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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

10,263 documents

Quant Q&A

The discussion examines the value of a total return swap that either party may terminate during a performance period. It contrasts a discounted mark-to-market valuation for a non-cancellable swap with an accrual-style cancellation payoff. One answer argues…

Derivatives pricingEquitiesFixed incomeRisk management
Quant Q&A

The post asks whether linear interpolation of implied volatility can create arbitrage, distinguishing interpolation across maturities from interpolation across strikes. It notes the concern that interpolating volatility over time may violate calendar…

OptionsDerivatives pricingVolatilityArbitrage
Quant Q&A

The document explains how a one-dimensional version of Girsanov’s theorem in Shreve’s stochastic calculus text follows from a more general formulation. The key identification is to take the Brownian motion as the local martingale and use the negative…

StatisticsDerivatives pricing
Quant Q&A

The document challenges a proposed rule linking an option’s time value to its delta. The claim is that when time value makes up at least a specified fraction of an option’s price, delta must be below a corresponding threshold. A Black–Scholes call example…

OptionsDerivatives pricingVolatility
Quant Q&A

The document asks how to plot a one-month implied volatility smile when call and put implied volatilities and option deltas are available, but spot and strike prices are missing. It notes that volatility smiles are often displayed against delta, so the…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document asks how to solve a three-dimensional backward Black–Scholes PDE with time- and state-dependent coefficients. Applying a Crank–Nicolson scheme across all three state variables at once creates a difficult coupled system. The response points to…

Derivatives pricingStatisticsBacktesting
Quant Q&A

The document explains why a slightly in-the-money American option does not generally have a delta of one. Delta reflects how the option’s total value, including remaining time value, changes with the underlying price; it is not determined solely by the slope…

OptionsDerivatives pricing
Quant Q&A

The document asks whether large options positions can make the underlying’s price respond to derivatives activity, especially when dealers must hedge positions with high gamma. It describes the proposed feedback: negative gamma hedgers may buy into sharp…

OptionsDerivatives pricingVolatilityMarket microstructure
Quant Q&A

The document asks how to model convexity adjustments for a payoff on the spread between two constant maturity swap rates when the rates are dependent. It notes that some approaches model each rate through an annuity mapping function and then use a copula to…

OptionsFixed incomeDerivatives pricingStatistics
Quant Q&A

The note clarifies that buying volatility is not always identical to buying an option, although vanilla options generally rise in value when implied volatility rises, all else equal. For a long option delta-hedged under a Black–Scholes model, it gives a…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document asks whether open-source software can support commodity pricing and risk management, noting that commodity contracts may involve a wide range of specialized payoffs. The answer says the author is not aware of a dedicated open-source library for…

CommoditiesDerivatives pricingRisk management
Quant Q&A

The document considers pricing a call-like payoff on the difference between the product of two correlated geometric Brownian motions and a scaled version of one process. It explains how to express the product process as a single geometric Brownian motion,…

Derivatives pricingOptionsVolatilityStatistics
Quant Q&A

The document poses a fixed-income question: how to lock in a one-year rate that begins three years from now using zero-coupon bonds with maturities from one to four years. It supplies annually compounded spot rates for each maturity and asks which bonds to…

Fixed incomeDerivatives pricing
Quant Q&A

The document presents implied volatility as a way to express option prices in familiar Black–Scholes terms. Because the model maps a vanilla option price to a volatility input, implied volatility helps compare options across strikes and maturities, track…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document explains why adding jumps to an option pricing model represents a different risk from simply increasing diffusion volatility. In a diffusion model, variability grows with the square root of time, while a Poisson jump component contributes…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document examines a bond yield-to-horizon calculation for a bond held until maturity. It contrasts a spreadsheet’s quoted 7.83% result with a calculation based on the ratio of horizon value to purchase price, and discusses reinvestment and compounding…

Fixed incomeDerivatives pricing
Quant Q&A

The document asks how to choose volatility and interest-rate inputs when pricing American puts with a binomial model and comparing estimates with market prices. The author proposes using the standard deviation of recent log returns for volatility and…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document summarizes a distinction between local volatility and stochastic volatility models when representing equity option markets. It reports that local volatility can fit observed vanilla option prices but may produce unrealistic forward volatility…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document examines whether an option’s extrinsic value, also called time value, follows a normal or lognormal shape as the underlying price changes. It describes an interpretation of the Black–Scholes call formula using a lognormal distribution of future…

OptionsDerivatives pricingVolatility
Quant Q&A

The document demonstrates how to use Halton low-discrepancy sequences in Monte Carlo option pricing. Uniform sequence values are transformed through the inverse standard normal distribution, then scaled by the drift and volatility of a risk-neutral log-price…

OptionsDerivatives pricingBacktesting
Quant Q&A

The document explores how to interpret the Radon–Nikodym derivative that converts real-world probabilities into risk-neutral probabilities in a one-step binomial market. In the two possible states, the derivative takes the ratio of risk-neutral to real-world…

Derivatives pricingStatisticsOptions
Quant Q&A

The document asks whether Black–Scholes call and put prices are convex as functions of implied volatility. The answers explain that convexity can vary with moneyness rather than holding uniformly. Vega, the derivative of option value with respect to…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document explains why a callable bond generally has a higher yield to maturity than a comparable noncallable bond. Its price can be viewed as the value of the noncallable bond minus the value of the issuer’s embedded call option. Since that option has…

Fixed incomeOptionsVolatilityDerivatives pricing
Quant Q&A

The document describes pricing a plain vanilla interest rate swap from a discount curve in QuantLib and simulating short-rate paths with the one-factor Hull–White model. It includes a detailed setup for fixed and floating legs, historical index fixings, a…

Fixed incomeDerivatives pricingVolatilityStatistics