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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 introduces variance swaps as instruments for taking a view on an underlying asset’s volatility, described in the question as historical volatility. It asks whether a variance swap can practically hedge vega or volga exposure, and in what market…

Derivatives pricingVolatilityOptions
Quant Q&A

The document explains how a near at-the-money payer and receiver swaption pair behaves as the underlying forward swap rate moves. Its initial delta is approximately zero, though the exact value depends on the pricing setup; spot-premium treatment can also…

Fixed incomeOptionsVolatilityDerivatives pricing
Quant Q&A

The document describes estimating an event-related move from options by separating variance expected across ordinary time from the extra variance attributed to the event. It uses at-the-money implied volatilities for the first two expirations after the event…

OptionsVolatilityEvent-drivenDerivatives pricing
Quant Q&A

The document considers the usual estimate that annualized volatility equals monthly return standard deviation multiplied by the square root of twelve, and asks whether different month lengths should change the calculation. It explains that the relevant…

StatisticsVolatilityRisk managementBacktesting
Quant Q&A

The document explains why implied volatility can still be useful even though it is calculated from an option’s market price. It presents Black–Scholes as a way to transform observed prices into volatility values, which can then be used to estimate prices for…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document explains how to price a barrier option with a finite-difference engine in QuantLib when volatility is represented by a market implied-volatility surface. It points to the finite-difference Black–Scholes barrier engine and notes that its…

OptionsDerivatives pricingVolatility
Quant Q&A

The document derives a European call value when a forward price follows a two-factor diffusion with volatility components that vary over time. It applies the exponential solution for the forward process and combines the factor variances into an integrated…

OptionsDerivatives pricingVolatility
Quant Q&A

The question describes problems retrieving an implied volatility smile from a SABR volatility surface through QuantLibXL. A positive time input below one year produces a negative-time error, while another error appears to contradict the function's default…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document explains why an in-the-money option does not necessarily become more valuable simply because expiration is closer. It separates an option’s value into intrinsic value, determined by the current underlying price and strike, and time value, which…

OptionsDerivatives pricingVolatility
Quant Q&A

The document outlines the Black–Scholes derivation: apply Itô’s formula to an option whose value depends on the underlying, combine it with the underlying in a portfolio, hedge away the source of randomness, and use no-arbitrage to obtain the pricing PDE. It…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

This document examines how units and parameter choices affect the Avellaneda–Stoikov market-making model. It gives the reservation-price skew and optimal spread equations, then asks how price variance, order-arrival intensity, inventory, and remaining…

Market makingVolatilityMarket microstructureRisk management
Quant Q&A

The document discusses portfolio optimization using an ETF and VIX futures, comparing minimum-variance and Sharpe-maximizing approaches across different rebalancing schedules. The response focuses on minimum-variance intuition: an asset’s weight is…

Portfolio constructionVolatilityFuturesRisk management
Quant Q&A

The document outlines a variance-covariance approach to estimating volatility for a portfolio of cryptocurrencies. It starts from daily price changes, forms a covariance matrix of daily returns, and scales that matrix by 365 to estimate annual variance,…

CryptoStatisticsVolatilityPortfolio construction
Quant Q&A

The document derives the instantaneous volatility of a zero-coupon bond price under a one-factor Hull–White short-rate model. It presents the bond price as a deterministic function of time multiplied by an exponential term in the current short rate. The…

Fixed incomeVolatilityDerivatives pricing
Quant Q&A

The document asks whether daily log returns can be presented directly as daily variation when the goal is not to report risk over a longer horizon. It distinguishes an individual return observation from a volatility estimate: one return shows a realized…

VolatilityStatisticsRisk management
Quant Q&A

The document asks about an approximation discussed in a paper on delta hedging with a volatility smile: treating the sensitivity of implied volatility to the underlying price as equal to its sensitivity to strike. Under a downward-sloping smile, the cited…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The document explains how aggregate dealer gamma may affect hedging flows near options expiry. When dealers are long gamma, movements in the underlying can lead them to trade against the move, buying after declines and selling after rallies. When dealers are…

OptionsVolatilityMarket microstructureRisk management
Quant Q&A

The document explains that the VIX Flip indicator can be approximated with Williams VIX Fix, a synthetic volatility measure calculated from the highest close over a recent window and the current period's low. The reported formula expresses the gap between…

Technical indicatorsVolatilitySentimentBacktesting
Quant Q&A

The document asks whether EGARCH volatility forecasts are biased and seeks a published academic source supporting that claim. It identifies a preprint on bias correction for EGARCH estimators and a published study of finite-sample properties of EGARCH…

VolatilityStatisticsBacktesting
Quant Q&A

The document examines how changing the shift in a SABR model affects recalibrated parameters and swaption sensitivities. It describes experiments that fit shifted SABR to a constructed volatility set, first freeing correlation and volatility of volatility,…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document explains how the semi-variance HAR model (SHAR) extends the heterogeneous autoregressive model of realized volatility to represent asymmetric effects of past returns. It splits the daily realized variance into positive and negative…

EquitiesVolatilityHigh-frequency tradingStatistics
Quant Q&A

The response clarifies that a forward rate agreement, a caplet or floorlet, and an option on an FRA are different instruments. A caplet and a floorlet on the same future LIBOR fixing have complementary single-period option payoffs and can approximately…

Fixed incomeOptionsDerivatives pricingVolatility
Quant Q&A

The document outlines a QuantLibXL workflow for valuing a floating-rate bond whose cap and floor strikes vary by coupon. It recommends supplying a strike for each coupon to the floating-rate bond, then pricing the bond with a bond engine. An Ibor coupon…

Fixed incomeDerivatives pricingVolatility
Quant Q&A

The document presents an attempted trinomial-tree implementation of an uncertain volatility model for pricing European calls between minimum and maximum volatility bounds. It lays out a backward-induction scheme, defines a discrete second-difference term…

OptionsVolatilityDerivatives pricingBacktesting