Skip to content

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
Quantpedia
86 documents
TqSdk
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

8,116 documents

Quant Q&A

The document explains how an excess-of-loss reinsurance layer can be represented as a call-like payoff on the insured portfolio’s losses. If total losses are represented by a random variable and the contract covers losses above a threshold, its modeled…

OptionsRisk managementDerivatives pricing
Quant Q&A

The answer explains why a forward-start option on a price ratio depends on the interval between its observation dates in the Black–Scholes setting. Assuming constant interest and dividend rates and volatility, the log price follows a drifted Brownian motion.…

OptionsDerivatives pricingVolatility
Quant Q&A

This discussion concerns mapping listed option identifiers between Bloomberg and Reuters. It gives an example of an older Reuters RIC pattern for a Eurodollar option: the identifier encodes an exchange marker, strike, expiry month, call or put designation,…

OptionsFuturesMarket microstructure
Quant Q&A

The discussion asks when option prices under the Black–Scholes–Merton framework have analytic closed-form solutions and when numerical methods are needed. Its central point is that closed-form pricing formulas are uncommon across option problems, so…

OptionsDerivatives pricingVolatility
Quant Q&A

The document considers a worst-of return payoff on the S&P 500 and Euro Stoxx 50, valued under a risk-neutral measure. The proposed setup calibrates a separate Heston stochastic-volatility model to each index’s benchmark option volatilities and models…

OptionsEquitiesDerivatives pricingVolatility
Quant Q&A

The document considers an option that pays the positive difference between two asset values at expiry. Rather than extending a basic binomial tree to track combinations of movements in both assets, the answer points to the Margrabe formula under…

OptionsDerivatives pricingStatistics
Quant Q&A

The document outlines a numerical route from option prices implied by a volatility surface to local volatility using Dupire's formula. It identifies the required inputs as the maturity derivative of call prices and the second strike derivative. Rather than…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document offers two perspectives on classifying path dependence in derivatives. One practitioner-oriented criterion treats a payoff as non-path-dependent when its present value can be written as a discounted expectation at a single future tenor. Under…

Derivatives pricingOptionsStatistics
Quant Q&A

The document explains the European put’s value when its underlying stock price has reached zero before expiration. Under a geometric Brownian motion model such as Black–Scholes, zero is an absorbing state: the stock remains at zero. The put’s future payoff…

OptionsDerivatives pricingRisk management
Quant Q&A

The document describes an attempt to value an American call by applying exercise thresholds obtained from a binomial method to simulated stock paths. It gives an example with three scheduled exercise points and reports both the binomial model value and a…

OptionsDerivatives pricingBacktesting
Quant Q&A

The response outlines a two-model approach for estimating a European option value from an American option quote. First, use a Cox–Ross–Rubinstein binomial tree to find the volatility that makes the model price of the American option match its observed market…

OptionsDerivatives pricingVolatility
Quant Q&A

The document explains why a Fourier integral implementation for Black–Scholes call pricing returns roughly half the expected price. The problem is that the characteristic function must retain its complex values: taking its real part inside the function…

OptionsDerivatives pricingStatistics
Quant Q&A

This exchange explains what can be inferred from the price of a narrow call spread. Its central correction is that the spread informs the risk-neutral probability of the underlying finishing above the lower strike, rather than the probability of finishing…

OptionsDerivatives pricingStatistics
Quant Q&A

The document discusses why implied volatility and Greeks can become difficult to interpret for options with only a short time remaining. The response says that, away from the at-the-money region, gamma and vega may be close to zero while delta approaches the…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The document asks whether an option on a compounded-in-arrears overnight rate must be priced with Monte Carlo simulation. Its answer describes a backward-pricing alternative for Asian-style payoffs: add the accumulated rate to the model’s state variables,…

OptionsFixed incomeDerivatives pricing
Quant Q&A

The discussion examines whether volatility exposure belongs in a portfolio as an asset class or is better understood as a risk factor. One view distinguishes volatility itself from the instruments that provide exposure, such as options and volatility…

VolatilityOptionsPortfolio constructionRisk management
Quant Q&A

The document asks how to value a compound option when its underlying instrument is itself option-like and has additional conditions. A preferred share with conversion rights and dividends is given as an example. The author is considering Monte Carlo methods…

OptionsDerivatives pricingMachine learning
Quant Q&A

The answer gives a local approximation for the conditional expected value of an option after a specified spot move. It assumes a stochastic spot process and a volatility process whose shocks are correlated, with a separate independent volatility shock.…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document compares three ways to incorporate dividends into Black–Scholes pricing: use a continuous yield, subtract the present value of discrete dividends from spot, or add their future value to the strike. It explains that the methods represent…

OptionsEquitiesDerivatives pricingVolatility
Quant Q&A

The document explains why the Black–Scholes theta of an at-the-money European option can vary roughly linearly with volatility locally, while theta for in-the-money or out-of-the-money options may respond less simply. Under the stated assumptions of zero…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document examines why a Monte Carlo estimate of a call payoff changes when the simulated stock return uses different expected drifts. The question compares simulated terminal prices and average call payoffs under a positive drift and zero drift, and…

OptionsDerivatives pricingStatistics
Quant Q&A

This exchange diagnoses an error in a proposed fast Fourier transform implementation for pricing a European call option with a Cox-Ross-Rubinstein binomial model. The problem was the ordering of terminal underlying prices: the code built them from the lowest…

OptionsDerivatives pricingBacktesting
Quant Q&A

The document asks how to rewrite path-dependent call option payoffs using returns instead of asset prices. It starts from the relation between each observation price and its cumulative return factor: the price at a given time equals the initial price…

OptionsDerivatives pricingStatistics
Quant Q&A

The note explains why a portfolio formed by shorting a derivative and holding a matching number of underlying shares has no instantaneous exposure to the underlying’s random movement. Applying Itô’s Lemma to the derivative value separates its change into a…

Derivatives pricingOptionsRisk managementStatistics