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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 document asks how to interpret the local volatility shapes implied by a stochastic-local volatility specification related to SABR. In this setup, the forward rate is scaled by a power of its level, with the exponent controlling the backbone; the author…

Fixed incomeVolatilityDerivatives pricing
Quant Q&A

The document asks whether a stock price can imply future volatility in the same way an option price does. The response explains that structural credit models can connect equity value to volatility because equity behaves like a claim on firm assets while debt…

EquitiesOptionsVolatilityDerivatives pricing
Quant Q&A

The document explains how to turn observed zero-coupon yields into bond prices and estimate instantaneous forward rates from maturity changes. The proposed finite-difference calculation uses adjacent maturities to approximate the maturity derivative of the…

Fixed incomeDerivatives pricingVolatilityStatistics
Quant Q&A

The document describes Markov-functional interest rate models as low-dimensional representations of the term structure built from functions of a Markov process. It notes their ability to calibrate to market prices and capture volatility smiles, while raising…

Fixed incomeOptionsDerivatives pricingVolatility
Quant Q&A

The discussion clarifies that a probability calculated from option implied volatility is not automatically a real-world forecast. Under Black–Scholes assumptions, the probability of finishing below a strike differs depending on the chosen pricing measure:…

OptionsVolatilityStatisticsDerivatives pricing
Quant Q&A

This thesis-related question asks how to choose bounds for the Heston model parameters kappa, theta, sigma, and rho when generating synthetic data to train a neural network for calibration. It compares one published set of ranges, described as excluding…

OptionsVolatilityMachine learningDerivatives pricing
Quant Q&A

This discussion considers a European call with an early-exercise feature that lets the holder exercise a portion and receive that portion’s current Black–Scholes value. The proposed replication is to hold the call and sell the corresponding fraction whenever…

OptionsDerivatives pricingVolatility
Quant Q&A

The document describes a calibration problem for a Libor market model used to value a Bermudan swaption. The proposed volatility structure has a parametric time-to-maturity shape and period-specific scaling factors, while correlations follow an exponential…

Fixed incomeDerivatives pricingVolatilityStatistics
Quant Q&A

The document asks how proprietary trading firms account for large intraday exposures when assessing annual trader performance with a PnL-to-VaR ratio. It distinguishes end-of-day ex-ante VaR, based on a trader’s positions, from risk estimates based on…

Risk managementStatisticsVolatility
Quant Q&A

The document explains how to estimate a variance risk premium when the available inputs are probability densities rather than volatility estimates. It defines the premium, loosely, as the difference between objective and risk-neutral variance of future…

OptionsVolatilityStatisticsDerivatives pricing
Quant Q&A

Implied volatility is the volatility input that makes an option pricing model, such as Black–Scholes, match an option’s market price. Because each strike, maturity, and option type is a distinct contract, each can trade at a different price and therefore…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document asks whether two assets with equal return volatility can be combined into a product with greater percentage-return volatility, without simply using cash leverage. It considers a long-only linear combination and derives its variance from the…

Multi-assetPortfolio constructionVolatilityOptions
Quant Q&A

The document clarifies a calculation for estimating volatility in a PRIIPs Category 2 stress scenario. The questioner first forms overlapping 63-day log returns, then calculates the standard deviation of those returns. The response says to calculate daily…

StatisticsVolatilityRisk management
Quant Q&A

The discussion considers how to build an equity volatility surface when American and European options are listed on the same underlying and provide separate implied volatility observations at each maturity. One practical preference is to use European options…

OptionsVolatilityDerivatives pricingMarket microstructure
Quant Q&A

The document explains how to infer implied correlation from an observed Margrabe option price. Given the two assets’ volatilities, prices, yields, and time to maturity, correlation determines the option’s relative volatility. The response notes that this…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The discussion examines why Black–Scholes can produce implausibly high values for very long-dated options. One explanation is that the model holds interest rates and volatility constant, even though both can change over time. The more detailed argument…

OptionsDerivatives pricingVolatilityEquities
Quant Q&A

The discussion considers why an exchange rate might be modeled with geometric Brownian motion, a process whose proportional changes have a drift and a volatility term. With constant coefficients, its solution is an exponential of a drift-adjusted time…

ForexStatisticsVolatility
Quant Q&A

The discussion examines the claim that a long calendar spread’s maximum loss is limited to its opening debit when the short option expires. In the usual intuition, if the underlying moves far below the strike, both calls lose value; far above it, both…

OptionsVolatilityRisk management
Quant Q&A

The discussion considers whether a constant displacement can adapt a standard LIBOR market model to negative interest rates. It proposes applying the shift to the forward rates used in the diffusion and drift numerators, while the accepted response clarifies…

Fixed incomeDerivatives pricingVolatility
Quant Q&A

The document works through the variance of a weighted basket when all asset returns have correlation one. For two assets, it writes the usual portfolio variance expression, including the covariance term, and recognizes that the expression becomes the square…

StatisticsVolatilityPortfolio construction
Quant Q&A

The document discusses how to calculate a one-year PRIIPs category 2 stress scenario for the Euro Stoxx 50 and why the reported value can change sharply between monthly KID dates. The response says the stress volatility should be based on rolling 21-day…

EquitiesVolatilityRisk managementStatistics
Quant Q&A

The document considers which volatility input to use when pricing options on futures with the Black model or a binomial tree. Its central point is that the appropriate volatility depends on the asset class and on which instrument provides the most relevant…

OptionsFuturesVolatilityDerivatives pricing
Quant Q&A

The document explains why variance swaps can serve as vega hedges and distinguishes several meanings of vega. A variance swap has sensitivity to its variance strike; option vega may instead refer to sensitivity to a parallel volatility shift or to changes in…

VolatilityOptionsDerivatives pricingRisk management