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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 discussion examines limits of Sharpe-style returns-based analysis when fund exposures shift, especially for long-short strategies or data at daily and finer frequencies. Suggested alternatives include Lasso to shrink factor coefficients, Bayesian…

Factor investingStatisticsMachine learning
Quant Q&A

The document asks how to infer shorter-maturity annualized spot rates from a sparse set of observed term-structure points. It gives three observations at maturities of three, six, and nine months, then asks for rates at two and four months and whether a…

Fixed incomeStatistics
Quant Q&A

The document clarifies the notation u∧t that appears in a covariance integral while deriving the Vasicek model. It means the minimum of the two arguments: for example, when s is earlier than t, s∧t equals s. This is the same minimum-time structure used in…

Fixed incomeStatistics
Quant Q&A

The document explains how covariance between two currency-rate returns can be inferred when a third rate is related to them through a currency triangle. In log terms, the cross rate is represented as the sum or difference of the two component rates,…

ForexStatisticsDerivatives pricing
Quant Q&A

The document explains why a simple unilateral credit valuation adjustment for an option must combine the option’s future value with the counterparty’s probability of default. The suggested discretized calculation averages discounted expected exposure at…

OptionsDerivatives pricingRisk managementStatistics
Quant Q&A

The document addresses how to test whether two indicators help explain a time series of returns when the indicators may be autocorrelated or nonstationary and a VAR analysis has not produced significant results. Its proposed starting point is a linear…

StatisticsBacktestingTechnical indicators
Quant Q&A

The document responds to a request for credible examples of machine learning in quantitative finance. It emphasizes that machine learning methods are general-purpose tools that can be applied to financial, economic, or other data, while noting that many…

Machine learningRisk managementStatistics
Quant Q&A

The document asks why markets appear to respect Fibonacci retracement levels and connects that question to broader beliefs about market cycles and the possibility of a recession after a long advance. It gives no data, testing method, or examples showing that…

Technical indicatorsMarket microstructureStatistics
Quant Q&A

The document discusses hedging a known future expense of 2,500 USD when the home currency is euros. Using the stated spot and six-month forward rates, the answer calculates the euro amount fixed by the forward contract: dividing the dollar expense by the…

ForexDerivatives pricingRisk management
Quant Q&A

The document compares White’s Reality Check with the Benjamini-Hochberg-Yekutieli procedure for screening a large set of backtested strategies against a benchmark. It describes the Reality Check as accounting for dependence among test statistics through…

BacktestingStatisticsMachine learning
Quant Q&A

The document clarifies how a volatility surface indexed by moneyness can remain consistent with put-call parity. Although the question assumes calls and puts use opposite moneyness ratios, the answer explains that moneyness is generally defined the same way…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document presents the Gordon growth model for valuing a dividend-paying stock, with growth derived from return on equity and the retention ratio. It asks how to update intrinsic value day by day when the last annual dividend was paid the previous day.…

EquitiesStatistics
Quant Q&A

The document lists a small set of quantitative trading competitions in response to a Singapore-based participant seeking opportunities beyond the International Quant Championship and SMU Alphathon. It mentions a stock-prediction model competition run by XTX…

EquitiesForexCryptoMachine learning
Quant Q&A

The document describes diagnosing weak convergence in Monte Carlo simulations of an option-pricing model with state-dependent volatility. The original comparison estimates expectations at two time-step sizes, but uses independent simulated paths. Sampling…

OptionsDerivatives pricingStatisticsBacktesting
Quant Q&A

The document asks how to scale returns calculated from hourly bars to create volatility-adjusted features at longer horizons, including several-hour and calendar-period returns. It specifically considers whether a multi-hour return should be divided by…

VolatilityTechnical indicatorsStatistics
Quant Q&A

The document asks how to test whether a proposed predictor forecasts weekly stock market returns when observations are formed from overlapping daily windows. Because adjacent weekly returns share days, their errors may be correlated, so a test designed for a…

EquitiesStatistics
Quant Q&A

The document considers a physically settled crop futures contract when the farmer cannot deliver after a natural disaster destroys the crop. The answer explains that the contract remains in force and that failure to deliver can constitute default,…

FuturesCommoditiesRisk management
Quant Q&A

The document explains that standard open, high, low, and close bars are constructed from transaction prices. Best bid and ask quotes, quote sizes, and aggregate volume or book-size fields do not provide the actual sequence of trades needed for true OHLC…

Market microstructureExecutionStatistics
Quant Q&A

The document examines whether compounding normally distributed values can produce leptokurtic outcomes. It models the compounded result as a product of independent, identically distributed normal variables and gives expressions for its mean, variance, and…

StatisticsEquities
Quant Q&A

This note explains an approximate way to translate the spread on a USD-denominated bond into an equivalent spread over a euro reference rate. It considers a euro issuer that borrows in dollars and uses the SOFR–ESTR cross-currency basis to express the USD…

Fixed incomeForexCarry
Quant Q&A

P&L leakage is a small, recurring loss that may be hard to notice in daily results but accumulates into a material drag over time. The note places the concept in hedging and trading, where a reported or expected profit can omit costs and risks that are…

Risk managementExecutionVolatility
Quant Q&A

This note addresses a Python type error when calculating a bond’s z-spread with QuantLib. The example passes a RelinkableYieldTermStructureHandle into BondFunctions.zSpread, but the available overloads expect a yield-curve object, producing an argument-type…

Fixed incomeDerivatives pricing
Quant Q&A

The document explains why futures open interest can be an odd number even though every open contract has both a long and a short. Open interest counts contracts, not the two sides separately, so its value does not need to be even. When both parties open…

FuturesMarket microstructure