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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

19,452 documents

Quant Q&A

The note explains how collateral and funding payments relate to liquidation in perpetual futures. In the answer’s account, a position is liquidated when collateral falls below the maintenance margin. Collateral includes the amount initially posted, realized…

CryptoFuturesPerpetual futuresRisk management
Quant Q&A

The document presents an eGARCH(1,1) fit to weekly Bitcoin log returns over a multi-year sample, using a generalized error distribution and a date-related dummy variable. The broader research aim is to compare volatility dynamics across Bitcoin, Ethereum,…

CryptoVolatilityStatisticsRisk management
Quant Q&A

The document considers whether EUR/USD returns can serve as the market benchmark when applying CAPM to Bitcoin returns. Its response treats Bitcoin as a currency for this purpose and suggests constructing a broader currency-market proxy by averaging returns…

CryptoForexStatistics
Quant Q&A

The question concerns regressions linking Bitcoin prices with daily Reddit post counts and sentiment. The author reports that price appears integrated while the social measures appear stationary, yet the series show strong correlation, high regression fit,…

CryptoStatisticsMachine learning
Quant Q&A

The document surveys research on whether cryptocurrencies differ quantitatively from currencies and other assets. It describes proposed distinctions such as decentralized transaction records, market-specific drivers, high volatility, and limited history. The…

CryptoMulti-assetMomentumVolatility
Quant Q&A

The document clarifies a market interpretation of declining open interest in long Bitcoin futures positions. The question asks how closing futures longs could limit further declines in Bitcoin, given that futures are often viewed as bets on the underlying…

CryptoFuturesMarket microstructureSentiment
Quant Q&A

The document asks how to implement the adapted Roll measure attributed to Easley and coauthors using daily cryptocurrency OHLCV data. Its main questions concern the meaning of lagged price changes such as ΔP at t−w and t−w+1, whether the lookback window W is…

CryptoStatisticsMarket microstructure
Quant Q&A

The document considers whether cryptocurrency market conditions such as low volume, high volatility, or market immaturity might allow intra-exchange triangular arbitrage gaps to persist long enough for an API-based strategy. It asks whether traders can…

CryptoArbitrageMarket microstructureExecution
Quant Q&A

The document considers how to validate a low-frequency crypto strategy with roughly 25 trades per year, focusing on the limits of statistical evidence from a small sample and the dependence introduced by adding correlated assets. One reply suggests extending…

CryptoStatisticsBacktestingMachine learning
Quant Q&A

The document outlines a variance-covariance approach to estimating volatility for a portfolio of cryptocurrencies. It starts from daily price changes, forms a covariance matrix of daily returns, and scales that matrix by 365 to estimate annual variance,…

CryptoStatisticsVolatilityPortfolio construction
Quant Q&A

The document collects operational safeguards for an automated trading script interacting with an exchange API. The proposed controls include prioritizing exits and stop orders, checking whether orders reached the venue, handling failed requests, monitoring…

ExecutionRisk managementMarket microstructureCrypto
Quant Q&A

The document explores whether financial asset fungibility is an all-or-nothing property or can depend on selected attributes. It uses hypothetical digital currency tokens to illustrate how issuer, currency symbol, decimal precision, and encumbrances might…

Fixed incomeMarket microstructureCrypto
Quant Q&A

The document clarifies how open interest changes when futures positions are opened or closed, including a question framed around crypto exchanges. Open interest counts outstanding contracts, with each contract having both a buyer and a seller. It does not…

FuturesCryptoMarket microstructure
Quant Q&A

The document explains why a candle can be green even when its close is below the previous candle’s close. In a common solid-candle convention, color compares the period’s close with its own open: green indicates the price rose during that interval, while red…

Technical indicatorsCrypto
Quant Q&A

The document raises a pricing question about crypto options: whether a reported discount rate around 10% is unusually high, and whether observed option quotes imply a rate near 12% when checked against put-call parity. It presents bid and ask snapshots for…

CryptoOptionsDerivatives pricingArbitrage
Quant Q&A

The document sets out proposed formulas for Bitcoin’s Pi Cycle top and bottom indicators and asks whether the inequalities are stated correctly. The top condition compares a 111-day simple moving average with twice a 350-day simple moving average. The bottom…

CryptoTechnical indicatorsStatistics
Quant Q&A

The discussion considers how to estimate an option implied volatility surface when the target asset has spot history but no option data, while related assets have observable option surfaces. It presents break-even volatility, or fair skew, as a way to infer…

VolatilityDerivatives pricingOptionsStatistics
Quant Q&A

The document considers whether historical futures data from one crypto exchange can support backtests for a strategy traded on another. The motivating issue is a change in listed contracts that leaves little history for the replacement market, prompting the…

CryptoFuturesBacktestingExecution
Quant Q&A

The document examines a SABR calibration on Ethereum option data where the fitted alpha parameter changes substantially when strikes and the forward are expressed at a different scale, even though the implied volatilities are unchanged. The questioner…

OptionsVolatilityDerivatives pricingCrypto
Quant Q&A

The document examines why maximum-likelihood estimates for an exponential Hawkes process can drive the decay rate and excitation parameter toward very large values when tick records share millisecond timestamps. In the stated likelihood recursion, zero…

High-frequency tradingMarket microstructureStatisticsCrypto
Quant Q&A

The document compares holding a cryptocurrency investment for a fixed period with periodically withdrawing gains while restoring the original principal. It describes a Monte Carlo example using simulated daily returns, then reports average outcomes for both…

CryptoMean reversionVolatilityBacktesting
Quant Q&A

The document collects suggestions for software and services that can be used to backtest investment strategies. The examples span a mobile portfolio tool, a Python framework, a form based service, standalone engines, and a brokerage platform with strategy…

BacktestingEquitiesFuturesForex
Quant Q&A

The document explains why exchanges may not provide idempotency for market orders and describes client-side checks to reduce accidental duplicates. It compares strict matching of past requests, order throttles, checks of consecutive or recent duplicate…

CryptoExecutionRisk managementMarket microstructure
Quant Q&A

The document defines a stochastic reserve system in which a fund backs liabilities and a solvency ratio scales an issuance adjustment. The adjustment grows with the square of the ratio up to a cap, while reserve inflows, outflows, and shocks drive changes in…

Risk managementStatisticsCrypto