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.
4,194 documents
The document examines why the Fama–French model regresses stock returns on market, size, and value factor portfolio returns instead of directly using firm size and book-to-market ratios. One answer argues that factor returns keep regressors in return units,…
The document asks whether equity factor models can tell a portfolio manager how to position a portfolio to earn alpha, beyond identifying its factor exposures. The response gives a limited conceptual distinction: in the stated arbitrage pricing theory…
The document outlines how to test the CAPM by comparing asset excess returns with market excess returns through estimated betas. It explains that the Kenneth French data library supplies market returns and a risk-free rate, but generally does not provide…
The note explains how to estimate monthly idiosyncratic volatility for German equities using a three-factor Fama–French regression. It advises using the precomputed European factors from Ken French’s data library rather than calculating a separate factor set…
The document discusses how to combine rolling-window estimation with the two-stage Fama–MacBeth method. The questioner estimates portfolio factor exposures over rolling five-year samples, producing many sets of estimates, and asks which exposure estimates…
The document raises a currency alignment issue in testing whether portfolio returns earned by a Danish investor are explained by European Fama–French three-factor returns supplied in US dollars. It reports two attempted specifications: regressing…
The discussion explains why a governance portfolio’s estimated market beta can be below one without implying that its total volatility is proportionately lower than the market’s. Beta measures the portfolio’s covariance with the market relative to market…
The document considers whether market beta should be estimated using raw returns or returns in excess of the risk-free rate. In a single-period setting, subtracting a constant risk-free rate from both asset and market returns does not change their covariance…
The document outlines several ways to assess whether a candidate signal adds useful return information. Suggested checks include risk-adjusted performance and tail risk, regression against established factor models to examine the intercept, trading costs and…
The document discusses where to obtain daily European value factor returns and why a single universal definition of a factor does not exist. Commercial risk models can provide factor breakdowns, but their factor definitions differ. A researcher seeking a…
The document outlines the Daniel, Grinblatt, Titman, and Wermers approach to evaluating stock strategies or funds against characteristic-matched benchmarks. It describes forming 125 portfolios sorted by size, book-to-market, and momentum, then assigning…
The document discusses econometric assumptions and alternatives for applying the Fama–MacBeth procedure to asset returns. Its main methodological point is that the procedure can accommodate cross-sectional correlation among errors, while the cited answer…
The document explains a CAPM derivation that relates an asset’s expected return to its covariance with the market portfolio. Beta is the asset-market covariance divided by market variance. Rewriting the expected-return equation shows that the risk term can…
This discussion asks whether a crypto strategy’s statistically significant intercept from a regression on established equity factors provides a fair measure of skill. It frames the issue as benchmark choice: an alpha is measured relative to the factors…
This document explains how to distinguish the finite-sample Gibbons, Ross, and Shanken F-test from an asymptotic chi-square test when assessing whether multiple time-series regression intercepts are jointly zero. The F-test is described under assumptions of…
The discussion asks how to distinguish risk factors from anomalies and whether an observed return pattern becomes a factor simply by adding it to a regression. One answer frames risk premia as compensation for bearing systematic risks, while anomalies may…
The document explores practical estimation questions in the Fama-French family of factor models. It describes estimating a stock's factor loadings with a time-series regression, then asks how to forecast factor premiums when historical averages may not be…
The document addresses how to estimate rolling cross-sectional return betas and out-of-sample slopes when studying expected stock returns across size groups using Fama–MacBeth regressions. It asks whether to estimate slopes within each size group or across…
The document explains how to estimate total and idiosyncratic volatility for an individual stock over a fiscal year. Total volatility is the sample standard deviation of daily returns, annualized by multiplying by the square root of the number of trading…
The document frames covariance forecasting as a trade-off between estimation error and model misspecification. A sample covariance matrix makes few structural assumptions but can be noisy when many assets or factors are estimated. A highly structured model,…
The document asks which platforms can support quantitative equity research and portfolio management while reducing time spent preparing data and handling foundational analysis. Responses name services for data, factor modeling, portfolio analytics,…
The document addresses how to construct the investable stock universe that existed at each historical rebalancing date. This matters when backtesting value strategies, because current ticker lists omit delisted securities and can introduce survivorship bias.…
The document describes a factor-research workflow: build long-short strategy returns from cross-sectional z-scores of predictive factors, run principal component analysis on the time series of those returns, and retain a subset of components. The researcher…
The document outlines a backward calculation for estimating a company’s earnings from a limited set of financial ratios and working-capital data. Starting with average accounts receivable and the time needed to collect payment, it estimates annual sales…