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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
WonderTrader
14 documents
Alphalens
14 documents
backtesting.py
11 documents
Technical Analysis
9 documents
QTPyLib
8 documents
Lumibot strategies
7 documents
QuantRocket
7 documents
Awesome Quant
1 documents

Search the library

12,303 documents

Quant Q&A

The document discusses how to express the Heston stochastic volatility pricing equation using a forward price, log-moneyness, time to expiry, and an undiscounted option value. It gives the spot and variance processes, their correlated Brownian shocks, and a…

OptionsVolatilityDerivatives pricingFixed income
Quant Q&A

The document explains why the Black–Scholes delta of an in-the-money call can first decline and later increase as volatility rises. Interpreting delta as the risk-neutral probability of exercise, it separates two effects: greater volatility makes the strike…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document discusses how to convert daily US Treasury volatility to an hourly measure and cautions against assuming that trading activity is evenly distributed across the full day. Treasury trading is described as over the counter, without official…

Fixed incomeVolatilityUS markets
Quant Q&A

The document explains how to find the probability mass under a normal distribution between a lower and upper bound. It uses the cumulative distribution function (CDF), which gives the accumulated probability from negative infinity up to a chosen value.…

StatisticsOptionsVolatility
Quant Q&A

The note explains how delta-hedging error arises when an option is valued using an assumed volatility that differs from the underlying asset's true volatility. The option's Black–Scholes pricing equation links its theta to its price, delta, gamma, interest…

OptionsDerivatives pricingRisk managementVolatility
Quant Q&A

The note asks why options on leveraged exchange-traded funds can appear cheaper than options on an unleveraged fund tracking the same index and expiry, despite an expectation that leverage should multiply implied volatility. It explains that a daily…

OptionsEquitiesVolatilityDerivatives pricing
Quant Q&A

The document compares two numerical approaches for pricing European calls under the Heston–Nandi GARCH model using an inversion integral. One implementation evaluates the integrand through adaptive quadrature, while another precomputes…

OptionsVolatilityDerivatives pricingBacktesting
Quant Q&A

The post asks how to select conditional-mean terms when fitting GARCH-family models to South African, Australian, and US equity index returns. The author compares autocorrelation plots, information criteria, ARCH tests, and the significance of terms in…

EquitiesVolatilityStatisticsBacktesting
Quant Q&A

The document explains why jump intensity cannot be interpreted independently of the assumed jump-size distribution. To estimate a model’s jump frequency, it recommends fitting intensity and the other model parameters jointly, using maximum likelihood or…

StatisticsVolatilityDerivatives pricing
Quant Q&A

The document investigates how to reproduce CBOE’s discontinued single-name 30-day normalized skew field using historical options data. It describes the target as the 25-delta put implied volatility minus the 25-delta call implied volatility, divided by…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The example shows how put-call parity and relationships across option strikes can be used to infer some option prices from quoted market data. Ignoring discounting, the response applies parity at the 70 strike to the given futures level and straddle price,…

OptionsDerivatives pricingVolatility
Quant Q&A

The document explains how options systems represent time remaining on expiration day. Rather than using whole-day buckets, pricing and risk software generally represents expiry tenors fractionally and may measure time internally in years, seconds, or…

OptionsDerivatives pricingMarket makingVolatility
Quant Q&A

The document poses a pricing problem for a path-dependent option on a geometric Brownian motion asset. Its European payoff depends on the running maximum and a time-averaged quantity formed from the integral of the squared asset price. The question asks how…

OptionsDerivatives pricingVolatility
Quant Q&A

The document asks whether the effective parameters in a time-decay SABR model can be expressed by one closed-form formula across all values of the decay start time. It presents two results from Sander Willems’s backward-looking SABR work: one for decay…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document explains that there is no standard rule for how many past days to use when estimating historical volatility. It distinguishes historical, or realized, volatility from implied volatility: option prices reflect the market’s view of future…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The note explains that options on volatility control indexes exist, even though they may not appear as exchange-listed contracts. It says these options are generally embedded in structured notes and are mainly traded over the counter. This provides a reason…

OptionsVolatilityDerivatives pricingMarket microstructure
Quant Q&A

The note discusses numerical instability when using the Bjerksund–Stensland 2006 option pricing model at very low volatility, especially when solving for implied volatility on out-of-the-money options. It offers a practical parameter choice: use a minimum…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document describes calculating Black–Scholes delta and vega in R for a sample of executive compensation contracts containing multiple options. The author derives the Black–Scholes call sensitivities and reports that computed vega values are zero,…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document asks how practitioners estimate equity volatility surfaces when listed option prices are scarce or unavailable. The answer describes a market-based approach rather than a formal model: index volatility is informed by active interdealer markets,…

OptionsVolatilityDerivatives pricingMarket microstructure
Quant Q&A

The document describes a question about measuring volatility for five equal-weighted portfolios drawn from S&P 500 constituents and grouped by ESG ratings. Constituents are updated monthly as index membership changes, while ESG group assignments are…

EquitiesVolatilityPortfolio constructionStatistics
Quant Q&A

The document raises a notation question about up-and-out and down-and-out call payoffs. It defines the terminal call payoff using the strike and multiplies it by an indicator based on whether the price path remains on the permitted side of a barrier. The…

OptionsDerivatives pricingVolatility
Quant Q&A

The document examines why paired leveraged and inverse ETFs can have different daily returns even when their stated goals are equal and opposite multiples of an index’s daily performance. It distinguishes the index level, the fund’s net asset value based on…

EquitiesRisk managementVolatilityExecution
Quant Q&A

The document raises a practical question about maintaining a long volatility hedge by rolling spot variance swaps monthly. It describes replicating spot VIX with a portfolio of out-of-the-money calls and puts, weighted by the inverse square of each strike,…

VolatilityOptionsDerivatives pricingRisk management