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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
Lumibot strategies
7 documents
QuantRocket
7 documents
Awesome Quant
1 documents

Search the library

20,364 documents

Quant Q&A

The document presents a question about a paper on deciding when to sell an asset whose price trend may be increasing or decreasing. The author is trying to understand a change of measure that is intended to simplify the model: the transformed process should…

StatisticsRisk managementDerivatives pricing
Quant Q&A

The discussion considers how to scale a large set of technical indicators when training a model across many stocks with different price levels and feature ranges. Suggested approaches include range scaling, mean-zero standardization, and converting skewed…

Technical indicatorsMachine learningStatisticsBacktesting
Quant Q&A

The document gives an intuitive explanation of the Merton model’s representation of risky corporate debt. A lender to a company that cannot default would receive the promised repayment, like holding a risk-free bond. With default risk, however, the lender…

Fixed incomeDerivatives pricingOptionsRisk management
Quant Q&A

The document examines the tracking error when a trader delta hedges an option using a Black–Scholes volatility that differs from the volatility the asset actually realizes. It presents an integral relating the error to the volatility difference and the…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The document examines why a QuantLib ImpliedTermStructure appears to change shape after the evaluation date is advanced. The example compares discount factors before and after moving the date by six months. The accepted explanation is that the underlying…

Fixed incomeDerivatives pricingStatistics
Quant Q&A

The document considers how to automate a spread strategy when the charting platform does not execute the user’s full rules automatically. The example strategy buys one instrument and sells another when their spread falls below a lower Bollinger Band, then…

ExecutionPairs tradingTechnical indicators
Quant Q&A

The document asks why the word “volume” is used for the total turnover of trades. Its answer traces the term to Old French, where it could refer to the mass or amount of something, including merchandise. It also notes that the modern French word has several…

Market microstructure
Quant Q&A

The document clarifies that asking whether futures follow a physical or risk-neutral distribution depends on the purpose of the analysis. The risk-neutral measure is a pricing tool: under suitable assumptions, prices of contingent claims can be represented…

FuturesDerivatives pricingRisk management
Quant Q&A

The document explains that a stock’s quoted implied volatility is inferred from option prices, rather than being a direct forecast of a one-standard-deviation move. Under Black–Scholes with constant volatility, one could estimate historical volatility from…

EquitiesOptionsVolatilityDerivatives pricing
Quant Q&A

The document derives the near-expiry approximation for the price of an at-the-money-forward European call under Black–Scholes. It rewrites the call price using the forward price and discounts the resulting payoff expression at the risk-free rate. At the…

OptionsDerivatives pricingVolatility
Quant Q&A

The document raises a calculus question that appears when differentiating the product of an exponential time factor and a Vasicek short rate. It asks how the ordinary time derivative relates to the differential expression and whether multiplying the…

Fixed incomeStatistics
Quant Q&A

The note examines a pricing argument for a replicable option payoff. If a trading portfolio and the derivative have equal terminal values almost surely, their discounted terminal values also agree, so their conditional expectations under a risk-neutral…

Derivatives pricingOptionsStatistics
Quant Q&A

The note distinguishes a zero-coupon bond price from the pathwise discount factor used to discount cash flows. In the Vasicek model, the bond price has an analytic expression conditional on the current short rate. The discount factor along a simulated path…

Fixed incomeDerivatives pricingStatistics
Quant Q&A

The document presents four regressions for a series and its first and second differences, then asks which integration level is supported. The examples include lagged-level coefficients, standard errors, and Breusch–Godfrey p-values for residual…

StatisticsBacktesting
Quant Q&A

The document explains how to turn a sequence of periodic returns into a continuous index or equity curve starting from a base value. It distinguishes adding return increments from compounding them and gives the accepted answer: multiply the index by one plus…

StatisticsBacktestingPortfolio construction
Quant Q&A

The document poses a question about how transforming two random variables affects second-order stochastic dominance (SOSD). Given that one variable SOSD-dominates another, it asks when applying the same monotonic function to both variables preserves that…

StatisticsRisk management
Quant Q&A

The document asks whether an individual stock’s historical monthly return frequencies can provide a valid expected return estimate. The proposed method groups observed log returns, treats each frequency as an estimated probability, multiplies returns by…

EquitiesOptionsStatisticsVolatility
Quant Q&A

The document outlines practical inputs and sample rules for calculating the Fama–French factors. It gives example Compustat formulas for book equity, operating profitability, market equity, and the book-to-market ratio, then describes how to form portfolios…

EquitiesFactor investingUS marketsPortfolio construction
Quant Q&A

The document outlines the two-step Fama–MacBeth procedure: estimate cross-sectional return regressions each month, then average each coefficient’s time series. It describes the usual standard error as the sample standard deviation of those monthly estimates…

StatisticsEquitiesBacktesting
Quant Q&A

The document explains how to transform a one-dimensional diffusion into a process with constant diffusion coefficient. Applying Itô’s lemma to a function of the state shows that the stochastic term is the derivative of the function multiplied by the original…

StatisticsDerivatives pricing
Quant Q&A

The discussion compares two ways to allocate capital between trade situations with different estimated profit factors. Scaling lots in proportion to each factor is presented as a way to maximize average profit factor across a fixed number of trials. With the…

Position sizingRisk managementStatistics
Quant Q&A

The document addresses an unexpected result in a Sharpe ratio sensitivity analysis: lowering the assumed risk-free rate appears to lower the ratio for both a strategy and its benchmark. The calculation described converts an annual rate into a daily rate,…

StatisticsRisk managementBacktesting
Quant Q&A

The document explains why a total return swap’s financing spread can reflect security borrow costs and how the contract relates to an index future. A TRS buyer receives the reference asset’s total return, including dividends, while paying a financing amount…

EquitiesFuturesDerivatives pricingCarry