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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

The article outlines an MQL5 system for classifying market behavior as trending, ranging, or volatile. It motivates regime awareness by explaining that strategies built for one condition may struggle when the market changes. The proposed foundation combines…

StatisticsVolatilityTrend followingMean reversion
MQL5 articles

The article presents an MQL5 architecture that turns AI analysis into structured signals an Expert Advisor can route, parse, display, and potentially execute. A central dispatcher maps stable action identifiers to separate workflows, each with its own data…

Machine learningExecutionBacktestingTechnical indicators
MQL5 articles

This tutorial introduces the MetaTrader 5 Economic Calendar and explains how its event data can be accessed from MQL5 programs. Calendar entries include country and currency associations, event descriptions, importance, scheduled times, and reported values…

Event-drivenForexMachine learning
MQL5 articles

This article describes chart indicators for inspecting MetaTrader 5 Strategy Tester runs. A reusable chart template can load a selected indicator automatically during visual testing. The Ticks indicator displays recent bid and ask ticks, shows their timing,…

BacktestingRisk managementExecution
MQL5 articles

The article explains how neural networks can support trading systems, focusing on signal generation and indicator calculation. It distinguishes forecasting a future closing price from producing a decision signal during a trading session, and argues that the…

Machine learningTechnical indicatorsForexBacktesting
MQL5 articles

This article presents ways to combine classifiers whose outputs may be discrete class choices, confidence values, probabilities, or ordinal rankings. It explains why rankings can help compare models with differently scaled outputs and why they are more…

Machine learningStatisticsBacktesting
MQL5 articles

This programming tutorial explains how MQL5 represents date and time values and applies them in trading-system logic. It introduces the datetime type as a count of seconds, shows how to compare and adjust timestamps, and describes conversions between strings…

ExecutionStatistics
MQL5 articles

The article presents StockFormer, a hybrid framework that combines Transformer-based predictive coding with an Actor–Critic reinforcement-learning agent. Three branches learn representations for long-horizon trends, next-day returns, and changing…

Machine learningEquitiesPortfolio constructionBacktesting
MQL5 articles

This article describes a MetaTrader 4 workflow for collecting profitable Expert Advisor optimization runs across multiple backtests into HTML tables that can be analyzed in spreadsheet software. It proposes recording separate results for long and short…

BacktestingStatisticsForex
MQL5 articles

The article explains how to calculate four common moving averages from price history in MQL5: simple, exponential, smoothed, and linearly weighted. It outlines each method’s weighting behavior and provides indicator implementation examples, starting with a…

Technical indicatorsForex
MQL5 articles

This article develops a pending-order strategy based on unusually high tick volume during a candle. It compares current volume with the average from a chosen number of closed candles, then scales the threshold according to a base deviation and an additional…

ForexMomentumBreakoutPosition sizing
MQL5 articles

This article describes an Expert Advisor that combines Bill Williams fractals with 14-period and 200-period exponential moving averages to mark potential breakout entries. For a bullish signal, price must cross above a recent fractal low while trading above…

Technical indicatorsBreakoutTrend followingBacktesting
MQL5 articles

This article extends a MetaTrader utility for filtering and navigating symbols with separate tabs for all candidates and user-selected long, short, and range lists. It describes storing each tab’s symbols in an array, drawing tab buttons in a loop, showing…

EquitiesExecution
MQL5 articles

The article presents an indicator that selects two swing points using DeMark-inspired rules, then draws rising or falling trend lines. Candidate peaks and troughs are identified by comparing each bar with its neighbors and applying additional close-price…

Technical indicatorsTrend followingStatistics
MQL5 articles

The article develops a modified ZigZag indicator and a class intended to make its swing data easier to retrieve and study. Its key adjustment is to use maximum bid prices for highs and minimum ask prices for lows, incorporating spread into the plotted…

Technical indicatorsMarket microstructureStatisticsBacktesting
MQL5 articles

The article surveys visual tools in the MetaTrader 5 strategy tester for examining both individual tests and optimization runs. Tester statistics include trading activity by month, day, or hour, distributions of maximum favorable and adverse excursion, and…

BacktestingTechnical indicatorsStatistics
MQL5 articles

The article describes an Expert Advisor that periodically retunes its strategy parameters against a rolling span of historical data. A manager requests candidate parameter sets from an optimization algorithm, runs each set through a virtual copy of the…

BacktestingMachine learningTechnical indicatorsRisk management
MQL5 articles

This installment explains how a MetaTrader trading engine can coordinate multiple independent strategy instances within one Expert Advisor. Its CStrategyList manager distributes events such as ticks, timers, and book updates to each strategy, while handling…

Portfolio constructionExecutionBacktesting
MQL5 articles

This article recasts a binary recurrence matrix as the adjacency matrix of an undirected network: observations become nodes, and recurrent pairs become edges, with self-links removed. It explains how network measures such as degree, clustering, transitivity,…

StatisticsTechnical indicatorsMulti-asset
MQL5 articles

The article discusses account-model differences that matter when adding automation to a MetaTrader Expert Advisor. Netting accounts combine trades in a symbol into one position with an average price, while hedging accounts keep positions separate and can…

ExecutionRisk managementPosition sizing
MQL5 articles

This installment describes organizing MQL5 code for projects that use a shared Expert Advisor library. It recommends keeping each project in its own repository and placing each dependency in an Include folder as a separate repository clone. A shared library…

StatisticsBacktestingMulti-asset