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 explains how to derive daily stock returns relative to the Fama-French three-factor model. The question asks whether regression residuals represent daily outperformance, or whether one should subtract factor contributions, weighted by estimated…
The document discusses how to calculate portfolio returns when some constituent stocks have missing monthly returns, using a value-weighted portfolio as its example. It contrasts treating a missing return as zero with calculating the portfolio return from…
The document describes a factor attribution exercise for a backtested equity strategy. The researcher aggregates strategy returns monthly, obtains monthly Fama–French factor returns, and runs a multivariate regression. The resulting fit is low, prompting…
The document explains a decomposition of momentum profits into effects associated with cross-sectional differences in average returns and with the time-series behavior of returns. It relays a three-part formulation attributed to Lo and MacKinlay: market…
The document frames equity risk model construction as a set of methodological choices, including factor selection, matching the horizon to the analysis, cross-sectional versus time-series estimation, regression design, and adjustments to the covariance…
This document distinguishes beta as a statistical regression slope from beta's role in the Capital Asset Pricing Model (CAPM). In a single index model, beta is estimated from the covariance of an asset's excess returns with a factor's excess returns divided…
The discussion asks whether investors can access systematic risk premia through funds, indices, or exchange-traded products. It names carry, curve or term premium, size, value, momentum and trend, liquidity, and volatility as areas of interest, and notes…
The document explains how principal component analysis (PCA) is used to describe changes in yields across maturities. PCA finds eigenvectors of the covariance matrix of yield changes, ordered by their eigenvalues, which measure the variance captured by each…
The document considers how to choose a tradable universe for statistical arbitrage that models shared factors or indices and trades residuals. It contrasts liquidity cutoffs, selecting assets by their contribution to strategy performance, and using principal…
The document discusses ways to assess whether publicly traded U.S. companies may face bankruptcy, with the aim of informing decisions from short-term trading through long-term investing. One response suggests tracking financial ratios such as leverage,…
The note explains where to retrieve a company’s Standard Industrial Classification code when working with Compustat data through SQL. The question arises because the Compustat fundamentals table, comp.funda, exposes SICH but not a field named SIC, even…
The document discusses how to interpret negative cost of equity estimates produced from CAPM beta calculations. It argues that a negative expected return can be consistent with portfolio theory: an asset that offsets another asset’s risk may have a negative…
A negative average SMB return does not establish that large stocks outperformed small stocks: the observed estimate may be statistically indistinguishable from zero. The response illustrates this with Swedish market data, where the estimated monthly SMB…
The document asks how a Barra-style factor model estimates factor returns from stock exposures and realized returns. It describes the standard cross-sectional fit: choose factor returns so the exposure-weighted estimates for each stock best match observed…
Fama–French portfolio breakpoints are thresholds calculated from NYSE-listed stocks and then applied to stocks listed on the NYSE, AMEX, and NASDAQ. The explanation links this choice to differences in market capitalization across exchanges and the addition…
The document explains why empirical studies and Magic Formula screens often exclude financial companies and utilities. Financial firms have business models and balance sheets that make leverage difficult to interpret alongside leverage at nonfinancial…
The document explores the distinction between factor research and alpha research. A factor is framed as an exposure that explains a systematic component of returns or risk, while alpha is described as a forecast of idiosyncratic returns without a systematic…
The document discusses the equity risk premium as an expected return on the market factor and examines how its estimate behaves in CAPM and Fama–French three-factor asset-pricing tests. It cites a conservative US equity premium estimate of 3–4% and argues…
The document explains why a Fama–MacBeth cross-sectional regression may estimate a market risk premium even though market returns are observed. It distinguishes the time-series regression, which estimates each asset’s beta and alpha, from a cross-sectional…
The document explains Cochrane’s argument that variation in the dividend-price ratio must be associated with forecasts of future dividend growth, future returns, or both. If the ratio is stationary and tends to revert toward typical levels, an unusually high…
This exchange considers whether CAPM or a multi-factor asset-pricing regression requires the portfolio being analyzed to be efficiently diversified. The answer says statistically significant coefficients can still be interpreted when the portfolio does not…
The document considers how business-cycle conditions may affect the performance of asset-pricing models applied to industry portfolios. It proposes dividing monthly excess returns into recession and non-recession subsamples, with recession dates identified…
The document asks how to obtain size and value risk premia for a Fama–French three-factor cost-of-equity estimate after estimating factor betas. One response proposes constructing the HML and SMB zero-investment portfolios from historical equity data, using…
The document surveys several ways to group systematic trading strategies. Strategy families include trend and reversal approaches, price or technical methods, fundamental, yield, growth, and quality signals, as well as arbitrage, market making, sentiment…