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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
Quantopian lectures
45 documents
Binance API docs
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

191 documents

NautilusTrader

The document explains how venue adapters connect exchange APIs to a trading system’s shared data and execution engines. It describes the typical roles of HTTP and WebSocket clients, instrument providers, data clients, and execution clients, then shows how…

ExecutionMarket microstructureRisk management
NautilusTrader

This example sets up a backtest for a Bitcoin to USDT market on Binance using level two market-by-price order book snapshots and updates. It configures a cash account with BTC and USDT balances, a maker taker fee model, and an order book imbalance strategy.…

CryptoMarket microstructureBacktestingExecution
NautilusTrader

This reference explains how to represent a contract for difference as a trading instrument. A CFD tracks an underlying asset without transferring ownership; the venue determines its quote currency, precision, increments, order limits, margin settings, and…

Derivatives pricingRisk managementExecution
NautilusTrader

The tutorial explains how to backtest a mean-reversion strategy on EUR/USD perpetual futures using TrueFX spot ticks as proxy data. It builds one-minute mid-price bars, then combines a 20-period Bollinger Band with a 14-period RSI: a lower-band touch with…

ForexMean reversionTechnical indicatorsBacktesting
NautilusTrader

This reference explains the order-pending-update event used after a system sends a modify-order request. The execution engine applies the request to the order, updates its cache, and publishes the event while waiting for the venue to acknowledge the change.…

ExecutionMarket microstructure
NautilusTrader

This example demonstrates borrow conflicts that can occur when Python actor callbacks reenter signal operations in a backtesting engine. A subscribing actor subscribes during startup and, in the signal scenario, publishes a nested signal from its callback…

BacktestingExecution
NautilusTrader

This example configures a composite market-making strategy that uses NVDA equity quotes as its signal and quotes an NVDA perpetual contract on Lighter. The settings specify a maximum position and trade size, a half-spread, inventory and signal skew factors,…

Market makingPerpetual futuresEquitiesExecution
NautilusTrader

An OrderFilled event represents an execution against an order, whether the execution completes the order or only fills part of it. The execution engine applies the event to the order, updates the cache, and publishes it through the message bus. Fills can…

ExecutionMarket microstructure
NautilusTrader

A market order tells a venue to execute a specified quantity promptly at the best available price. The document outlines when traders might use one, such as urgent risk reduction or entering a liquid, fast-moving market, and shows how an order can include…

ExecutionForexMarket microstructureRisk management
NautilusTrader

This reference explains the fields used to describe a listed put or call on a non-crypto underlying. It covers contract identity, underlying asset, option type, strike, activation and expiration times, premium currency, price precision, minimum price…

OptionsDerivatives pricing
NautilusTrader

This example configures a live market-making strategy for an NVDA perpetual contract on Lighter, using NVDA equity quotes from Databento as an external signal. The strategy combines a configured half-spread with inventory and signal skew, limits position…

Market makingPerpetual futuresEquitiesExecution
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
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
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
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
NautilusTrader

This guide explains how a backtest engine turns each OHLCV bar into four synthetic book updates, processes resting orders along that path, and dispatches the completed bar to strategies afterward. It covers timestamp conventions, venue and book requirements,…

BacktestingExecutionMarket microstructure
NautilusTrader

This example shows how to configure a live trading node to test order handling on the Deribit testnet. At startup, the built-in tester can open a position with an immediate-or-cancel order, then maintain post-only limit orders on both sides of the book. It…

CryptoExecutionMarket microstructure
NautilusTrader

This guide describes connecting to AX Exchange, a regulated venue for derivatives on traditional asset classes. It outlines perpetual and dated futures, including USD cash settlement, funding payments, contract sizing, margin, and how the adapter maps venue…

FuturesPerpetual futuresExecutionMarket microstructure
NautilusTrader

This document describes a plotting workflow for examining Betfair backtest logs that record bid and ask volumes by runner. It extracts periodic batch volumes and cumulative imbalance, then creates three visual views: imbalance over successive updates, the…

Market microstructureStatisticsBacktesting
NautilusTrader

This guide explains how a backtest engine can use trade ticks as evidence for executing resting orders, and how that behavior changes with L1, L2, or L3 market data. Trade aggressor direction determines which passive side can be filled. The guide describes…

ExecutionMarket microstructureBacktesting
NautilusTrader

This technical reference describes an OKX integration for market data and order execution across spot, margin, perpetual swaps, dated futures, options, spreads, and event contracts. It outlines the adapter's data and execution components, instrument loading…

CryptoFuturesOptionsExecution
NautilusTrader

This example shows how to configure a multi-venue backtest with distinct account and execution settings. It builds a probabilistic fill model with limit-fill and slippage probabilities, a static latency model with separate delays for order insertion,…

BacktestingExecutionMarket microstructureRisk management
NautilusTrader

This integration guide describes a Rust and Python adapter for connecting NautilusTrader to Coinbase Advanced Trade. It covers live market data and order execution for spot products and Coinbase Financial Markets derivatives, including perpetual swaps and…

CryptoSpot marketsPerpetual futuresFutures