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

21,023 documents

Quant Q&A

The document describes the challenge of turning SEC filings into readable balance sheets and income statements. Its author retrieves reported facts for thousands of companies, using filing identifiers and fields such as reporting date, accounting tag, period…

EquitiesStatistics
Quant Q&A

The note asks why fixed-income practitioners use duration times credit spread, often called spread duration times spread, while an equivalent duration-times-yield measure is uncommon. It compares the rationale given for spread duration times spread with the…

Fixed incomeStatisticsRisk management
Quant Q&A

The document derives an inverse covariance matrix for a single-factor CAPM model with a zero risk-free rate. It represents total asset covariance as the sum of a diagonal matrix of idiosyncratic variances and a rank-one market-factor contribution. The…

StatisticsPortfolio constructionRisk management
Quant Q&A

The document considers whether a Libor Market Model volatility function, built from a maturity-dependent linear term multiplied by an exponential and then shifted by a constant, remains bounded. It assumes the parameters and the rate’s maturity are constants…

Fixed incomeVolatilityStatistics
Quant Q&A

The document asks how to interpret a step in a proof involving Gyöngy’s lemma, where an expectation weighted by a Dirac delta at a level is rewritten using an expectation at that level. The response frames the delta as concentrating the contribution on…

Statistics
Quant Q&A

The document explains a change of variables used when writing a likelihood for a linear regression with normally distributed errors. In the stated model, the error is the outcome minus the fitted linear expression. When the predictors and regression…

Statistics
Quant Q&A

The document describes a simulation problem: a researcher wants to compare a trading model’s behavior on ordinary price paths and paths with jumps, while isolating the effect of increased skewness. They can match the mean of the jump process to a geometric…

StatisticsVolatilityBacktesting
Quant Q&A

The document explains that volatility skew and statistical skewness are related terms with distinct meanings. Implied volatility skew describes how option-implied volatility varies across strikes for a fixed expiry; it is observable from option prices after…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document describes simulations using the Gibbons–Ross–Shanken test to evaluate a CAPM-style model across multiple test portfolios. With returns generated under the model, the test does not reject the null; adding nonzero portfolio alphas leads to…

StatisticsFactor investingBacktesting
Quant Q&A

The document raises the problem of converting probabilities inferred from stock option prices under a risk-neutral measure into real-world, or physical, probabilities. Its only proposed method is the Recovery Theorem, named in a brief answer. No derivation,…

OptionsStatisticsDerivatives pricing
Quant Q&A

The document explains how to estimate the probability that an underlying asset reaches an option strike before expiry. It distinguishes this first-passage event from the probability of finishing in the money, noting that option delta is not generally the…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document proposes combining annualized returns measured over several horizons with a weighted mean and weighted standard deviation. It illustrates assigning each horizon a weight that decays exponentially with its length, controlled by a chosen decay…

StatisticsPortfolio construction
Quant Q&A

The document asks how to compare daily five-day volatility estimates for two countries’ benchmark government bonds. Because both series use rolling windows, adjacent observations share most of their underlying price data and are serially dependent. Simply…

Fixed incomeVolatilityStatistics
Quant Q&A

The document addresses whether MATLAB’s one-dimensional interpolation function can produce cubic spline interpolations for yield curve data. The response says that the built-in spline method is suitable for interpolating sampled curve values and identifies…

Fixed incomeStatistics
Quant Q&A

The document asks whether probabilities inferred from derivatives on non-traded variables, such as weather outcomes or central bank rate decisions, represent risk-neutral or real-world beliefs. The responses distinguish pricing measures from objective…

Derivatives pricingFuturesStatistics
Quant Q&A

The document examines a stop-loss style strategy for replicating a call option and asks how its hedging costs relate to the time the underlying spends near the strike. The answer explains the call payoff using the Tanaka-Ito-Meyer decomposition: intrinsic…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document raises a regression-design question: whether to exclude a covariate when it has substantially fewer observations than the other variables. The author gives an example in which one variable has 80,000 observations while others have 100,000, and…

StatisticsMachine learning
Quant Q&A

The document clarifies the dividend-yield convention used in the Goyal and Welch stock return predictability data. The dataset’s dividend yield is computed as aggregate dividends paid by all stocks divided by total stock market capitalization measured at the…

EquitiesStatisticsFactor investing
Quant Q&A

The document explains how prices of European receiver swaptions relate to the risk-neutral distribution of the underlying swap rate. It corrects the idea that an out-of-the-money premium, compared directly with an at-the-money premium, gives the probability…

Fixed incomeOptionsDerivatives pricingStatistics
Quant Q&A

The document addresses whether value at risk remains useful despite shortcomings in how it is sometimes interpreted and its failure to satisfy coherence. It explains that financial institutions use VaR as one component of risk management, often with models…

Risk managementStatistics
Quant Q&A

The document outlines maximum-likelihood estimation for a GARCH(1,1)-M return model under the physical measure, then discusses an implementation problem in an R optimizer. The model specifies conditional returns using a known risk-free rate, an estimated…

StatisticsVolatilityOptionsDerivatives pricing
Quant Q&A

The document concerns noisy, incomplete one-minute price and volume data for several stocks, with the goal of forecasting volatility for the month after the sample ends and investigating whether volatility is related to liquidity. The response recommends an…

High-frequency tradingVolatilityEquitiesStatistics
Quant Q&A

The document asks how investors’ target risk might be chosen in light of wealth, future income, savings, housing, and expected expenses. It contrasts this problem with broad allocation rules and age-based target-date strategies, then proposes a questionnaire…

Risk managementPortfolio constructionStatistics
Quant Q&A

The document poses a one-period binomial market problem with a risk-free asset and a stock that can finish in either an up or down state. It asks how to establish no arbitrage, replicate a claim whose payoff is the squared terminal stock price, calculate the…

Derivatives pricingArbitrageStatistics