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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

12,303 documents

Quant Q&A

The document asks whether factor volatilities in the multi-factor Heath–Jarrow–Morton framework may be negative. It notes that the drift expression uses products of volatility functions, then reports a reference that explicitly assumes these functions are…

Fixed incomeVolatilityDerivatives pricing
Quant Q&A

The document considers how to track changing dependence between two time series when a changing regression slope may reflect shifting variances rather than a stronger relationship. It raises similar interpretive concerns about time-varying quantile…

StatisticsVolatilityMachine learning
Quant Q&A

The document asks how to price structured products that depend on three-month EURIBOR, including constant-maturity swap spreads, range accruals, and target redemption notes, when discounting uses €STR. It proposes modeling the €STR short rate with a…

Fixed incomeDerivatives pricingVolatility
Quant Q&A

The document explains why the Black–Scholes delta hedge can have gains or losses when volatility changes, despite the model’s claim of a riskless hedge. The key distinction is that the theoretical result assumes geometric Brownian motion and continuous…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The document addresses which implied volatility to use when converting a quoted option delta into a strike. Its guidance is to use the volatility associated with that particular delta, together with the other inputs required by the option-pricing…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document explains the intuition behind buying an option when its implied volatility appears lower than a forecast of realized volatility. A long option position has positive gamma: as the underlying rises, its delta increases and a trader can sell some…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document asks what parameter restrictions apply when estimating EGARCH and GJR-GARCH volatility models, contrasting them with the familiar positivity and stationarity conditions for standard GARCH. It presents the two asymmetric model specifications but…

VolatilityStatistics
Quant Q&A

Financial prices often behave as nonstationary series: their statistical properties can depend on the price level and past observations. Returns, calculated as percentage changes or differences in log prices, are more often treated as stationary. That makes…

StatisticsVolatilityBacktesting
Quant Q&A

The document distinguishes implied-volatility skew across option strikes from skewness in the underlying asset’s return distribution. It presents model-free implied skewness as a measure connected to realized skewness, and describes research finding a…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The response suggests comparing a volatility forecast from a non-normal GARCH model with the volatility implied by option prices. If the options appear inexpensive relative to the forecast, the proposed position is to buy calls and puts; if the implied…

OptionsVolatilityMachine learning
Quant Q&A

The document discusses how market participants price American options on Eurodollar futures and when a European-option approximation may be adequate. It contrasts tree-based models that represent early exercise with the simpler European treatment often used…

FuturesOptionsFixed incomeDerivatives pricing
Quant Q&A

The discussion explains why equity volatility and credit default swap spreads may move together, focusing on structural models of a firm’s capital structure. In the basic Merton framework, equity behaves like a call option on firm assets, with debt repayment…

EquitiesFixed incomeVolatilityArbitrage
Quant Q&A

This exchange addresses how to retrieve the long-run variance component from a component GARCH model fitted with the rugarch package in R. The questioner can obtain conditional volatility with the package’s standard accessor but needs the time-varying…

VolatilityStatisticsMachine learning
Quant Q&A

The note explains why hedging skew exposure in a forward-starting option differs from hedging an ordinary option. A forward-starting put may be analytically short skew, yet during the forward period its strike resets in proportion to the underlying price.…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The note explains why stock price models often require the volatility process to be square integrable so that its stochastic integral with Brownian motion is well defined in the standard Itô framework. It distinguishes the condition that the expected…

EquitiesVolatilityStatistics
Quant Q&A

The document compares three representations of option market information: implied volatility by strike and maturity, raw call or put premiums, and the risk-neutral return distribution. It argues that these are equivalent views of the same information and can…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document asks how to select the mean-reversion parameter in a one-factor Hull–White model when pricing Bermudan swaptions. It describes a calibration approach based on the ratio of standard deviations of two forward rates with a shared expiry and…

Fixed incomeDerivatives pricingVolatilityMean reversion
Quant Q&A

The document distinguishes the average return conditional on a loss from the unconditional contribution of losses to expected return. For a zero-mean normal return with volatility parameter sigma, it identifies the requested conditional quantity as the…

Risk managementStatisticsVolatility
Quant Q&A

The document maps views about forecast return distributions to simple option positions. A belief that expected returns are understated or overstated is associated with buying a call or put, respectively. Views on dispersion are paired with long or short…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document studies a payoff that delivers the stock’s terminal price only when its return relative to an index clears a threshold. It first sketches Monte Carlo simulation using geometric Brownian motion, then gives a risk-neutral derivation. The…

OptionsDerivatives pricingVolatility
Quant Q&A

The document explains how QuantLib’s BlackVarianceCurve distributes variance through time according to its day-count convention. Because the curve interpolates linearly in variance, using Business/252 produces a constant variance increment per business day…

VolatilityDerivatives pricingOptions
Quant Q&A

The document discusses using SABR to price EUR inflation caplets when strikes can be negative, a setting where standard Black and unshifted SABR formulations are not directly applicable. One response recommends reconsidering the model: inflation option…

OptionsDerivatives pricingVolatility
Quant Q&A

The document asks whether option prices can reveal a likely rise followed by a later decline in a security. The answer explains that a sufficiently broad set of European option strikes for two expirations can be used to infer a risk-neutral price…

OptionsDerivatives pricingVolatilityStatistics