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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
Lumibot strategies
7 documents
QuantRocket
7 documents
Awesome Quant
1 documents

Search the library

12,303 documents

Quant Q&A

The document compares two ways to estimate the distribution of an hour of USDJPY one-minute returns: repeatedly convolving an empirical histogram and Monte Carlo sampling sums of 60 observed moves. The simulated sums produce a wider distribution, while the…

ForexStatisticsVolatilityBacktesting
Quant Q&A

The question examines whether an American option on a deterministic, zero-volatility asset can have time value. Its proposed reasoning treats the option’s value as the best payoff reached along the asset’s deterministic path and argues that early exercise…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document asks how to estimate portfolio volatility when each of two assets has an exponentially weighted variance estimate. The central guidance is to calculate correlation using the same weighting convention as the variances. Applying common weights to…

StatisticsVolatilityPortfolio constructionRisk management
Quant Q&A

The discussion distinguishes independent increments from dependence on the current state and from correlated increments. It notes that Wiener motion has independent increments, while geometric Brownian motion’s price changes scale with the current price; the…

StatisticsVolatilityEquitiesFixed income
Quant Q&A

The document addresses the claim that small-cap stocks are more volatile than large-cap stocks and suggests comparing the standard deviations of their returns, a common measure of volatility. It gives an illustrative comparison between a large-cap market ETF…

EquitiesVolatilityStatistics
Quant Q&A

The note explains how to interpret transition parameters from a three-state Markov-switching GARCH fit in R’s MSGARCH package. Although a three-state transition matrix has nine entries, only six are independently estimated because each state’s remaining…

Machine learningVolatilityStatistics
Quant Q&A

The document derives the price of a call option that pays the square of the underlying price divided by the strike when the underlying finishes at or above the strike, and otherwise pays nothing. Under a Black–Scholes lognormal model, the direct approach…

OptionsDerivatives pricingVolatility
Quant Q&A

The document explains why options on one stock can have different implied volatilities across strikes and maturities. Implied volatility is a way to express an option price using Black–Scholes assumptions; it does not mean the market expects each option’s…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document addresses whether Dupire’s local volatility formula can be expressed using put prices as well as call prices. Under the stated zero-rate, zero-dividend setup, or when working with undiscounted options on forwards, the formula uses the option’s…

OptionsDerivatives pricingVolatility
Quant Q&A

The document asks how traders should select strikes and expiries for option positions such as protective puts and volatility strangles, while expressing concern that choices based only on backtest performance may be overfit. The response offers a practical…

OptionsExecutionVolatility
Quant Q&A

The discussion asks what to do when a historical Value-at-Risk model fails conditional coverage or independence backtests. It recommends treating the failure as a prompt to investigate the model and its inputs, rather than assuming that changing the return…

Risk managementBacktestingVolatilityStatistics
Quant Q&A

The document explains two Brownian motion calculations relevant to barrier option pricing: the midpoint distribution conditional on the terminal value, and the probability of crossing a barrier between fixed endpoints. For the midpoint, it uses the joint…

OptionsDerivatives pricingStatisticsVolatility
Quant Q&A

The document explains two ways a long option position can benefit from volatility: a rise in implied volatility can increase the option’s resale value, while large underlying price moves can benefit a long gamma position. A long straddle combines exposure to…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document asks for the expected product of a Wiener process evaluated at three ordered times. It establishes that the expectation is zero, using properties of Brownian motion rather than a numerical example. One argument exploits the symmetry of the…

StatisticsVolatility
Quant Q&A

The discussion addresses whether maximum-likelihood estimates of a Heston stochastic-volatility model, often used in derivative pricing, can be applied to value at risk. The reply distinguishes risk-neutral calibration for pricing from real-world risk…

Risk managementVolatilityStatisticsBacktesting
Quant Q&A

The discussion examines a Monte Carlo pricing expression that represents VIX through the risk-neutral expectation of the log of the S&P 500’s future level relative to its current level. The question is why simulated values might make the expression under the…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document discusses a proposed solution to a modified Black–Scholes equation for a European put when volatility depends on the underlying asset price. The proposed expression uses associated Laguerre polynomials and is evaluated as a series. A numerical…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document discusses ways to generate returns that reflect skewness and kurtosis, which a normal model does not capture. One approach uses a truncated Gram–Charlier Type A density: its coefficients are linked to cumulants, and the described setup gives a…

StatisticsVolatilityDerivatives pricing
Quant Q&A

The document investigates why a short put’s hedge delta increased even as the underlying price rose slightly. It reports that volatility also declined and two days elapsed, with a long time remaining to expiration. The response identifies charm, or delta…

OptionsDerivatives pricingVolatilityRisk management
Quant Q&A

The document raises practical questions about modeling American options with Black–Scholes–Merton, including early exercise, changing bid–ask spreads, intraday time to maturity, volatility estimation, historical risk-free rates, strike listings, and…

OptionsDerivatives pricingVolatility
Quant Q&A

The document explains how put-call parity for year-on-year inflation caps and floors can be used to infer the market rate of the underlying inflation swap. In present-value terms, the cap value minus the floor value equals the value of a swap that pays fixed…

OptionsFixed incomeDerivatives pricingVolatility
Quant Q&A

The discussion explains why VIX returns are often negatively associated with S&P 500 returns even though VIX represents implied volatility rather than market direction. In falling markets, investors may seek protection through index puts, raising option…

OptionsVolatilityEquitiesMarket microstructure
Quant Q&A

The question asks why some researchers fit curves to implied volatilities rather than option prices, given that both can vary nonlinearly with strike. The response points out that a standard pricing framework such as Black–Scholes provides a conventional…

OptionsVolatilityDerivatives pricing