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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
Quantpedia
86 documents
TqSdk
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

8,116 documents

Quant Q&A

The document discusses why a basic Euler simulation of the Heston stochastic volatility model may fail to reproduce a volatility surface and run slowly. Suggested approaches include the QE-M scheme, Milstein discretization, more simulation paths, and…

OptionsVolatilityDerivatives pricingBacktesting
Quant Q&A

The document asks why rough Heston calibration or neural-network approximation may use the Hurst parameter, correlation, volatility of volatility, and forward variance, while leaving out mean reversion, initial variance, and long-run mean variance as…

OptionsVolatilityDerivatives pricingMachine learning
Quant Q&A

The document explains why Hull–White interest-rate model calibration often fixes mean reversion while fitting volatility. With mean reversion held constant and volatility represented as a stepwise or piecewise-linear function, volatility can be bootstrapped…

Fixed incomeOptionsVolatilityDerivatives pricing
Quant Q&A

The document offers possible undergraduate research directions related to the VIX and the newer SPIKES index. Suggestions include examining whether the VIX and its futures serve their intended purpose, what a theoretically sound volatility product might look…

VolatilityOptionsFuturesDerivatives pricing
Quant Q&A

The document asks how a broker might price European options on an index that has no readily available listed option market. The trader has options at several strikes with a shared expiry, while the broker appears to use a volatility surface and a market data…

OptionsVolatilityDerivatives pricing
Quant Q&A

The question asks how to attribute an option price change between time decay and a change in implied volatility, using a call whose underlying rises while the option loses a small amount of value. It supplies hypothetical theta and vega figures, but the…

OptionsVolatilityDerivatives pricing
Quant Q&A

This exchange clarifies why an implied volatility surface built using forward information may still display its moneyness against spot. The questioner expects the at-the-money volatility node to correspond to the implied forward strike, but observes a…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document clarifies how Fourier inversion produces the two probabilities used in a European call valuation under the Heston model. The bond-numeraire probability is obtained by inverting the risk-neutral characteristic function of terminal log price. The…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document addresses which interest rate to use when pricing a long-dated European option on a USD stock with Black–Scholes. It recommends using a risk-free rate swap curve, such as the USD SOFR curve, rather than choosing a Treasury yield or the overnight…

OptionsDerivatives pricingFixed incomeUS markets
Quant Q&A

The document explains that a probability density inferred from a continuum of European call prices is risk-neutral rather than a forecast of the real-world distribution. Under the risk-neutral measure, a call price is the discounted expected payoff. Applying…

OptionsDerivatives pricingStatistics
Quant Q&A

The document examines why a one-step binomial call value differs from a Black–Scholes value when both are applied to a stock that can move up or down over one day. Its main method is to match the first two moments of the binomial log return to the…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document raises a conceptual question about whether implied standard deviation can be treated as an estimate of volatility under the risk-neutral measure. It also asks whether derivatives whose underlying variable is implied standard deviation can be…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document considers whether short gamma, commonly associated with selling options, is inherently a losing strategy. Its response distinguishes cash-secured put writing from leveraged, uncovered option selling: collateral can limit losses to the invested…

OptionsVolatilityRisk managementPosition sizing
Quant Q&A

The document asks how to interpret the mean and standard deviation of a risk-neutral density inferred from one-week AMD options using the Breeden-Litzenberger result. It treats the discounted density’s expected underlying price as a forward-price estimate…

OptionsDerivatives pricingVolatility
Quant Q&A

The document explains why there is no fixed number of Monte Carlo simulations that reliably prices every European call. Required sample size depends on inputs such as the interest rate, volatility, strike, maturity, and initial asset price, as well as the…

OptionsDerivatives pricingStatisticsBacktesting
Quant Q&A

The post asks whether rising options open interest is generally associated with more trading in the underlying asset. One answer cites an older study reporting increases in market depth, volume, trade size, and trade frequency, along with narrower spreads.…

OptionsMarket microstructureStatistics
Quant Q&A

The document raises implementation questions about sticky-strike and sticky-delta assumptions in options hedging. These assumptions describe how implied volatility is treated as spot moves, and therefore affect the relationship between spot changes and…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The discussion explains why continuously or frequently delta hedging a fairly priced option does not, by itself, create expected profit. For a short call, the hedge offsets directional exposure while leaving the trader exposed to the relationship between…

OptionsDerivatives pricingVolatilityMarket making
Quant Q&A

Knowing the mean of a random variable and the expectations of its positive and negative parts does not, in general, determine the expectation of an arbitrary twice differentiable payoff. For a positive lognormal variable, the positive-part expectation equals…

OptionsDerivatives pricingStatistics
Quant Q&A

The document asks how to estimate the strike and maturity derivatives needed to apply the Dupire equation to a dense, arbitrage-consistent grid of option prices. It raises central finite differences as a possible approach, with small bumps in maturity and…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document explains why a put option on an underlying that cannot fall below zero cannot be worth more than its strike. At the lowest possible underlying value, the put payoff reaches the strike; because the option’s value is based on possible discounted…

OptionsDerivatives pricingCommoditiesFixed income
Quant Q&A

The document compares practical ways to infer volatility from American option prices on dividend-paying stocks. Its favored market approach, called de-Americanization, prices each American option with a model that accounts for dividends and early exercise,…

OptionsVolatilityDerivatives pricingMarket microstructure
Quant Q&A

The question concerns the interpretation of equity option volatility skew: why a heavy left tail in the risk-neutral distribution can be described as shifting probability mass toward higher stock prices, rather than simply increasing the chance of low…

OptionsVolatilityDerivatives pricingStatistics