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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

12,303 documents

Quant Q&A

The discussion addresses volatility forecasting for financial stocks observed at five-minute intervals and notes that standard ARCH and GARCH approaches may not work as well at this frequency. One response reports that, in a thesis and related literature,…

EquitiesVolatilityMachine learningStatistics
Quant Q&A

The document separates three tasks that are easy to conflate when constructing an option volatility term structure. Implied volatility is inferred by finding the volatility input at which an option-pricing model, such as Black–Scholes, matches the traded…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document asks how to derive the two risk-free rates used in VIX calculations from a table of Treasury yields when the near-term and next-term SPX option series expire on different days. It describes linear interpolation between the 30-day and 60-day…

VolatilityOptionsFixed incomeDerivatives pricing
Quant Q&A

The document asks which barrier options can have negative gamma after the questioner finds positive gamma in the knock-in and knock-out options they examined. One response gives a nearby example rather than a barrier structure: a digital call near its…

OptionsVolatilityDerivatives pricing
Quant Q&A

The note considers why volatility can show long memory and why its measured persistence may vary across periods. It describes an analysis of daily realized volatility for multiple assets, comparing autocorrelations before and after the global financial…

VolatilityStatisticsMarket microstructureTrend following
Quant Q&A

The document derives the probability that a zero-strike spread put finishes in the money. Its payoff is positive when the second asset’s terminal forward price exceeds the first asset’s. Assuming both forwards are lognormally distributed, their log-price…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document examines Monte Carlo estimation of a European call’s delta under the Heston stochastic-volatility model. Its central correction is that the Malliavin weight should use the Brownian component driving the stock that is orthogonal to the…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document proposes simulating equity prices under a constant elasticity of variance model, then pricing European and American options across strikes and maturities. It asks whether implied volatilities inferred from those prices would form the same…

OptionsEquitiesVolatilityDerivatives pricing
Quant Q&A

The document asks whether pairs trading can be applied to related options or to an option and its underlying asset. The proposed idea is to trade a stationary linear combination over short horizons, where changes in delta and time decay may have less…

OptionsPairs tradingStatisticsVolatility
Quant Q&A

The document examines a multi-asset delta-hedging P&L decomposition and asks why a pricing function should satisfy a condition involving a positive break-even covariance matrix. Taylor expansion and delta hedging remove the first-order asset-price terms; the…

OptionsDerivatives pricingVolatilityRisk management
Quant Q&A

The document asks whether a Black-Scholes equation with an issuer credit spread is suitable for pricing an autocallable structured product, and how to examine its Delta, Vega, and hedge. The response advises against using Black-Scholes as the pricing model…

Derivatives pricingOptionsVolatilityRisk management
Quant Q&A

The document discusses which volatility convention to use when deriving forward volatilities from cap prices. Its central point is that the appropriate model depends on the currency and rate environment. For currencies such as EUR or CHF, negative rates and…

Fixed incomeOptionsVolatilityDerivatives pricing
Quant Q&A

The document discusses the familiar claim that higher volatility raises the value of standard American calls and puts, and considers why a formal reference may be hard to find. The response suggests reasoning from the relationship between American and…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document asks for a rigorous basis for a proposed decay-time relationship between diffusion volatility and the effect of lognormally sized Poisson jumps on the final return distribution. It focuses on a claim from a volatility text that relates the…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document raises a comparison between a Fourier-based estimator of realized variance and covariance and the conventional sum of squared returns. The author applies the estimator to one day of ultra-high-frequency observations, samples the data at…

StatisticsVolatilityHigh-frequency trading
Quant Q&A

The document explains a simple way to estimate an option’s future value across a range of underlying prices for a platform-style P&L chart. The proposed baseline is to reprice with Black–Scholes using the remaining time to expiry and a chosen volatility,…

OptionsDerivatives pricingVolatility
Quant Q&A

The question considers how a call’s value might change when stock returns have fatter tails than a log-normal model. It gives a numerical setup with zero interest rate, specified volatility and maturity, and an initial stock price equal to the strike. The…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

This discussion explains how option quotes on a less liquid stock can reflect both the difficulty of hedging in the underlying and the flow of customer orders. Market makers account for hedge liquidity in their bid–ask spreads and implied volatility, so…

OptionsMarket makingVolatilityMarket microstructure
Quant Q&A

The document asks how selecting an iron condor’s short strikes by option delta relates to changes in implied volatility. The central question is whether choosing a target delta makes the spread width adjust as volatility changes, even though the distance…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document considers the reciprocal of a stock price modeled by geometric Brownian motion (GBM). It gives the standard GBM solution and uses the moment-generating identity for a Gaussian variable to derive the reciprocal’s mean. For initial price S₀, drift…

StatisticsVolatilityBacktesting
Quant Q&A

The document examines whether a basic Kalman update can estimate both the evolving mean and the variability of a price series. It presents a recursive mean update using the Kalman gain, with a filtered state variance that shrinks when the gain is below one.…

StatisticsTechnical indicatorsVolatility
Quant Q&A

The document asks which implied volatility surface should serve as the target when calibrating the leverage function in a stochastic-local volatility model. It describes a two-stage setup: first calibrate pure Heston parameters, then fit the leverage…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document explains an apparent asymmetry in simulated currency prices generated from a GARCH model. The model is fitted to log returns, which may have a symmetric innovation distribution, but the simulation is transformed back into price levels by…

ForexVolatilityStatisticsMachine learning
Quant Q&A

The document asks how quickly simulated asset paths converge under a Milstein discretization of the Heston stochastic volatility model. It gives the coupled stochastic differential equations for the asset price and variance, including mean reversion in…

OptionsVolatilityStatistics