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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

9,660 documents

MQL5 code base

This short MetaTrader programming note shows how an expert advisor can detect the arrival of a new chart bar by comparing the current bar count with the count saved during initialization. It stores the baseline in an integer, refreshes a second count on each…

ExecutionStatistics
MQL5 code base

This document describes an indicator that displays recent bid and ask ticks, showing the latest 300 observations. It can also run in a strategy tester, where users can examine how different tick-generation modes produce similar or different tick sequences.…

Market microstructureExecutionBacktesting
FMZ forum

This article describes a high-frequency trading tactic that tries to profit from a large buyer who repeatedly raises a displayed bid. The trader first moves the market up by a tick, watches whether the buyer follows, and continues stepping prices higher if…

High-frequency tradingMarket microstructureExecutionRisk management
MQL5 code base

The document describes an indicator for viewing historical tick data, showing both Ask and Bid prices. Comparing the two series lets a trader inspect how the spread changes over time. It uses a date query to retrieve ticks and can display a selected number…

ForexMarket microstructureExecution
FinRL

The page introduces FinRL as a framework for applying deep reinforcement learning to automated stock trading. It explains that reinforcement learning agents learn through interaction and trial and error, while deep neural networks approximate the functions…

Machine learningEquitiesPortfolio constructionExecution
FMZ forum

This document raises implementation questions about trading two OKEX futures maturities through one exchange object. Its example switches between the this-week and quarterly contracts to request tickers over WebSocket, then switches again before submitting…

CryptoFuturesArbitrageExecution
vn.py community

The discussion explains how to inspect a strategy's logical position during a VeighNa backtest. The strategy's `self.pos` value represents its net position quantity and updates as the strategy processes opening and closing trades. It is scoped to the…

BacktestingExecution
MQL5 code base

This document describes an expert advisor that counts observed spreads in predefined ranges as market ticks arrive. It reports the counts separately for each year and prints the statistics to the trading platform’s journal when it stops, making the output…

StatisticsMarket microstructureExecution
Hummingbot docs

This guide explains how to create and fund a Vega wallet, connect it to Hummingbot, and launch a sample directional strategy on Vega perpetual markets. The sample uses RSI to open long positions in oversold conditions and shorts in overbought conditions,…

CryptoPerpetual futuresTechnical indicatorsExecution
vn.py

These release notes describe changes across versions of the VeighNa trading framework. For quantitative research, notable updates include a cross-sectional percentile ranking function, revised factor and signal performance analysis, an added VWAP matching…

Machine learningFactor investingBacktestingExecution
NautilusTrader

The document explains how NautilusTrader connects to Tardis historical files, Tardis Machine streams, and the Tardis API. It describes loading normalized CSV data, replaying historical feeds into Parquet catalogs, and configuring live or replay clients. A…

CryptoMarket microstructureExecutionDerivatives pricing
MQL5 code base

This brief indicator description identifies an Ergodic tick-volume tool built around multiple exponential moving averages and attributed to William Blau. It concerns tick volume, a measure of price updates that can serve as a proxy for trading activity,…

Technical indicatorsMarket microstructureExecution
MQL5 code base

This document describes a MetaTrader 4 toolkit that combines chart information, support and resistance drawing, order planning, and chart controls. Its money-management panel lets a trader position entry, stop-loss, and take-profit lines, inspect the…

ForexTechnical indicatorsRisk managementPosition sizing
ProRealCode

This indicator description presents the Zex as a lower-timeframe tool intended for scalping. It begins with a Stochastic Momentum Index calculated from closing prices, smooths that series with a triangular average, and defines a histogram from the difference…

Technical indicatorsMomentumExecution
MQL5 code base

The document outlines a trade-opening function for a trading platform. It says the function derives an opening price, take-profit levels, and a stop-loss from user parameters and symbol information, then assembles a trade request containing details such as…

ExecutionRisk management
MQL5 code base

OrderNotify is an expert advisor watcher that emails information whenever a trade is opened or closed. The message is intended to include details about the affected trade, allowing a user to receive notifications from an expert advisor’s activity. To use it,…

ExecutionHigh-frequency trading
NautilusTrader

This brief quickstart introduces a minimal Rust live node that connects a Lighter data client to public Testnet market streams and runs a built-in data tester. It is intended to confirm that the data path works before adding trading functionality. The guide…

ExecutionMarket microstructure
NautilusTrader

This guide describes setup paths for connecting a Rust or Python application to Lighter through a live trading node. It recommends establishing public market-data subscriptions first, using tester actors to check client wiring, and then adding an execution…

ExecutionMarket microstructureMarket makingRisk management
MQL5 code base

This description explains an expert advisor that maintains configurable grids of pending orders above and below the current market price. Traders choose the number of orders per side, spacing, lot size, slippage limit, and the order types used on each side.…

ForexGrid tradingExecutionRisk management
BigQuant

The article argues that Rust can suit quantitative trading infrastructure where large data workloads, dense computation, concurrency, and low latency matter. It attributes this fit to Rust’s performance, memory and thread safety guarantees, and lack of…

ExecutionHigh-frequency tradingEquitiesFutures
NautilusTrader

The document explains how a simulated trading engine processes each market-data point in three stages: the exchange matches existing orders against the updated market, strategies receive the data and can issue commands, and venues settle eligible commands…

BacktestingExecutionMarket microstructureRisk management
vn.py community

This forum post explores how VeighNa's historical bar loading relates to strategy initialization, bar aggregation, and trading decisions. The author asks whether loading bars at minute, hourly, or daily intervals supplies the corresponding historical data,…

FuturesExecutionMarket microstructure
NautilusTrader

QuoteTick represents a single instrument’s best available bid and ask, including the displayed size at each price and event and initialization timestamps. The document specifies the required fields and describes precision constraints: bid and ask prices must…

Market microstructureExecution