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 discussion compares principal component analysis (PCA) and clustering as ways to build risk models for portfolio optimization. PCA is presented as a method for reducing a set of risk variables to a smaller number of uncorrelated factors. Clustering…
The document compares smart beta, alternative indexes, and factor investing. Alternative indexes use weighting rules beyond market capitalization, including tilts toward momentum, value, smaller companies, or lower volatility, as well as fundamental measures…
The document considers whether assets with extreme estimated betas should be excluded when using CAPM to predict expected returns and calculate residual, or idiosyncratic, returns. The proposed model estimates monthly total returns against a global equity…
The document raises questions about different James–Stein shrinkage-factor formulas used to adjust estimated asset-class returns before mean-variance portfolio optimization. One expression uses the number of observations, a grand mean, and the inverse…
The document outlines how to simulate one-day returns for many stocks using factor-model inputs: factor returns, factor covariance, stock factor loadings, and idiosyncratic risk. It proposes drawing correlated factor shocks through a Cholesky decomposition,…
The document explains how to assess whether a proposed factor adds explanatory power to a Fama–French three-factor model. It distinguishes time-series regressions on sorted portfolios, which measure how much factor variation explains return variation, from…
Macro funds do not share one standard framework for managing risk or modeling returns. Their practices differ with each firm’s strengths, investment style, and willingness to use quantitative methods; some are less receptive to formal risk models than…
The document distinguishes factor evaluation from factor modeling. It asks whether a factor’s long-short portfolio return and statistical significance correspond to the factor return in a model where asset returns depend on factor exposures. The answer…
The document explains how to calculate the Lakonishok et al. herding measure from the fraction of active institutions buying a stock, the market-wide buy proportion, and an adjustment factor. The question asks how to derive that factor and how to aggregate…
The document addresses which book equity measure to use when replicating a monthly book-to-market variable in a study of expected stock returns. The accepted response infers that the intended numerator is common equity, even though the paper does not…
The document compares three ways of working with investment factors. One approach builds long-short portfolios by ranking stocks on a characteristic such as price-to-book and buying the highest-ranked group while shorting the lowest. The author notes that…
The document asks whether stock exposure to market, value, or momentum factors should be estimated using returns during factor drawdowns, since those losses may be linked to factor risk premiums. It also raises the estimation challenge: crash periods offer…
The discussion considers replacing discretionary Black-Litterman views with systematic signals. The proposed example estimates each stock’s residual return from a market model, standardizes residual averages by their volatility, and uses the difference…
The document addresses how to calculate each company’s percentile rank for dividend yield and PEG ratio within its industry, using a universe such as the S&P 500 Pure Value Index. The suggested workflow is to retrieve ticker, industry, PEG, and…
The document discusses the reported finding that stocks with greater sensitivity to innovations in aggregate volatility have lower average returns, and asks why such exposure might act as a hedge against market downside risk. It does not settle the puzzle;…
The document compares monthly Fama-French factor returns with values obtained by geometrically compounding the published daily series. It focuses on the market excess return and the SMB and HML factors, which are built from portfolios formed by size and…
The document asks how matrix notation expresses the ordinary least squares objective and how differentiation produces the estimator. It starts from the linear model, writes residuals as the observed response minus fitted values, and expands the residual sum…
The document discusses how accounting knowledge can matter across different quantitative finance roles. Its answers distinguish work focused on short-horizon research or derivatives pricing from roles involving fundamental equity selection, credit and…
The document describes a proposed zero-investment stock portfolio in which each asset's weight depends on observable state variables, such as factors related to stock performance. This is the parametric portfolio policy approach associated with Brandt and…
The document explains which stocks qualify for the annual Fama–French size and book-to-market portfolio sorts. Portfolios are formed at June end using market equity for size and book-to-market information based on prior fiscal-year book equity and December…
The document considers how to include valuation data in a regression when some companies have no meaningful positive price-to-earnings ratio because they are unprofitable. It raises two possible treatments: assigning those firms an artificially high P/E, or…
The document explains how to estimate a stock’s exposure to the Fama–French SMB and HML factors. The proposed method is a linear regression of the stock’s returns on the relevant factor returns; the resulting coefficients are the estimated factor betas.…
The document raises a research question about measuring the stability of factor loadings in models such as Fama–French or Carhart. It frames loading stability as a criterion for evaluating alternative ways to construct a risk factor, using a possible climate…
The note explains that an asset pricing factor does not have to be an excess return or even a traded portfolio. In a one-factor model where the factor is itself an excess return, its risk price can be read directly from its average value: the factor has a…