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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 document explains how daily leveraged and inverse exchange-traded products can lose value through compounding when the underlying index is volatile. It compares short sequences of positive and negative index returns and shows that the inverse product’s…

EquitiesVolatilityDerivatives pricingStatistics
Quant Q&A

The document discusses pricing a zero-coupon bond under the Cox-Ingersoll-Ross short-rate model and asks how to choose its long-run rate, mean-reversion speed, and volatility. One response expresses bond value as the expected discount factor over the bond’s…

Fixed incomeDerivatives pricingStatistics
Quant Q&A

The document considers a one-period market with two risky assets and three possible future states. After arguing that the market is arbitrage-free, the question is how to establish that every contingent claim can be replicated without solving explicitly for…

Derivatives pricingPortfolio constructionArbitrageStatistics
Quant Q&A

The document asks how to select an Esscher change-of-measure parameter for an exponential Lévy asset so that the discounted asset price is a martingale under the new measure. It writes the Radon–Nikodym density as an exponential tilt and uses conditional…

Derivatives pricingStatisticsOptions
Quant Q&A

The document explains how correlation between asset returns and volatility innovations affects the relationship between Black–Scholes volatility and a stochastic-volatility model such as Heston. Negative correlation is reported as typical for equity indices…

OptionsVolatilityDerivatives pricingEquities
Quant Q&A

The document surveys R packages for option pricing and related analysis. It names RQuantLib and NMOF for model implementations, including Black–Scholes–Merton, jump-diffusion, Heston, and characteristic-function approaches. It also points to RND for…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document shows how to check that a Black-Scholes call price satisfies the Black-Scholes partial differential equation by substituting expressions for delta, gamma, and theta. The PDE relates the option value to its time sensitivity, underlying-price…

OptionsDerivatives pricingStatistics
Quant Q&A

The document describes several uses of options pricing formulas even when markets are broadly efficient. Models can help traders assess possible mispricing, value contracts that are newly issued or lack a direct market quote, and infer quantities such as…

OptionsDerivatives pricingVolatility
Quant Q&A

The document explains how to adapt a collateralized forward-pricing relationship for an inflation-linked bond with a coupon paid before forward settlement. The nominal bond proceeds method is adjusted by applying an index ratio to the spot value, interim…

Fixed incomeDerivatives pricingCarry
Quant Q&A

The document examines whether a European call can be replicated when the stock follows an arithmetic Brownian motion and the bank account grows at a constant rate. It outlines an argument for market completeness by finding a change of measure that makes the…

OptionsDerivatives pricingStatistics
Quant Q&A

The document explains why operating a gas-fired power plant creates exposure that resembles being long electricity and short natural gas. The plant’s gross margin depends on the electricity price received minus the fuel and emissions costs, adjusted for…

CommoditiesFuturesRisk managementDerivatives pricing
Quant Q&A

The document explains how to interpret the variance-rate assumption in the original Black–Scholes model. For a diffusion process, the instantaneous variance rate is the square of the coefficient multiplying the Brownian motion. In geometric Brownian motion…

OptionsDerivatives pricingStatisticsVolatility
Quant Q&A

The document explains how to derive an implied volatility surface for a currency pair from surfaces quoted for two related pairs. Its example combines EURUSD and USDJPY data to price EURJPY options. It first expresses the target option payoff in terms of the…

ForexOptionsVolatilityDerivatives pricing
Quant Q&A

The document describes an implementation attempt for Haug’s double-barrier binary option formulas and explains why the asymmetric case produced incorrect results. The key correction is to treat the final term involving the asset’s position between the lower…

OptionsDerivatives pricing
Quant Q&A

The document poses a derivation problem in currency derivatives. It defines stochastic dynamics for a foreign-market stock and the domestic/foreign exchange rate, alongside a deterministic domestic money account. The proposed approach converts the foreign…

ForexDerivatives pricingStatistics
Quant Q&A

The answer introduces the relationship between a chosen numeraire and the probability measure used for pricing. Its central idea is that, under the measure associated with a numeraire, the price of another asset divided by that numeraire has no expected…

Derivatives pricingStatisticsFixed income
Quant Q&A

The document explains why binomial-tree formulas for the up factor can differ across constructions. In the Cox–Ross–Rubinstein tree, the up and down factors are set symmetrically around zero log drift, with volatility determining their size. The answer notes…

OptionsDerivatives pricingStatistics
Quant Q&A

The document asks how to calculate the variance of integrated variance in the Heston stochastic-volatility model. It connects the problem to the closely related Cox-Ingersoll-Ross square-root process, whose integrated state variable has a known…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document explains how to screen listed-option observations before calibrating a pricing model. It describes filters based on low average prices, wide bid-ask spreads, extreme moneyness, and very short or long times to expiry. These rules aim to remove…

OptionsDerivatives pricingMarket microstructureStatistics
Quant Q&A

The note explains why an asset’s volatility over a fixed horizon matches the volatility of a prepaid forward contract on that asset with the same expiry. Both are measured as the standard deviation of a log return over the period. At the start, the asset…

VolatilityDerivatives pricingFutures
Quant Q&A

The document rearranges European put-call parity to explain the components of put value when there are no dividends. It frames the put's intrinsic value as the strike minus the stock price, with time value reflecting both the call's upside protection and the…

OptionsDerivatives pricingEquities
Quant Q&A

The document asks how to obtain an analytical expression for a process defined as a power of geometric Brownian motion. It states the geometric Brownian motion model, presents an application of Itô’s lemma for the powered process, and rewrites the dynamics…

StatisticsDerivatives pricing
Quant Q&A

The document presents Python code for pricing a European call or put with an implicit finite-difference grid. It asks why the coefficient matrix is modified at its first and last rows and why boundary grid values at each time step are extrapolated from…

OptionsDerivatives pricingStatistics
Quant Q&A

The document asks when a fixed-strike arithmetic Asian call can be worth more than a vanilla call with the same maturity. Its answer compares their maturity payoffs: the Asian call pays on the average underlying price, while the vanilla call pays on the…

OptionsDerivatives pricing