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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

21,023 documents

Quant Q&A

The document addresses whether squared simple returns or squared log returns should be used when studying volatility and applying ARCH or GARCH models. It defines log returns as the difference between the logarithms of consecutive prices and says this is the…

EquitiesVolatilityStatistics
Quant Q&A

The document compares holding a high-coupon bond bought just after a coupon payment with buying it shortly before the next payment. With the same clean price and a hold to maturity, the earlier purchase also pays accrued interest, while the next coupon…

Fixed incomeStatistics
Quant Q&A

The document describes constructing a synthetic futures price at a target maturity by linearly interpolating between two listed contracts whose expiries fall on either side of that target. The weights depend on how far the target lies between the shorter and…

FuturesCommoditiesStatisticsRisk management
Quant Q&A

This discussion points readers to examples of Kalman filtering in finance, including an application to the Kyle model and a pricing framework for spot and futures markets. In the Kyle setting, a market maker updates an estimate of an asset’s final value as…

EquitiesFuturesMarket microstructureStatistics
Quant Q&A

The document describes an analysis of daily returns for eleven MSCI World sectors and the MSCI ACWI index. The analyst groups daily observations into weekly and monthly periods, calculates a correlation for each group, and applies the Augmented Dickey-Fuller…

EquitiesStatisticsBacktesting
Quant Q&A

The document considers a market with one homogeneous good, multiple buyers and sellers, capacity limits, willingness-to-pay and reservation-price bounds, and utility functions. It outlines two standard game-theoretic formulations: Cournot competition, where…

Market microstructureStatistics
Quant Q&A

The document explains why mean-variance optimization can assign nearly all capital to one asset as the asset universe grows. Its account centers on covariance structure: many assets share a small number of meaningful risk factors, leaving other variance…

Portfolio constructionRisk managementStatistics
Quant Q&A

The document explains why the yield spread between a corporate bond and a risk-free bond cannot be read as a default probability on its own. The spread reflects expected default losses, including both the chance of default and the loss given default;…

Fixed incomeRisk managementStatistics
Quant Q&A

The document considers how to assess bid, ask, and volume data from two vendors when observations do not share exact timestamps. The questioner samples prices at regular time intervals, finds that plots look similar, but sees weak cross-correlation after…

Market microstructureStatisticsBacktestingExecution
Quant Q&A

The document examines the relationship between required returns, variance, stock-index levels, and expected volatility measures. The response points to a decomposition of the market’s expected excess return that includes risk-neutral variance and additional…

OptionsVolatilityStatistics
Quant Q&A

The document explains an inflation hedge in terms of how an asset’s return responds to inflation surprises, rather than whether its total return exceeds the inflation rate in a particular period. It presents a regression framework in which an asset’s excess…

EquitiesStatisticsRisk management
Quant Q&A

The document asks how to bootstrap spot and forward curves from daily US Treasury yields when a coupon bond’s cash flows fall at maturities without quoted securities. For the two-year note, the missing one-and-a-half-year spot rate is needed alongside…

Fixed incomeUS marketsStatistics
Quant Q&A

The document examines how to annualize a cumulative return when capital was invested during separated intervals. It contrasts annualizing over the 450 days actually invested with annualizing over the full three-year span. The responses distinguish a…

StatisticsBacktestingPortfolio construction
Quant Q&A

The document clarifies the scope of the Gordy formula as described through its underlying asymptotic single-risk-factor credit model. The model represents an entity at the horizon as either performing or defaulted, and recognizes a monetary loss when default…

Fixed incomeRisk managementStatistics
Quant Q&A

The document considers whether official central bank exchange rate fixings can stand in for end-of-day spot forex data in lower-frequency analysis. The response points to the European Central Bank’s daily exchange rate series, noting that its rates are fixed…

ForexStatisticsBacktesting
Quant Q&A

The document responds to an observation that volatile Bitcoin prices seem to form a Weierstrass-like pattern across candlestick time scales. It explains that rough, fractal-like paths are not unique to cryptocurrency: Brownian motion and related stochastic…

CryptoStatisticsVolatilityMean reversion
Quant Q&A

The note addresses whether an information ratio should use average monthly returns or cumulative monthly returns. Its answer recommends dividing the average monthly return by the standard deviation, pointing readers to an external response for further…

StatisticsPortfolio construction
Quant Q&A

The document discusses how to identify common risk factors in private markets when asset prices are infrequently observed or unavailable. One suggested route is to describe companies using observable characteristics such as industry, business relationships,…

Fixed incomeStatisticsRisk managementPortfolio construction
Quant Q&A

The document asks how to choose a probability measure when pricing derivatives with Monte Carlo simulation. It starts from risk-neutral valuation, where price is the discounted expected payoff, and notes that simulations may require modeling state variables…

Derivatives pricingFixed incomeStatisticsBacktesting
Quant Q&A

The document poses an inverse pricing problem: fitting a Black–Scholes model to binary option prices observed across strike prices when the time to maturity, volatility, risk-free rate, and underlying price are all unknown. The stated goal is to predict…

OptionsDerivatives pricingStatistics
Quant Q&A

The document presents a derivation of the CAPM by treating the market portfolio as a portfolio on the capital allocation line that maximizes the Sharpe ratio. Under the assumption that investors choose mean–variance efficient portfolios, individual holdings…

StatisticsPortfolio constructionRisk management
Quant Q&A

The document distinguishes the Samuelson effect’s maturity-related volatility pattern from volatility measured directly on futures price levels. The effect concerns returns volatility: nearby commodity contracts are often more volatile than deferred…

CommoditiesFuturesVolatilityStatistics
Quant Q&A

The document explains how to obtain the Radon–Nikodym derivative when changing from a probability measure associated with numeraire M to one associated with numeraire N. The derivation uses the martingale property of asset prices expressed in units of the…

Derivatives pricingStatistics