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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
Lumibot strategies
7 documents
QuantRocket
7 documents
Awesome Quant
1 documents

Search the library

20,364 documents

Quant Q&A

The answer identifies a gas-fired power plant’s spark spread—the relationship between electricity revenue and the gas cost required to generate it—as a central exposure. It describes over-the-counter spread options as a way for a plant operator to hedge this…

CommoditiesFuturesOptionsRisk management
Quant Q&A

The accepted answer explains how to minimize conditional value-at-risk, also called expected tail loss, using a scenario-based linear program. It introduces portfolio weights, a variable representing the value-at-risk threshold, and one auxiliary variable…

Portfolio constructionRisk managementStatisticsBacktesting
Quant Q&A

The document describes a simulation designed to compare covariance transformations for minimum-variance portfolio construction. For each lookback window, the author samples portfolios of 100 assets, estimates a sample covariance matrix, transforms it, and…

Portfolio constructionStatisticsRisk managementBacktesting
Quant Q&A

The document proposes a quadratic program for finding an efficient frontier between expected alpha and a portfolio’s residual variance relative to a benchmark. It expresses residual variance as portfolio covariance risk less the benchmark variance scaled by…

Portfolio constructionStatisticsRisk management
Quant Q&A

The document frames an out-of-sample estimation question for a cointegration pairs strategy. In sample, the proposed workflow applies the Engle–Granger two-step procedure, estimates a hedge coefficient for the spread, and standardizes that spread using its…

Pairs tradingMean reversionStatisticsBacktesting
Quant Q&A

The discussion collects several ways to transform stock prices for analysis. Suggested measures include log prices, price deviations from a mean, standardized deviations using a standard deviation, log-price deviations from a mean, log returns, percentage…

EquitiesStatisticsPairs tradingBacktesting
Quant Q&A

The discussion explains reflexivity as a feedback loop: traders form expectations from information and prices, act on those expectations, and thereby change prices and later beliefs. It points to Keynesian beauty contests, game theory, agent-based models,…

Market microstructureStatisticsExecutionSentiment
Quant Q&A

The document compares two CAPM regression forms: one uses the asset's return in excess of the risk-free rate, while the other regresses the raw asset return on the market's excess return. It explains that, when the same observations and regressors are used,…

EquitiesStatisticsFactor investing
Quant Q&A

The document asks how to construct an efficient frontier by optimizing portfolio weights at specified volatility levels, rather than relying on random sampling. It describes maximizing expected portfolio return subject to a volatility ceiling and nonnegative…

EquitiesPortfolio constructionStatistics
Quant Q&A

The document describes implied volatility as a way to represent option prices on a more interpretable and comparable scale. A pricing model maps a market option price to the volatility input that would reproduce that price, allowing traders to discuss an…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document explains why equal percentage losses and gains do not cancel when returns compound. After a loss, the same percentage gain applies to a smaller capital base, so the account remains below its starting value. It gives a formula for the number of…

StatisticsRisk managementPosition sizing
Quant Q&A

The document asks how to interpret the Spearman correlation used in the Fundamental Review of the Trading Book to compare hypothetical P&L (HPL) with risk-theoretical P&L (RTPL). The stated procedure ranks each series in ascending order, then applies the…

StatisticsRisk management
Quant Q&A

The problem describes a seller who observes a sequence of prices for different future delivery days and must choose when to commit to selling. Prices for each fixed delivery date are assumed to follow a martingale. The proposed approach begins with a Bellman…

FuturesStatisticsExecution
Quant Q&A

The document asks whether trading strategies can remove volatility clustering—the persistence of large or small absolute returns—and what that would imply for diversification and alpha. It contrasts the CAPM view of market exposure with anecdotal claims that…

VolatilityStatisticsRisk managementMulti-asset
Quant Q&A

The discussion explains why currency spreads can widen sharply around 22:00 GMT, corresponding to 17:00 in New York. Forex trading is decentralized, and liquidity can fall when major financial centers hand activity over or close for the day. Contributors…

ForexMarket microstructureExecution
Quant Q&A

The discussion considers a daily strategy that holds positions for one day while using an indicator built from a five-year price history. Because adjacent indicator readings share much of the same input data, they are strongly serially dependent. The…

BacktestingTechnical indicatorsStatistics
Quant Q&A

The note asks whether traditional factor models become less adequate as markets grow more complex and new return patterns emerge. It cites the Fama-French three-factor model, which captures broad cross-sectional return patterns in the mid-1990s but does not…

Factor investingEquitiesMomentumStatistics
Quant Q&A

The document asks how to estimate the variance of monthly returns when a return series includes both monthly observations and one quarterly aggregate. The proposed response describes a moment-based approach under temporal independence: infer the quarterly…

StatisticsVolatilityRisk management
Quant Q&A

The document asks why credit rating grades can span different widths of probability of default (PD). Its example mapping assigns relatively narrow PD intervals to stronger grades and wider intervals to weaker grades, and raises the possibility that a PD…

Fixed incomeStatisticsRisk management
Quant Q&A

The document poses a fixed-income modeling question: whether a bond spread curve can be converted into a credit curve by applying the same bootstrapping function used for a CDS par-spread curve. The setup assumes a standard CDS framework with piecewise…

Fixed incomeStatistics
Quant Q&A

The document considers how to estimate a portfolio variance-covariance matrix when assets began trading at different times. One direct method is to use only the period in which every asset has data, which avoids mismatched histories but discards older…

StatisticsPortfolio constructionRisk management
Quant Q&A

The document explains the distinction between an option’s notional exposure and the price paid for the contract. Using the SPX example, the response applies a contract multiplier of 100 to the index level to calculate notional value, and applies the same…

OptionsDerivatives pricingUS markets
Quant Q&A

The document asks how to infer a stock’s beta from return expectations and how to attribute its variance to market risk. One response writes returns as a market-linked component plus an idiosyncratic residual. Under the single-index assumptions that the…

EquitiesStatisticsFactor investing