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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
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

20,364 documents

Quant Q&A

The document asks whether sharp foreign exchange price moves around short binary option expiries reflect trades or misleading posted bids, and where traders can inspect FX order depth. The answer attributes many such moves to market makers hedging binary…

ForexOptionsDerivatives pricingMarket microstructure
Quant Q&A

The document examines why a reproduction of an older study’s positive, exponentially decaying autocorrelation in S&P 500 log returns does not appear in more recent minute data. The answer says that current high-frequency equity returns commonly show negative…

EquitiesHigh-frequency tradingStatisticsMarket microstructure
Quant Q&A

The document explains why implied volatility calculated from in-the-money (ITM) and out-of-the-money (OTM) equity calls may appear higher for ITM strikes. For calls, ITM contracts have strikes below spot, while OTM contracts have strikes above spot; the…

OptionsEquitiesVolatilityDerivatives pricing
Quant Q&A

The document presents a question about extracting a risk-neutral density from SPY weekly options using the R package RND. The author fits a three-lognormal mixture to American option prices and plots the resulting density over strikes around spot, but finds…

OptionsEquitiesDerivatives pricingStatistics
Quant Q&A

The document asks for the maximum price of a European call butterfly with strikes at 103, 106, and 108, assuming no fees and a zero interest rate, without specifying a distribution for the underlying. The accepted reply gives a maximum theoretical value of…

OptionsDerivatives pricingRisk management
Quant Q&A

The document asks why Jegadeesh and Titman used overlapping portfolio holding periods when testing momentum strategies. The replies give two intuitions: overlapping periods can create a larger sample than non-overlapping periods, and examining portfolios…

MomentumEquitiesBacktestingStatistics
Quant Q&A

The document describes an attempt to estimate Ornstein–Uhlenbeck process parameters by maximizing a Gaussian transition likelihood, then asks why the estimates fail or produce a math domain error. The replies identify a numerical singularity: the conditional…

StatisticsMean reversionBacktesting
Quant Q&A

The document summarizes ways to relate bilateral valuation adjustments to unilateral CVA and DVA. One explanation frames bilateral counterparty risk through scenarios in which both parties survive, the counterparty defaults first, or the institution defaults…

Derivatives pricingRisk managementFixed income
Quant Q&A

The document explains why a company’s income statement may not show depreciation and amortization as a separate line even when the cash flow statement reports it. The proposed explanation is that depreciation is often allocated among operating expense…

EquitiesStatistics
Quant Q&A

The document examines a puzzle about the Efficient Market Hypothesis: if traders can profit from information about mispriced stocks, why keep that information secret instead of publishing it after taking a position? Its answer is that the conclusion depends…

EquitiesStatisticsMarket microstructure
Quant Q&A

The document considers how market participants might proxy expected economic growth, taking GDP as the likely but not uniquely defined target. It points to the yield curve, especially the spread between ten-year and three-month Treasury rates, as an…

Fixed incomeStatisticsUS markets
Quant Q&A

The document describes the collateral choice option as an expectation involving the time integral of the maximum among several spread processes, typically modeled as Gaussian. It notes that this expectation is difficult to calculate and that a cited…

OptionsFixed incomeDerivatives pricingStatistics
Quant Q&A

The document explains how to interpret a cross-sectional rank correlation used in a trading alpha. At each date, rank securities by each variable across the same universe, such as open price and volume, then calculate the correlation between those two…

StatisticsTechnical indicatorsBacktesting
Quant Q&A

The document advises aspiring practitioners to learn statistics and machine learning before applying models to market data, then study financial modeling and backtesting, including transaction costs. It explains model fitting in terms of prediction error and…

Machine learningStatisticsBacktestingEquities
Quant Q&A

The document considers whether a fault at one exchange could create inconsistent trade records or apparent duplicate share sales, then discusses how exchanges and their supporting systems seek to preserve transaction integrity. The response uses the database…

Market microstructureExecutionHigh-frequency tradingRisk management
Quant Q&A

The document explores how to backtest an Avellaneda–Stoikov style market-making strategy using historical limit order book data. The question describes estimating order-arrival intensities from synchronized order and book events, then asks how simulated…

Market makingHigh-frequency tradingMarket microstructureBacktesting
Quant Q&A

The document raises two questions about using combinatorial purged cross-validation (CPCV) for a binary trading model: whether to select hyperparameters by averaging metrics across splits or across reconstructed paths, and whether evaluating those parameters…

BacktestingMachine learningStatistics
Quant Q&A

The document asks how to compare a numerical European call price from an explicit finite-difference scheme with the analytical Black–Scholes value at an intermediate time step. The model uses spatial grid points corresponding to underlying asset prices, and…

OptionsDerivatives pricingBacktestingStatistics
Quant Q&A

The document considers a four-option position consisting of a long put below the middle strike, two short options at the middle strike, and a long call above it. The questioner calculates one region of the payoff and finds a negative amount, which appears…

OptionsDerivatives pricing
Quant Q&A

The note examines the default intensity in the Black–Cox structural credit model, where default occurs when a geometric Brownian firm value first reaches a fixed absorbing barrier. It rewrites the distance to default as a Brownian motion with drift and gives…

Fixed incomeStatisticsRisk management
Quant Q&A

The document poses a calibration problem for a one-factor Hull–White short-rate model with constant volatility and mean-reversion speed, using historical zero rates. It proposes inferring mean reversion from the relationship between the historical…

Fixed incomeStatisticsDerivatives pricing
Quant Q&A

The document describes several ways to select bonds for a butterfly trade, depending on the rationale for the position. For a relative-value or mean-reversion trade, a trader can assess whether the middle maturity looks unusually rich or cheap against the…

Fixed incomeMean reversionPortfolio constructionRisk management
Quant Q&A

The document addresses why fitted AR parameters from a simulated ARMA series may differ substantially from the values used to generate it. The response says the simulation and fitting logic are sound and points to sampling variability: a series with only a…

StatisticsBacktesting
Quant Q&A

The document explains the probability meanings of the two normal cumulative terms in the Black–Scholes call price. The probability associated with the strike indicator in the discounted payoff is computed under the risk-neutral measure, while the…

OptionsDerivatives pricingStatistics