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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
WonderTrader
14 documents
Alphalens
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 explores how strike selection and time to expiration affect the cost and payoff profile of long options. It considers the intuition that out-of-the-money options cost less and can deliver a larger percentage gain if the underlying moves…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document explains aggregate volatility as an estimated quantity used in studying whether marketwide volatility is priced in stock returns. In the cited research, changes in the VIX serve as a proxy for innovations in aggregate volatility. This is a…

VolatilityStatisticsFactor investing
Quant Q&A

This exchange clarifies a local relationship between normal and lognormal implied volatility when both models are used to represent the same option prices. The question presents a conversion factor involving the forward or spot level and moneyness, then asks…

OptionsVolatilityDerivatives pricingFixed income
Quant Q&A

This explanation examines why the CBOE dispersion index construction uses a market-cap-weighted sum of constituent variances, even though portfolio variance normally depends quadratically on weights and includes correlations. It defines dispersion as the…

EquitiesOptionsVolatilityStatistics
Quant Q&A

This exchange explains a sign error in valuing a floorlet with the Bachelier normal model. The question uses the call-style payoff expression with the forward rate above the strike, producing a premium far larger than the Bloomberg value. The accepted answer…

Fixed incomeOptionsDerivatives pricingVolatility
Quant Q&A

The document asks how to keep variance nonnegative in a discretized mean-reverting Heston-style model. Its response interprets the variance update as a discretization of a square-root diffusion, then states the Feller condition that keeps the continuous-time…

VolatilityDerivatives pricingRisk managementStatistics
Quant Q&A

The document asks how to explain the vega of an exotic derivative when its volatility surface is represented with Gatheral’s SVI parameterization. It proposes examining changes in each SVI parameter across time slices and approximating the resulting change…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document discusses how to present a quantitative trading interview assignment that forecasts volatility for several stocks from a short high-frequency dataset. The candidate used a Bayesian multivariate stochastic-volatility model and wonders whether the…

VolatilityMachine learningStatistics
Quant Q&A

The document describes an out-of-sample comparison of one-day-ahead variance forecasts from an ARMA-GARCH model against realized-volatility estimates for twelve stocks. It proposes checking calibration by regressing observed variance on forecast variance: an…

EquitiesVolatilityStatisticsBacktesting
Quant Q&A

The document introduces the distinction between implied and local volatility through a learner’s interpretation of option prices and diffusion models. Implied volatility maps strike and maturity to the volatility that reproduces a market option price under…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document shows how to price a European option with payoff equal to the positive part of the underlying raised to a constant power, less the strike. Under Black–Scholes, the underlying follows geometric Brownian motion. Applying Itô’s lemma to its power…

OptionsDerivatives pricingVolatility
Quant Q&A

The document examines a deep out-of-the-money call whose quoted market price implies far more volatility than the data provider reports. Recalculating implied volatility with an American-option model gives a value in the vicinity of 150%, while the provider…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document frames a choice between forecasting a stock basket’s correlation matrix with rolling-window Kendall’s tau or a generalized orthogonal APARCH(1,1) model. The motivating use is pricing options on a basket whose maturity defines the forecast…

EquitiesOptionsVolatilityStatistics
Quant Q&A

The document explains how to calculate an option’s volatility-related P&L when a pricing model maps observed market implied volatilities into calibrated parameters and then into the volatility used for the instrument. By the chain rule, sensitivity to each…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The document asks whether one scalar can summarize an implied volatility smile for a single maturity. It considers ATM curvature, estimated from nearby implied volatilities, and proposes SABR’s volatility-of-volatility parameter alpha as a possible…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document describes a thesis problem: fitting conditional volatility models to financial returns so their standardized residuals are approximately independent and identically distributed with zero mean and unit variance. GARCH(1,1) and GJR-GARCH(1,1)…

StatisticsVolatilityEquitiesTechnical indicators
Quant Q&A

The document asks how to represent two-month and three-month maturities from a broker’s implied FX volatility delta-tenor table when using the Black–Scholes formula. It contrasts converting the tenor to a simple year fraction, such as months over twelve,…

ForexOptionsVolatility
Quant Q&A

The document considers whether a covered-call seller should close a short out-of-the-money call after it has lost much of its value, then sell a call closer to the money. The proposed benefit is to collect additional premium as the short option’s delta and…

OptionsEquitiesRisk managementVolatility
Quant Q&A

The document compares annualized standard deviation of returns with realized volatility computed as the square root of summed squared high-frequency returns. It says the realized variance approach can make better use of intraday observations than a standard…

VolatilityStatisticsHigh-frequency trading
Quant Q&A

The discussion distinguishes stochastic volatility from the leverage-like relationship that creates an asymmetric implied volatility skew. Random volatility by itself can make returns heavier-tailed than a single normal distribution and produce a roughly…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The discussion explains why a strategy that anticipates underlying price moves and seeks delta exposure may still lose money through vega. For European vanilla calls and puts with the same strike, put-call parity implies equal vega; holding equal and…

OptionsVolatilityRisk managementDerivatives pricing
Quant Q&A

The discussion examines the claim that election probabilities should behave like binary option prices and that volatile forecasts violate no-arbitrage principles. The accepted answer challenges this analogy and the claimed volatility rules. It describes a…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document compares two long-term U.S. Treasury bond futures for outright, long-biased trading. It presents Ultra Treasury Bond futures as having a more consistent volatility profile, attributing this to a more homogeneous deliverable basket and an…

FuturesFixed incomeUS marketsVolatility
Quant Q&A

The document derives a Cox–Ingersoll–Ross process by summing the squares of independent Ornstein–Uhlenbeck processes. Applying Itô’s formula to each squared component produces a mean-reverting drift with a constant term, while the combined stochastic term…

Fixed incomeVolatilityStatistics