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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 why a study of a two-factor Double Heston model calibrates against option-market observations from many Wednesdays across a year, rather than conducting a separate calibration for each date. It contrasts that setup with research using…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document describes how to estimate a foreign-exchange risk-neutral density from vanilla option data, in the context of comparing the distribution for GBP/EUR around two historical dates. The required inputs include option prices across strikes and…

ForexOptionsVolatilityDerivatives pricing
Quant Q&A

The document considers an arithmetic Brownian motion with constant volatility and asks how often it is expected to move a fixed distance from its current level, resetting the reference band after each crossing. The question is framed in terms of repeated…

StatisticsVolatilityDerivatives pricingRisk management
Quant Q&A

The document raises the hypothesis that trend-following strategies may perform better in low-volatility conditions and asks how a trader might switch between trend and range-bound approaches. It defines volatility as the standard deviation of the price rate…

VolatilityTrend followingMean reversionTechnical indicators
Quant Q&A

The document describes how practitioners can approximate a digital option using a narrow call spread around its strike. Buying the lower-strike call and selling the upper-strike call creates a payoff concentrated between the strikes; as the gap narrows, the…

OptionsDerivatives pricingVolatilityExecution
Quant Q&A

The document explains why commodity options commonly reference futures or forwards rather than spot prices. Futures can offer liquid, standardized contracts with established price discovery and settlement conventions, making them practical underlyings for…

CommoditiesOptionsFuturesVolatility
Quant Q&A

The document raises a question about calculating rolling volatility for a PRIIPs category 2 stress scenario. The asker has calculated the initial sequence of log returns but is unsure how to apply the formula shown in presentation slides and reports getting…

VolatilityRisk managementStatistics
Quant Q&A

The document explains why higher volatility can increase the cost of delta-hedging a short option. Its central point is that the volatility used to price an option is an estimate of what the underlying will realize over the option’s life. If actual realized…

OptionsVolatilityRisk managementDerivatives pricing
Quant Q&A

The discussion addresses the lack of a direct implementation for a VECM-GARCH model in R and outlines a possible approximation. First estimate an error-correction term, for example with the Johansen procedure, then specify separate conditional mean and GARCH…

StatisticsVolatilityRisk management
Quant Q&A

The question compares Nasdaq volatility across years using average daily true range (TR). Since the index level changes over time, the author asks whether TR should be converted to a percentage or expressed through logarithms. The response says the right…

VolatilityStatisticsTechnical indicators
Quant Q&A

A constant maturity swap rate is the par swap rate for a chosen tenor, observed on each reset date. A CMS leg therefore references a swap rate such as the ten-year rate even when payments reset more frequently. In a CMS swap, that rate may be exchanged for a…

Fixed incomeDerivatives pricingVolatility
Quant Q&A

The post asks how a trader should adjust a volatility surface when pricing a product that includes a long option. The answer describes shifting the parameters of a chosen surface model in absolute terms, with adjustments reflecting the trader’s exposure to…

OptionsVolatilityRisk managementDerivatives pricing
Quant Q&A

The document examines how an option’s theta changes as time passes, sometimes described as theta acceleration. It distinguishes the textbook Black–Scholes theta from a finite-difference estimate obtained by repricing after a one-day time shift. Comparing…

OptionsDerivatives pricingVolatility
Quant Q&A

The question asks how to model high-frequency asset returns with a Student-t distribution after estimating two-scale realized volatility, and how to annualize the result and choose a sampling frequency. The response focuses on degrees-of-freedom estimation…

StatisticsVolatilityBacktesting
Quant Q&A

The document considers calibrating an equity stochastic-volatility model alongside a stochastic short rate, with correlations among the driving processes. It explains that the stated combination may lack a tractable closed-form pricing formula, making direct…

OptionsDerivatives pricingVolatilityFixed income
Quant Q&A

The document frames the model-selection problem for pricing vanilla swaptions on fixed-versus-floating or floating-versus-floating legs. Requirements include multiple floating-rate tenors, OIS and LIBOR legs across currencies, mid-curve structures, and both…

OptionsFixed incomeDerivatives pricingVolatility
Quant Q&A

The document considers whether options can reveal the market’s expected volatility from one close to the following open. It explains that an option’s implied variance over its life represents variance accumulated across the full interval to expiry. A quoted…

OptionsVolatilityStatisticsDerivatives pricing
Quant Q&A

The document asks whether a volatility skew creates expected profit from buying an at-the-money option and delta hedging it. Its answer separates implied volatility from the path of realized prices: a move to a particular terminal level does not reveal how…

OptionsVolatilityDerivatives pricing
Quant Q&A

The note examines why an equity option’s annualized at-the-money implied volatility can be higher for a shorter expiry than for a longer one. It distinguishes a downward-sloping volatility term structure from negative forward variance: comparing two implied…

OptionsEquitiesVolatilityDerivatives pricing
Quant Q&A

The document compares two ways to estimate the price of a European call at a strike and maturity absent from the market: interpolate neighboring option prices directly, or interpolate model inputs such as implied volatility and then reprice with…

OptionsVolatilityDerivatives pricingArbitrage
Quant Q&A

The discussion explains why delta neutrality is common in options trading while emphasizing that it depends on the trader’s objective. A market maker who earns spreads may hedge directional exposure to focus on volatility and pricing, whereas a risk taker…

OptionsMarket makingVolatilityRisk management
Quant Q&A

The document examines why the Schöbel–Zhu stochastic volatility model can be treated as affine when deriving the stock price characteristic function. It describes augmenting the state with squared volatility and applies Itô’s lemma to obtain the dynamics of…

Derivatives pricingVolatilityStatistics
Quant Q&A

The document explains how to interpret realized variance formed by summing squared returns over a chosen sampling window. A sum of 5-minute squared returns covering two hours is a two-hour realized variance; annualization requires scaling by the number of…

VolatilityStatisticsMarket microstructure
Quant Q&A

The document describes how to recover an option’s implied volatility when its price must be estimated by Monte Carlo simulation. Independent random draws at each volatility can make estimated prices jump around, obscuring the price-versus-volatility…

OptionsVolatilityDerivatives pricingStatistics