MQL5 articles

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…

Technical indicatorsBreakoutRisk management
MQL5 articles

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…

Technical indicatorsStatisticsForexCommodities
MQL5 articles

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.…

BacktestingRisk managementStatistics
MQL5 articles

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,…

Technical indicators
MQL5 articles

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…

Technical indicatorsTrend following
MQL5 articles

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…

Risk managementPosition sizingStatistics
MQL5 articles

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…

BacktestingMarket microstructureExecution
MQL5 articles

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.…

Technical indicatorsVolatilityExecutionRisk management
MQL5 articles

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…

ForexTechnical indicatorsRisk managementBacktesting
MQL5 articles

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…

Machine learningStatisticsBacktesting
MQL5 articles

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…

ExecutionBacktestingTechnical indicators
MQL5 articles

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…

Execution
MQL5 articles

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…

CommoditiesTrend followingMachine learningBacktesting
MQL5 articles

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…

Machine learningBacktestingStatistics
MQL5 articles

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…

ForexRisk managementPortfolio construction
MQL5 articles

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…

Machine learningStatisticsBacktesting