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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

21,023 documents

Quant Q&A

The document frames interest rate modeling as a historical progression, listing equilibrium models such as Vasicek and CIR, no-arbitrage models such as Ho–Lee and Hull–White, multifactor models, the HJM framework, the Libor Market Model, and the Forward…

Fixed incomeDerivatives pricingStatistics
Quant Q&A

The document explains how to extend minimum-variance portfolio construction by adding a penalty on asset weights while keeping the weights summing to one. It notes that a convex penalty yields a convex optimization problem that can be solved numerically,…

Portfolio constructionRisk managementStatistics
Quant Q&A

The document explains why expected shortfall for the sum of two loss variables is no greater than the sum of their separate expected shortfalls. The key idea is that the worst observations for the combined portfolio generally differ from the worst…

Risk managementStatisticsPortfolio construction
Quant Q&A

The document asks whether a QuantLib term structure can use one interpolation style for the short end and another beyond a chosen maturity. The example is an overnight-indexed swap curve with flat, stepwise behavior around central-bank meeting dates,…

Fixed incomeDerivatives pricingStatistics
Quant Q&A

The document compares distributional choices for modeling interest rates, beginning with a proposed sequence of nonnegative independent observations. Responses caution that this assumption misses persistence and changing volatility: rates tend to cluster…

Fixed incomeStatisticsMean reversionVolatility
Quant Q&A

The document asks how a paper’s infinite-product representation of a pricing kernel relates to the familiar one-period stochastic discount factor and the change of measure from historical probabilities to risk-neutral probabilities. It outlines an affine…

Fixed incomeDerivatives pricingStatistics
Quant Q&A

The document asks whether bootstrap resampling should happen before strategy data mining or after a candidate strategy has been selected. It describes a monthly SPY and TLT rebalancing strategy tested over six years and 72 trades, reporting a backtest Sharpe…

BacktestingStatisticsMachine learningPortfolio construction
Quant Q&A

The document addresses how to calculate earnings before tax in a financing model when a company earns interest on cash. It asks whether interest income should be added to EBIT alongside the subtraction of interest expense. The answer cautions that interest…

EquitiesStatistics
Quant Q&A

The document explains an event equality for a continuous Brownian motion starting below a level u. It compares paths that reach a higher threshold, 2u−d, after the first time they hit u with paths that reach that higher threshold at any time before T. Given…

Statistics
Quant Q&A

The document explains why two derivatives for a two-asset portfolio's volatility differ when one asset's weight is constrained to equal one minus the other's. Roncalli's marginal risk contribution is a partial derivative: it varies one asset's weight while…

Portfolio constructionRisk managementStatistics
Quant Q&A

The document tests whether the process formed by multiplying one standard normal random variable by the square root of time is Brownian motion. Although each value has a normal distribution with mean zero and variance equal to time, those marginal…

StatisticsDerivatives pricing
Quant Q&A

The document describes a time-series analysis of European equity industry portfolio returns against Fama–French factor returns, with momentum included in one model. The portfolios include a value-weighted portfolio and equally weighted portfolios formed by…

EquitiesFactor investingStatistics
Quant Q&A

The document explains the drift in the extended Vasicek, or Hull–White, short-rate model. Under the risk-neutral measure, the short rate follows a mean-reverting process with a time-dependent drift term and volatility. The drift is not itself the riskless…

Fixed incomeDerivatives pricingStatistics
Quant Q&A

The document asks how to identify the most likely value associated with a call option when the underlying price is lognormally distributed. It starts from the discounted expected call payoff and distinguishes the mode of the underlying price distribution…

OptionsDerivatives pricingStatistics
Quant Q&A

The document compares simulating three assets independently with simulating them jointly through a multidimensional geometric Brownian motion. In the joint approach, correlated log returns are represented using a covariance structure and Cholesky…

Multi-assetRisk managementStatistics
Quant Q&A

The document asks how to formulate a Kalman filter for return-based style analysis, where a fund’s returns are related to factor returns and the factor exposures may change over time. It proposes modeling the beta coefficients as the hidden state, perhaps…

Factor investingStatisticsMachine learning
Quant Q&A

The document asks how to price a zero-coupon bond from a short-rate model, starting with the risk-neutral conditional expectation of the exponential of the negative accumulated short rate. It names several model families and asks how simulated rates,…

Fixed incomeDerivatives pricingStatistics
Quant Q&A

The document explains how floating-rate notes linked to overnight benchmarks accrue interest over a coupon period. It frames the calculations as adaptations of overnight indexed swap compounding and distinguishes simple averaging from compounding. It also…

Fixed incomeDerivatives pricingStatistics
Quant Q&A

The document explains why a historical portfolio Value at Risk calculation can return an empty result at a high confidence level. The cited implementation converts the confidence level to a lower-tail probability, multiplies that probability by the number of…

Risk managementStatisticsPortfolio constructionBacktesting
Quant Q&A

The document distinguishes reinsurance by the losses to which the retention and coverage limit apply. Stop-loss reinsurance covers aggregate losses over a period: the reinsurer pays the portion of total losses above a retention, potentially capped at a…

Risk managementStatistics
Quant Q&A

The document asks how to derive the conditional distribution of a Brownian motion value between two observed times. Given the values at the interval endpoints, it states that the intermediate value is normally distributed, with a mean formed by linear…

Statistics
Quant Q&A

The document defines Day One Profit or Loss as the difference between a financial instrument’s transaction price and its estimated fair value when a deal begins. It says fair value is typically estimated from market data and valuation models. The concept can…

Derivatives pricingRisk managementStatistics
Quant Q&A

The document explains why options on the same underlying can imply different volatilities across strikes even though the Black-Scholes model assumes constant volatility. It presents several interpretations: the smile can reflect model misspecification,…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The discussion considers whether high-dimensional Sobol sequences are practical for large market simulations and Monte Carlo pricing, where the required dimension may exceed the limits of common implementations. One answer points to established Sobol…

StatisticsBacktestingOptionsDerivatives pricing