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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
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 describes a way to express a fixed tanker transportation payment as a percentage of the oil cargo’s value. It relates vessel capacity in barrels to the futures contract’s stated unit size, then uses the quoted futures price to value the cargo.…

CommoditiesFutures
Quant Q&A

The document considers whether beating or missing analysts’ earnings estimates predicts stock performance over horizons from a quarter to several years. The proposed approach defines surprise measures, separates positive and negative surprises, and regresses…

EquitiesEvent-drivenStatistics
Quant Q&A

The document explains why a stock modeled with geometric Brownian motion has drift equal to the risk-free rate under a risk-neutral probability measure. It contrasts the expected growth and discounted value of a riskless account with those of a risky stock…

Derivatives pricingStatisticsRisk management
Quant Q&A

The document asks whether extensions to the SABR stochastic-volatility model, often motivated by rates that can become negative, offer benefits for options on non-negative underlyings such as equities and foreign exchange. The response argues against using…

OptionsVolatilityDerivatives pricingFixed income
Quant Q&A

The document describes a proposed forward-starting swap steepener: receive fixed on a five-year swap and pay fixed on a thirty-year swap, with both starting at a future date. It frames carry as the benefit that may arise if the spot five-to-thirty-year curve…

Fixed incomeFuturesCarry
Quant Q&A

The document asks how to calibrate the one-factor Hull–White interest-rate model under a historical measure for counterparty credit risk calculations. It distinguishes this from risk-neutral calibration, which commonly fits market prices of swaptions or…

Fixed incomeStatisticsDerivatives pricing
Quant Q&A

The document addresses a performance question about calculating option prices or Greeks across many inputs in R. Its answer explains that the fOptions package's GBSGreeks function already accepts vector inputs, so a separate compiled-loop package is not…

OptionsDerivatives pricing
Quant Q&A

The document considers how to hedge a government bond portfolio using available short- and long-maturity futures. It cautions that a single quoted risk measure or maturity match is not enough to determine an effective blend: DV01 is nonlinear, and duration…

Fixed incomeFuturesRisk managementPortfolio construction
Quant Q&A

The document distinguishes market-by-order (MBO) data from market-by-price (MBP) data. MBO records individual orders, while MBP aggregates displayed quantities by price. Exchanges maintain order-level books internally, but traders build the representation…

Market microstructureExecutionHigh-frequency trading
Quant Q&A

The document considers a portfolio problem that maximizes expected alpha subject to bounds on factor exposures, and asks how this linear formulation compares with Markowitz optimization. The responses clarify that the classical Markowitz mean-variance…

Portfolio constructionRisk managementStatistics
Quant Q&A

The document asks how UK banks can offer mortgage rates that appear lower than the rates paid on some deposits. Its answers challenge the idea that comparing those two rates alone reveals the economics of mortgage lending. One answer says large banks often…

Fixed incomeStatistics
Quant Q&A

The document compares keeping strategy research and live trading in one environment with translating the strategy into a separate implementation language. It explains that research often analyzes fixed datasets with vectorized calculations, while live…

ExecutionBacktestingMarket microstructureHigh-frequency trading
Quant Q&A

The document asks how stock returns and historical prices should account for dividends, including how adjusted share prices reported by Yahoo Finance are calculated. It frames the issue around the price movement near a dividend payment: a stock may rise…

EquitiesStatistics
Quant Q&A

The document explains why risk-neutral probabilities can be useful even though they are not forecasts of real-world frequencies. It uses a currency example: a terminal probability of a specified euro decline against the dollar can be viewed as an implication…

Derivatives pricingStatisticsForexOptions
Quant Q&A

The document describes a proposed passive rebate trade in which a trader posts a bid on one marketplace, waits for a fill, then posts an offer at the same price elsewhere. If another participant responds to the displayed price, the trader might complete both…

ArbitrageMarket makingMarket microstructureExecution
Quant Q&A

Perpetual bonds have no contractual maturity date, so they provide a real-market example of instruments modeled with an infinite lifetime. The document explains that this legal feature does not necessarily mean investors should expect the bond to remain…

Fixed incomeDerivatives pricing
Quant Q&A

The note asks how to size option positions so a strategy reaches a chosen long-run daily volatility. It considers strangles and risk reversals, and compares sizing from the historical P&L volatility of one unit, from implied-volatility and vega estimates, or…

OptionsVolatilityPosition sizingRisk management
Quant Q&A

The document formulates a mean-variance approach to pricing a European call in an incomplete market. It seeks an equivalent martingale measure that minimizes the expected squared difference between the terminal value of a dynamically managed portfolio and…

OptionsDerivatives pricingRisk managementStatistics
Quant Q&A

The note clarifies what volatility implied by VIX options represents. VIX itself reflects an estimate of S&P 500 volatility over a forward 30-day period, but a VIX option does not simply measure the future volatility of today’s spot VIX. VIX options expire…

OptionsVolatilityDerivatives pricingFutures
Quant Q&A

The note explains why Fama–French factor research commonly waits six months after fiscal year-end before using accounting data such as book-to-market and firm size. Although quarterly reports may become available sooner, reporting dates and filing delays…

EquitiesFactor investingBacktestingStatistics
Quant Q&A

The document raises research design questions for comparing two sentiment datasets as predictors of volatility. It considers whether to include both GARCH and HAR models to broaden the analysis, and how to use sentiment measured continuously when the HAR…

VolatilityMachine learningStatistics
Quant Q&A

The document clarifies how a performance analytics workflow can treat the risk-free rate when calculating or plotting portfolio risk and return. A scalar input represents a constant rate, while a vector can associate a different rate with each return period.…

Risk managementStatisticsPortfolio construction
Quant Q&A

The document explains why logarithmic, power, and related concave utility functions recur in economic and investment models. Their appeal is mathematical tractability and the ability to express risk preferences through Arrow–Pratt absolute risk aversion, a…

StatisticsRisk managementPortfolio construction
Quant Q&A

The document asks why portfolio utility commonly subtracts a variance penalty instead of a standard deviation penalty. For a single risky asset, a position scales expected return linearly and variance quadratically, which can produce a finite optimal…

StatisticsRisk managementPortfolio construction