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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

8,116 documents

Quant Q&A

The discussion clarifies two meanings of an option’s initial hedging investment in a Cox-Ross-Rubinstein binomial model. The portfolio’s initial value is the option’s fair price, expressed as the stock position times the initial stock price plus the bond…

OptionsDerivatives pricingRisk managementStatistics
Quant Q&A

The answer explains that a known characteristic function makes Fourier-based pricing and calibration efficient for many affine stochastic-volatility and Lévy models. It contrasts these with models that lack a known characteristic function, which can still be…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document offers an intuitive account of how patterns in out-of-the-money put implied volatility may relate to local volatility across stock levels and maturities. One response describes a forward line as the path of forward levels across expiries and…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document asks how to strengthen a lower bound for an American call when a stock pays two discrete dividends before expiration. It starts from a basic bound using the stock price, the present value of dividends, and the discounted strike. It then adds…

OptionsEquitiesDerivatives pricingStatistics
Quant Q&A

The document examines whether an at-the-money American call on a dividend-paying stock should be exercised before the ex-dividend date, then considers an arbitrage when the quoted call price is below a theoretical lower bound. It explains that the stock…

OptionsEquitiesArbitrageDerivatives pricing
Quant Q&A

The document explains why increasing volatility of variance in the Heston model can lower the at-the-money implied volatility level across maturities even while making each maturity’s smile more curved. It uses the expected integrated variance, expressed as…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document addresses valuation of a variance swap observed from a current date when realized variance is computed from daily closing-price returns. It points to several replication-based approximations for discrete variance swaps, including continuous…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document asks how the rough Heston volatility equation relates to empirical evidence that changes in log volatility behave like increments of fractional Brownian motion with a Hurst parameter below one half. It presents the rough Heston variance as a…

VolatilityOptionsStatistics
Quant Q&A

The document raises questions about the forward implied variance defined in a volatility modeling treatment. The quantity is expressed as a ratio of conditional expectations weighted by the Black–Scholes gamma, while the average implied volatility over the…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document addresses questions that arise when applying a finite difference method to a basket option under the Black–Scholes framework. A principal component transformation rotates log-price coordinates using the eigenvectors of the covariance matrix,…

OptionsDerivatives pricingStatistics
Quant Q&A

The document asks how the Breeden–Litzenberger relationship connects call option prices across strikes to prices of state-contingent claims. It presents a finite-difference expression built from calls at a central strike and nearby strikes, then asks why the…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document discusses how practitioners might measure time to expiry when valuing commodity options on futures. It frames the choice between calendar-day and business-day conventions as dependent on how theta is accumulated and how volatility estimates…

CommoditiesOptionsVolatilityDerivatives pricing
Quant Q&A

The document discusses how to deepen study of path-dependent options in a partial differential equation framework. It recommends using Wilmott’s quantitative finance text as an accessible foundation, while adding practical finite-difference methods and…

OptionsDerivatives pricingVolatility
Quant Q&A

Calibration frequency for stochastic volatility models depends on the model and market, rather than following one fixed schedule. The answer illustrates this with SABR, separating parameters according to how quickly they are typically updated. The initial…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document surveys ways to represent implied volatility across strikes at a fixed maturity, while emphasizing that the data do not define one unique curve. Different choices of bid, ask, midpoint, and option type produce distinct curves, so the fitted…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document asks whether a trader who buys options based on a view that realized volatility will exceed implied volatility should delta hedge using fixed or changing implied volatility. It introduces a Greek-based P&L decomposition and the familiar…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The document explains how to estimate historical volatility for comparison with option implied volatility under the Black–Scholes framework. Assuming geometric Brownian motion, log returns have variance that grows with time, so the answer recommends…

OptionsVolatilityStatistics
Quant Q&A

The document explains how to price a European call spread in a two-period binomial model and find the portfolio that replicates it. A call spread is treated as a long call at the lower strike and a short call at the higher strike. The method assigns the…

OptionsDerivatives pricingStatistics
Quant Q&A

The document considers whether retail investors can hedge severe equity-market declines by buying deep out-of-the-money index puts, how to size and roll such positions, and whether a packaged product may be easier to use. The replies caution that repeatedly…

OptionsRisk managementVolatilityPortfolio construction
Quant Q&A

The document explains why over-the-counter vanilla options are commonly quoted using delta and implied volatility rather than option premium. Delta identifies an option in a way that supports communication across counterparties: a 25-delta call can be…

OptionsVolatilityDerivatives pricingMarket microstructure
Quant Q&A

The document considers whether dynamically delta-hedging a call can generate gamma profits when the underlying stock has positive drift but zero volatility. Its answer applies the Black–Scholes setting’s no-arbitrage condition: a riskless stock must grow at…

OptionsEquitiesDerivatives pricing
Quant Q&A

The document discusses finding an importance sampling drift that minimizes the variance of a least squares Monte Carlo estimate. It defines an objective as the second moment of a weighted payoff and gives an expression for its gradient. The proposed…

StatisticsOptionsBacktesting
Quant Q&A

The document asks why a Black-Scholes derivation for a dividend-paying underlying includes dividends in the change of a delta-hedged portfolio but omits them from the portfolio's risk-free return equation. The included answer separates these steps: dividend…

OptionsDerivatives pricingRisk management
Quant Q&A

The document derives a European call pricing approach when the logarithm of the underlying price follows a mean-reverting stochastic process. It first obtains the conditional distribution of the future price and the corresponding futures price, then uses the…

OptionsDerivatives pricingVolatility