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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
QuantRocket
7 documents
Lumibot strategies
7 documents
Awesome Quant
1 documents

Search the library

20,364 documents

Quant Q&A

The document explains how to estimate one-day Value at Risk for a single-asset portfolio when its delta, the asset value, and daily volatility are given. It interprets delta as the portfolio’s sensitivity to a small percentage move in the underlying, then…

Risk managementPosition sizingStatistics
Quant Q&A

The document sketches why a market with stochastic volatility may be incomplete when volatility risk is driven by an independent source of randomness that cannot be traded directly. In a one-stock setting, changing the risk premium associated with the…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document investigates a Python QuantLib TypeError raised while constructing Heston model calibration helpers for options. The replies point to mismatched input types or values as the likely cause and identify code issues to check, including an…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document asks why a process formed by keeping Brownian motion unchanged up to a stopping time and reflecting its later path around its value at that time is itself standard Brownian motion. The response uses the strong Markov property: after a finite…

Statistics
Quant Q&A

The document proposes choosing a retail time-deposit term by calculating the net present value of deposits with different maturities and converting each value into an equivalent constant annual payment over its term. It selects the term with the highest…

Fixed incomeStatisticsBacktesting
Quant Q&A

The document discusses estimating the liquidity parameters in the Avellaneda–Stoikov market-making model from historical limit-order data. The model describes fill intensity at a quote distance from fair value using a baseline intensity A and a distance…

Market makingHigh-frequency tradingMarket microstructureStatistics
Quant Q&A

The response distinguishes two interpretations of a share purchase plan in which the bank can terminate during the purchase period. If the customer’s price is the average only through the termination date, the answer argues that termination does not create…

EquitiesOptionsVolatilityDerivatives pricing
Quant Q&A

The document explains why a Black–Scholes option price is not the discounted expected payoff under real-world probabilities. That calculation uses the stock’s physical drift, which reflects expected returns, but ignores how traded assets and hedging…

OptionsDerivatives pricingArbitrageStatistics
Quant Q&A

Corporate bond yields combine a Treasury-related risk-free component with a credit and liquidity spread. The relative size of these components helps explain why investment-grade bonds tend to move more closely with comparable-maturity Treasury yields, while…

Fixed incomeUS marketsStatisticsRisk management
Quant Q&A

The document asks what drives the price of a bond futures calendar spread when both contracts share the same deliverable basket and cheapest-to-deliver bond. The accepted answer identifies the forward repo rate implied by term repo rates extending to each…

FuturesFixed incomeDerivatives pricing
Quant Q&A

The document asks where to obtain inexpensive historical tick data for a futures contract, using NYMEX WTI crude as an example. Its answer explains that data price often reflects whether the feed preserves all reported activity or filters some events. A…

FuturesCommoditiesMarket microstructureExecution
Quant Q&A

The document asks how an expected shock to one asset should affect the weights of other holdings, and whether portfolio substitutability can explain those changes. It proposes that assets with more similar characteristics might receive more of the…

Portfolio constructionRisk managementStatistics
Quant Q&A

The document asks why a leverage or volatility-scaling factor changes the turnover ratio of a momentum portfolio, citing the approach associated with Barroso and Santa-Clara. It distinguishes the intuitive idea of multiplying portfolio exposures by a scale…

MomentumPortfolio constructionExecution
Quant Q&A

The document addresses how to account for upcoming corporate actions when implementing a long-short equity statistical arbitrage strategy using a Bloomberg data license. The strategy holds positions across many stocks, and the author asks how to find events…

EquitiesEvent-drivenPortfolio construction
Quant Q&A

The document clarifies how SVI parameterizations describe implied volatility data. Raw and natural SVI parameterizations represent total implied variance across strikes for a single expiry, while SVI-Jump-Wings represents implied variance for a single…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document explains why binary option quotes that appear inconsistent with a simple Black–Scholes volatility range may still be reasonable. It gives the digital call price in terms of the forward price, strike, time to expiry, rates, and volatility, then…

OptionsVolatilityDerivatives pricingUS markets
Quant Q&A

The document describes a bond discount-curve fitting error in QuantLib. The questioner supplies bond maturities and coupon rates alongside market prices, then constructs fixed-rate bond helpers for a Nelson–Siegel fitted discount curve. The reported…

Fixed incomeBacktestingStatistics
Quant Q&A

The document examines a terminal payoff formed by taking the positive part of the stock’s gain over its current price, subtracting a fixed notional, and capping the result at zero. It asks how to price this payoff under risk-neutral valuation, while noting…

OptionsDerivatives pricingEquities
Quant Q&A

The document asks why reported short-sale volume from venues such as NYSE, Nasdaq, and BATS can appear much larger than published short interest. It raises questions about differences in venue coverage and whether transactions connected to securities…

EquitiesMarket microstructureUS marketsStatistics
Quant Q&A

The document considers whether large traders can manipulate e-mini futures and whether that possibility makes systematic trading impractical. Its answers distinguish ordinary market impact from deliberate manipulation: large buy orders can push prices up,…

FuturesMarket microstructureExecutionOptions
Quant Q&A

The document explains why futures are commonly quoted by their settlement or delivery price rather than by the contract’s present value. It places this convention alongside other market practices, such as quoting bonds by yield and options by implied…

FuturesCommoditiesDerivatives pricingMarket microstructure
Quant Q&A

The document considers how to adjust a fitted vanilla-option implied volatility surface to represent a lower-volatility market or an abrupt volatility shock. It cautions that blindly adding a constant to implied volatility or multiplying it by a scale factor…

OptionsVolatilityArbitrageDerivatives pricing
Quant Q&A

The document explains how investment banks’ charges for derivatives relate to market competition and the transparency of pricing. It frames the added cost as a wider bid–ask spread rather than necessarily as a separate fee on top of a theoretical…

Derivatives pricingMarket microstructure