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.
5,922 documents
The document explains how to combine volatility estimates from consecutive periods. If returns across the periods are uncorrelated, their variances add, so the standard deviation over the full two-year span is the square root of the sum of the two annual…
The document discusses implementing the nine Piotroski F-score signals with company financial data. The response treats the questions as accounting and data-mapping issues, and recommends consulting the original research for precise definitions. It suggests…
The document asks whether a proposed constrained portfolio optimization setup correctly represents Kelly growth, how its portfolio curve relates to the familiar Kelly parabola, and how Kelly allocation differs from Markowitz mean-variance analysis. The…
The discussion explains why estimating returns and covariances from historical prices for Modern Portfolio Theory (MPT) does not, by itself, contradict the weak Efficient Market Hypothesis (EMH). MPT prescribes how to allocate assets given expectations about…
The discussion presents stochastic portfolio theory (SPT) as a framework for portfolio growth that accounts for asset variances and co-movements. It contrasts arithmetic expected returns with long-run logarithmic growth, explaining that volatility can reduce…
The discussion addresses how to keep a portfolio’s normalized value continuous when holdings are added or sold. Simply summing each stock’s normalized value using current portfolio weights can create an artificial jump at a trade, obscuring gains accumulated…
The response describes Markowitz mean-variance optimization as a model that remains in use because its logic is familiar and easy to explain, while its sensitivity to forecast assumptions is widely recognized. It compares extreme portfolio weights caused by…
The question asks to show that a tangency portfolio does not exist when the risk-free rate equals the expected return of the global minimum variance portfolio. One algebraic answer defines standard covariance-matrix quantities and assumes a solution to the…
The question asks why an asset should be added when its Sharpe ratio exceeds the existing portfolio’s Sharpe ratio multiplied by the asset’s correlation with that portfolio. One answer expresses portfolio Sharpe as a weighted combination of asset Sharpe…
The document distinguishes two claims that are often treated as if one automatically proves the other: that investors hold the same tangency portfolio among risky assets, and that this portfolio is the market portfolio. In the mean–variance framework,…
The document describes a portfolio-construction approach that substitutes a connectedness matrix for the covariance matrix and active returns for expected returns within a mean-variance optimization framework. The matrix is built from pairwise dependence…
The document asks how to choose portfolio objectives for investors with different risk preferences. It questions whether the Sharpe ratio suits a risk-neutral investor and whether replacing standard deviation in its denominator with value at risk or…
The document discusses how to organize historical equity data so backtests can handle delistings, acquisitions, ticker changes, dividends, and splits. One proposed design assigns stable internal identifiers to companies and separately tracks stock series and…
This note contrasts the analytical minimum-variance portfolio with portfolio optimization for maximum skewness. The minimum-variance problem has a closed-form solution under a full-investment constraint. The skewness objective instead depends on a coskewness…
The document considers whether value-at-risk or conditional value-at-risk (also called expected shortfall) is better suited to portfolio construction, focusing on a long/short equity portfolio without options. It summarizes a debate over risk measure…
The post asks whether expected utility portfolio optimization can be formulated when market models permit arbitrage. It references work on pricing under a weakened no-arbitrage assumption, while noting that the cited approach does not resolve utility…
The document says short-horizon curve construction depends on the market and intended use. For a USD swap curve, builders can incorporate actively traded instruments with different maturities and frequencies, including monthly fed funds futures, short-dated…
The document explains how to choose weights for two risky assets when their returns are highly correlated and their volatilities differ. It gives the variance of a weighted return portfolio in terms of the asset weights, individual variances, and cross-asset…
The document presents two matrix expressions for portfolio risk attribution: one labeled asset risk contribution and another labeled correlation-weighted asset risk contribution. It defines the identity matrix, diagonal weight and volatility matrices, asset…
The document treats replication of an option payoff using options at a different set of strikes as a constrained function approximation problem. It represents the target call payoff as a weighted combination of calls at available strikes, then chooses the…
The discussion questions whether reinforcement learning is useful when a portfolio model is trained on fixed historical prices. In that setup, market states advance independently of the chosen action, and next-period rewards can be deterministic given the…
The discussion explains how to include cash dividends when calculating an asset’s year-to-date return for performance analysis or backtesting. If dividends are not reinvested, the suggested calculation adds dividends received during the period to the ending…
The discussion distinguishes standard conditional value at risk (CVaR), also called expected shortfall, from a separate copula-based measure called CCVaR. Standard CVaR is described as a coherent risk measure, whose properties include subadditivity: the risk…
The document explains how to handle companies that fail during a historical stock study, such as an analysis comparing returns by corporate social responsibility ratings. Its answer recommends defining an investable universe using information available at…