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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

191 documents

NautilusTrader

This example shows how to set up a crypto strategy backtest using Binance ETHUSDT trade ticks. It loads trade data from a CSV, registers the instrument and a cash account, and configures a maker taker fee model with equal stated rates. The example strategy…

CryptoTechnical indicatorsBacktestingExecution
NautilusTrader

This tutorial describes a short-term order book imbalance strategy for a gold perpetual contract. It uses CME gold futures best bid and ask quotes as a proxy for the exchange contract, then triggers fill-or-kill orders toward the thinner side when the bid…

CommoditiesPerpetual futuresMarket microstructureBacktesting
NautilusTrader

The document explains how a currency pair represents a spot or cash instrument quoted as base currency against quote currency. It distinguishes the asset being traded from the currency used to price it, and describes how the instrument type can represent…

ForexCryptoSpot marketsExecution
NautilusTrader

This guide explains how a live trading system rebuilds and checks its internal order and position state against venue reports. At startup, it uses cached state when available, or creates state from venue orders and positions. During runtime, recurring checks…

ExecutionRisk managementMarket microstructure
NautilusTrader

The document presents two example automated strategies. The first combines Bollinger Bands with RSI: it enters long when price closes at or below the lower band and RSI is below a configurable threshold, and enters short when price reaches the upper band…

Mean reversionTechnical indicatorsMarket microstructureExecution
NautilusTrader

A limit order rests in the order book at a chosen price and can execute only at that price or a more favorable one. Traders can use it to control execution price, provide liquidity, make markets, scale into or out of positions, or seek maker fees when…

ExecutionMarket microstructureFuturesCrypto
NautilusTrader

This document sets out how contributors should measure and report performance in trading software. It distinguishes small hot-path microbenchmarks from scenario benchmarks that approximate larger user workflows, and argues that benchmarks should represent…

BacktestingExecutionMarket microstructureStatistics
NautilusTrader

The document explains how a trading portfolio values positions, converts PnL and exposure across currencies, calculates equity, and records account snapshots. It describes price and exchange-rate selection, including mark prices, side-specific quotes, last…

Multi-assetPortfolio constructionRisk managementStatistics
NautilusTrader

The document explains a data object for recording changes in an instrument's venue trading state. It includes the instrument identifier, a normalized status action, event and initialization timestamps, and optional fields for a reason, venue event label,…

Market microstructureExecutionRisk management
NautilusTrader

This script runs a NautilusTrader backtest of a Bollinger Band and RSI mean-reversion strategy on EUR/USD perpetual contract quotes. It reads TrueFX bid and ask ticks, builds a margin venue with a starting balance and maker/taker fees, and aggregates data…

ForexMean reversionTechnical indicatorsBacktesting
NautilusTrader

This reference explains how an engine represents cash, margin, betting, and wallet accounts across backtests and live trading. It defines total, locked, and free balances and requires them to reconcile at currency precision. It also describes how pending…

Risk managementPosition sizingPortfolio constructionDerivatives pricing
NautilusTrader

The document explains two ways to obtain option sensitivities in a trading system: consume venue-reported Greeks, or calculate Black-Scholes values from cached market data. Venue values can be subscribed to, stored, and replayed as market data. The local…

OptionsDerivatives pricingRisk managementBacktesting
NautilusTrader

The overview describes a multi-asset trading platform that uses a Rust core for event-driven processing and Python for strategy control and system orchestration. Its central design idea is to use common strategy and execution components across research,…

BacktestingExecutionMarket microstructureMulti-asset
NautilusTrader

This documentation explains how NautilusTrader routes order commands from strategies through emulators or execution algorithms, risk checks, the execution engine, and venue clients. It distinguishes command paths for submissions, modifications,…

ExecutionRisk managementPosition sizingMarket microstructure
NautilusTrader

This example shows how to assemble and run a small backtest for an EUR/USD strategy. It creates artificial one-minute bars: an initial bar followed by a sequence of rising bars and then falling bars, with prices shifted by a fixed number of ticks and…

ForexBacktestingExecution
NautilusTrader

This Chinese-language post outlines a stock screen for companies in the metaverse theme whose prior-day price is above the 250-day moving average and whose price-to-earnings ratio is positive. The stated rationale combines a thematic category, a long-term…

EquitiesChina marketsTechnical indicatorsFactor investing
NautilusTrader

The roadmap describes NautilusTrader’s priorities as a production-oriented algorithmic trading engine. Its main plans are to stabilize the Rust runtime and Python bindings, improve documentation and tutorials, and make APIs and configuration easier to use.…

BacktestingExecutionMarket microstructurePortfolio construction
NautilusTrader

This plotting script creates four explanatory visuals for an ETH short-strangle options example. The panels show expiry profit and loss for a short put and call, how the combined option delta may change as spot moves, how a threshold-triggered hedge could…

OptionsDerivatives pricingVolatilityRisk management
NautilusTrader

This reference explains how an exchange-defined futures spread is represented as a single tradable instrument, including calendar and inter-commodity spreads. The venue supplies the strategy symbol, tick size, expiry, and other contract details. The…

FuturesCommoditiesDerivatives pricingMarket microstructure
NautilusTrader

This documentation explains a trading platform’s logging architecture and configuration for both backtests and live systems. Python and platform events pass through a logger into a multi-producer, single-consumer queue, then a dedicated thread writes them to…

BacktestingExecutionRisk management
NautilusTrader

This reference explains a mark price update as a data record for an instrument’s current mark price. The record includes an instrument identifier, price value, event timestamp, and initialization timestamp. It distinguishes mark prices from trade…

CryptoPerpetual futuresRisk managementBacktesting
NautilusTrader

This overview explains NautilusTrader’s market data types, order book levels, event flags, instruments, and bar construction. It distinguishes order by order L3 books from aggregated L2 books and top of book L1 books. Delta flags mark snapshot content and…

Market microstructureTechnical indicatorsBacktesting
NautilusTrader

This example demonstrates how to model a futures contract reaching expiry in a backtest. It loads instrument definitions and best bid and offer quote data for two consecutive E-mini S&P 500 contracts, then submits a market buy for one expiring-contract unit…

FuturesBacktestingExecution