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

8 documents

Quant course library

The document describes a software framework for executing spread trades across multiple instruments. It tracks each leg’s orders, fills, costs, and positions, then estimates the spread’s completed volume and average fill price. For inverse contracts, it…

Multi-assetExecutionRisk management
Quant course library

This document describes a live monitoring system in which users define named formulas over instrument prices. The system subscribes to the instruments referenced by each rule, reads their latest available prices when market updates arrive, evaluates the…

Multi-assetTechnical indicatorsExecution
Quant course library

This document describes a graphical interface for defining and monitoring spread trades. Users can create standard or flexible spreads, specify leg instruments and directions, set a pricing formula, identify an active leg, and enter minimum trade volume. The…

Multi-assetPairs tradingExecutionMarket microstructure
Quant course library

This example outlines a multi-timeframe analysis workflow for Bitcoin-dollar price data. It loads minute history over a stated date range, configures a transaction-rate assumption and a rolling analysis window, and assigns technical indicators to several…

CryptoTechnical indicatorsMulti-asset
Quant course library

This document describes the data model and calculations behind a synthetic multi-leg spread. Each leg stores its market quotes, contract details, and position state. Configurable price multipliers define the spread price, while trading multipliers define how…

Multi-assetPairs tradingMarket microstructureBacktesting
Quant course library

This guide explains how a Python script engine can connect to trading gateways, subscribe to market data, query account and instrument records, and submit or cancel orders. It describes both an interactive notebook workflow and a continuously running script…

Multi-assetExecutionMarket microstructure
Quant course library

This algorithm takes liquidity in the active leg of a multi-leg spread when the quoted spread reaches a configured limit. For a long spread, it checks whether the ask is at or below the target; for a short spread, it checks whether the bid is at or above it.…

ExecutionMarket microstructureArbitrageMulti-asset
Quant course library

The document surveys the components of a Python trading framework, from connections to market venues through strategy development and automated execution. It outlines event-driven infrastructure, data handling, graphical tools, and applications for…

Multi-assetBacktestingExecutionRisk management