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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

1,747 documents

FMZ forum

The article proposes modifying a range-trading grid to generate trading volume, aimed at market makers or traders seeking lower fees. It describes using maker orders to add positions as price falls, then closing profitable positions after a larger rebound…

Grid tradingMarket makingExecutionRisk management
Hyperliquid docs

The document explains how Hyperliquid validators produce spot oracle prices for perpetual futures assets. Validators publish prices every three seconds. Each validator calculates an asset price as a weighted median of spot mid prices from Binance, OKX,…

CryptoPerpetual futuresMarket microstructureRisk management
Amberdata research

This article recounts BitMEX’s development and describes exchange mechanics relevant to crypto derivatives traders. It discusses perpetual swaps and their funding mechanism, liquidation when maintenance margin is insufficient, and an insurance fund intended…

CryptoDerivatives pricingPerpetual futuresMarket making
Amberdata research

The document explains how crypto perpetual futures differ from dated futures. Perpetual contracts have no expiry or rollover, so exchanges use funding payments between long and short holders to encourage the futures price to track spot. When the contract…

CryptoPerpetual futuresRisk managementPosition sizing
FMZ live strategies

This live-robot snapshot scans perpetual futures across Binance, GateIO, and OKX for differences in funding rates. It pairs a short position on the venue with the higher funding rate and a long position on the venue with the lower rate, then reports…

CryptoFuturesArbitrageCarry
Amberdata research

This weekly crypto market report examines a Bitcoin-led selloff through prices, volatility, trading volume, derivatives positioning, ETF and stablecoin flows, orderbook liquidity, and DeFi activity. It describes falling open interest alongside price weakness…

CryptoPerpetual futuresVolatilityMarket microstructure
Hyperliquid docs

This support note briefly describes how assets become available on Hyperliquid. Spot token deployments are permissionless, while perpetual market listings are based on community requests and organic demand. It points readers to the platform’s native token…

CryptoSpot marketsPerpetual futuresMarket microstructure
Amberdata research

This derivatives newsletter interprets Bitcoin options and futures positioning in the week before a US PCE release and developments in the 2024 election campaign. It reports a rise in implied volatility relative to realized volatility, a week-over-week…

CryptoOptionsPerpetual futuresVolatility
FMZ forum

This strategy modifies a two-way martingale by opening a position against the current exposure when price reaches a configurable hedge threshold. It describes settings for initial order size, take-profit distance, leverage, position growth, and the…

CryptoGrid tradingPosition sizingRisk management
NautilusTrader

This example configures a built-in execution tester for an ETH-USD perpetual market on dYdX. On startup, it can open a position with an immediate-or-cancel order, then maintain post-only limit buy and sell quotes offset from the top of book. It subscribes to…

CryptoPerpetual futuresExecutionMarket microstructure
FMZ forum

This article describes a cash-and-carry approach to crypto perpetual futures: hold spot while shorting a matching perpetual position to collect funding when the rate is positive. It explains that funding payments help keep perpetual prices near spot, and…

CryptoArbitragePerpetual futuresSpot markets
FMZ forum

This document is a reference table of reported fees and fee-page locations for numerous cryptocurrency exchanges, covering spot markets and several derivatives venues. Some entries state maker and taker rates or broad fee estimates; others refer to linked…

CryptoMarket microstructureExecutionPerpetual futures
OctoBot

This OctoBot guide outlines how to configure automated futures trading. It lists supported trading modes: DCA, Dip Analyser, TradingView, and Daily. It names Binance, Bybit, and Kucoin as supported futures exchanges. A profile's leverage setting is adjusted…

FuturesPerpetual futuresExecutionRisk management
FMZ forum

The document describes a crypto futures strategy that combines ATR-based channel signals with Avellaneda–Stoikov quoting. It treats a move above the upper band as a short signal and a move below the lower band as a long signal, while quotes are adjusted for…

CryptoFuturesMean reversionMarket making
Hyperliquid docs

The document explains how Hyperliquid account abstraction modes determine whether spot and perpetual-futures balances share collateral. Unified accounts combine balances by asset across spot and eligible cross-margin positions. Portfolio margin pools…

CryptoPerpetual futuresRisk managementPortfolio construction
NautilusTrader

This tutorial describes running a shared short volatility strategy on Derive. It selects an out-of-the-money ETH call and put at the nearest expiry, tracks venue supplied option Greeks, and offsets net portfolio delta with ETH perpetual orders when exposure…

CryptoOptionsVolatilityPerpetual futures
FMZ live strategies

This live strategy dashboard describes a multi-asset perpetual futures system that combines factor signals, assigns target exposures across contracts, and submits passive limit orders. The listed seed factors cover reversal, momentum, premium, funding, and…

CryptoPerpetual futuresMachine learningPortfolio construction
Amberdata research

This podcast recap describes Push Protocol as a cross-chain communication layer for Web3 applications, wallets, and users. Its notification use cases include alerting traders to margin and leverage conditions on a derivatives venue, informing liquidity…

CryptoDeFiOn-chain dataPerpetual futures
FMZ live strategies

This live strategy listing describes a cycle-reversion approach with position compounding across several Binance crypto futures markets. The page identifies a one-hour chart period and says the strategy runs on a repeating schedule several times per day,…

CryptoFuturesMean reversionPosition sizing
Quant Q&A

The document explains the role of a fixed interest component in perpetual futures funding. Funding combines a premium component with an interest-rate component, and its broader purpose is to encourage perpetual prices to track spot prices. The premium…

Perpetual futuresFuturesSpot marketsArbitrage
Quant Q&A

The document suggests market data to consider when forecasting a crypto asset, using Bitcoin as an example. For perpetual futures, it points to the contract’s pricing mechanism, including funding rules, funding intervals, and the related spot price. These…

CryptoPerpetual futuresMarket microstructureMachine learning
Quant Q&A

The document examines how to calculate average entry price while backtesting positions in perpetual swap contracts, focusing on inverse contracts whose value is denominated in cryptocurrency. A simple harmonic-style average of execution prices can fail when…

CryptoPerpetual futuresDerivatives pricingBacktesting
Quant Q&A

The document describes the difficulty of hedging a spread between inverse futures contracts with different maturities. The author notes that the contract exposure is nonlinear and sensitive to both spot prices and interest rates. They compare several hedge…

FuturesPerpetual futuresDerivatives pricingRisk management
Quant Q&A

The document outlines an Avellaneda–Stoikov market-making setup for perpetual futures. It gives a reservation price adjusted for inventory, volatility, time remaining, and an expected funding payment, then places bid and ask quotes symmetrically around that…

Perpetual futuresMarket makingDerivatives pricingRisk management