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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

8,116 documents

NautilusTrader

This reference explains how to represent an exchange-listed cryptocurrency option spread as one tradable instrument. It describes the instrument identity, underlying and quote and settlement currencies, inverse sizing flag, strategy type, activation and…

CryptoOptionsDerivatives pricingRisk management
Amberdata research

This podcast recap contrasts the sharp equity selloff after unexpectedly severe U.S. tariff announcements with Bitcoin’s relative price and implied-volatility stability. It discusses possible explanations, including earlier crypto deleveraging, seller…

CryptoOptionsVolatilityRisk management
Amberdata research

This product update describes several analyses for crypto derivatives and blockchain activity. Its options material includes constant-maturity butterfly values across selected deltas and time windows, at-the-money implied volatility box plots, and dealer…

OptionsVolatilityDerivatives pricingOn-chain data
Amberdata research

This market commentary reviews Bitcoin and Ether options through realized and implied volatility, expiry term structures, call skew, and relative value. It reports Bitcoin realized volatility in the mid-30s and Ether near 50 after spot weakness, while…

OptionsCryptoVolatilityDerivatives pricing
Amberdata research

The document explains how implied volatility (IV) surfaces organized by option moneyness can help identify relative pricing anomalies. A floating surface compares options at their actual listed expirations, while a constant surface interpolates or…

OptionsVolatilityDerivatives pricingCrypto
Amberdata research

This weekly market review surveys Bitcoin and Ether options through realized and implied volatility, term structure, skew, relative value, option flows, and dealer gamma positioning. It describes falling front-end implied volatility, a pronounced shift…

CryptoOptionsVolatilityDerivatives pricing
Amberdata research

The document explains volatility cones as percentile benchmarks of historical realized volatility across several lookback periods. Traders compare current realized volatility with levels such as the lower quartile, median, and upper quartile to judge whether…

CryptoOptionsVolatilityRisk management
Amberdata research

This mid-week recap summarizes conditions in Bitcoin and Ether derivatives as of January 18, 2023. It highlights realized volatility returning above 20%, a shift to inverted term structures, and a complete reversal in skew. These measures describe different…

CryptoOptionsVolatilityDerivatives pricing
Amberdata research

This market recap interprets Bitcoin and Ether options volatility, term structure, skew, trading flows, and dealer gamma around anticipated spot ETF decisions. It reports rising implied volatility alongside stable recent realized volatility, with Bitcoin’s…

CryptoOptionsVolatilityMarket microstructure
BigQuant

The document describes Panoptic, a decentralized protocol that offers perpetual options linked to Uniswap liquidity pools. It explains how concentrated liquidity ranges can serve as strike selection and how liquidity provision can create option-like…

CryptoOptionsVolatilityDeFi
Lumibot

This page catalogs trading bot examples built around AI agents, ranging from copying reported investor or insider holdings to sentiment signals, agent debates, options strategies, intraday rules, and macro or sector portfolio discussions. It outlines…

Machine learningBacktestingOptionsEquities
Amberdata research

The article argues that ETH options volatility may offer a long-volatility opportunity despite the historically positive variance risk premium often observed in crypto. It compares ETH and BTC implied and realized volatility, describing ETH’s relative…

CryptoOptionsVolatilityDerivatives pricing
Amberdata research

This market commentary examines crypto options and volatility around the US presidential inauguration, alongside regulatory developments and upcoming economic releases. It argues that Bitcoin’s implied volatility around the event was close to the realized…

CryptoOptionsVolatilityPerpetual futures
NautilusTrader

This technical guide explains how NautilusTrader’s Interactive Brokers adapter connects to Trader Workstation or IB Gateway for market data, order execution, instrument discovery, and historical requests. It covers socket access, paper and live connection…

ExecutionMarket microstructureEquitiesFutures
BigQuant

This report surveys hedging choices for U.S. equity portfolios during drawdowns and recessions, drawing on a historical sample from 1985 through 2018. It contrasts rolling index puts and short credit risk with Treasury and gold exposures, then examines…

EquitiesFuturesOptionsTrend following
SuperMind

This review compares passive and active approaches to protecting U.S. equity portfolios during severe drawdowns and recessions. Its sample covers 1985–2018, including eight equity declines greater than 15% and three U.S. recessions. It discusses rolling S&P…

EquitiesFuturesOptionsTrend following
Lumibot

This documentation explains how to use Polygon as a historical price-data source for LumiBot backtests across stocks, options, forex, and cryptocurrencies. It describes supplying an API key, selecting a backtest date range, and running a simple example…

BacktestingMulti-assetEquitiesOptions
Amberdata research

This market recap reviews BTC and ETH options conditions around ETF-related news. It describes a surge in realized volatility followed by lower implied volatility after the event, and explains that the resulting negative volatility carry is not, by itself, a…

CryptoOptionsVolatilityDerivatives pricing
vn.py community

The article outlines the data requirements for options strategy research: a maintained history of contract details and price bars covering both current and expired contracts. It describes a workflow using a commercial data feed and a local trading database.…

OptionsBacktestingMarket microstructureChina markets
vn.py community

This forum exchange concerns running an options strategy in a SimNow simulated environment. A user reports receiving ticks for the IO options contract but not for the underlying, and says a data subscription call returns false. Participants suggest using IF…

OptionsFuturesExecution
Amberdata research

The article compares Bitcoin market conditions in late 2023 with the rally in late 2020, using spot returns, options implied volatility, futures basis, and realized volatility. It reports that implied volatility was near its 2023 high amid call buying, while…

CryptoOptionsFuturesVolatility
Amberdata research

The document reviews BTC and ETH conditions after a sharp market squeeze, connecting macro uncertainty and price levels with options pricing. It describes falling implied volatility alongside elevated realized volatility, negative carry, changes in term…

CryptoOptionsVolatilitySentiment
Amberdata research

FalconX product manager Jill Gao describes moving from traditional finance into crypto product development and discusses changes in institutional trading. The document outlines Marketspot, a Telegram-based analytics tool that lets users query historical…

CryptoOptionsVolatilityPerpetual futures
Amberdata research

This market commentary combines a US macro calendar with views on Japanese rates, Bitcoin, and Ethereum options. It notes that the Federal Reserve decision and US employment report could move markets, while a weaker employment result might support bonds and…

CryptoOptionsVolatilityForex