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 develops a first-order approach to immunizing a bond portfolio against nonparallel interest-rate shifts. It approximates each bond’s price change by differentiating its discounted cash flows with respect to rates at each maturity, producing…
The document surveys ways to combine fundamental, market, analyst, and alternative data in quantitative investment analysis despite their different observation frequencies. One option is to resample inputs to a common frequency; another is to train separate…
The document asks how to interpret Fama–French three-factor regressions on portfolios sorted by book-to-market. The reported pattern is that the low book-to-market portfolios have insignificant intercepts and factor loadings, the higher book-to-market…
The document proposes a way to compare mutual funds grouped by holdings-based investment style. For each style, construct both an equally weighted portfolio and a value-weighted portfolio from the funds’ quarterly returns. These alternative aggregations show…
The document explains how to interpret a Carhart four-factor regression when evaluating a portfolio or trading strategy. Rather than treating a coefficient as a direct comparison between individual small and large companies, it frames the factor coefficients…
The document considers whether a panel model with industry fixed effects is suitable for estimating the Fama-French five-factor alphas of many industry portfolios. The factors can be common across industries and vary over time; constructing separate factor…
The document raises the problem of inconsistent definitions of the quality factor in financial research and investment practice. It notes that some studies emphasize a single accounting measure, such as gross profits relative to assets, while index providers…
The document examines whether removing factor exposure from a trading signal or from forward returns produces the same performance estimate. With a projection matrix P and residual-maker M = I − P, it writes the strategy’s cross-sectional return as the inner…
The document explains what the left-hand side and intercept mean in factor regressions, using questions about comparing stocks and choosing a benchmark. An excess return is the difference between two portfolio returns, so a regression can model an asset’s…
The document investigates a claim that portfolio positions proportional to forecast returns maximize an alpha strategy’s information ratio. It relates the question to mean-variance portfolio theory, treating returns relative to a benchmark as analogous to…
The document surveys ways to study relationships among time series, including covariance, correlation, principal component analysis, factor analysis, cointegration, information measures, graph theory, and clustering. Its central question is whether these…
The document examines a proposed return model combining Fama-French factors with industry random intercepts. The modeler reports a strong relationship between residuals and fitted values and suspects that correlations among industry effects or a nearly…
The document describes a Fama–MacBeth cross-sectional regression of stock excess returns on idiosyncratic volatility, log market capitalization, book-to-market, and beta. The researcher reports statistically significant coefficients and says the…
The document addresses whether industry portfolio returns from Kenneth French's data library can be converted into historical prices. Its answer is that the portfolios are collections of stocks and do not have a single underlying traded price series. Returns…
The document introduces a beta-based long–short idea: short assets with higher market beta and buy assets with lower beta, with the aim of profiting across bullish and bearish markets. The response connects this concept to the betting-against-beta literature…
The document surveys lower-cost sources for historical financial statements, aimed at students or researchers who need panel data on US companies. The requested fields include balance-sheet, income-statement, and cash-flow items, along with ticker, period…
The document outlines a practical workflow for stock factor investing: define an investible universe, collect and process factor data, then rank or score securities. It describes several ways to turn scores into holdings, including selecting a subset and…
The document explains how to estimate alpha for many funds at once using the Fama–French three-factor model. It arranges each fund’s returns in a separate column, subtracts the risk-free rate to form excess returns, and constructs a shared factor matrix with…
The document considers turning an investor’s discretionary stock selection into a systematic screening process. Candidate inputs include institutional holdings disclosures, repurchases, insider trades, expectations, fallen-angel ratings, enterprise value…
The document explains aggregate volatility as an estimated quantity used in studying whether marketwide volatility is priced in stock returns. In the cited research, changes in the VIX serve as a proxy for innovations in aggregate volatility. This is a…
DGTW adjusted returns measure a stock’s performance relative to a characteristic-matched benchmark. For each stock, the method subtracts the return of a portfolio of firms assigned to matching groups based on market equity, market-to-book ratio, and prior…
The document examines why highly profitable firms might earn higher average returns despite appearing safer. It reviews several ways to measure profitability and presents two real-options explanations. One links profitable firms to a greater share of assets…
The document discusses how to assess whether an asset pricing model needs an additional factor, using the size factor in a three-factor model as an example. A factor’s average return alone does not determine whether it can be removed: dropping it can change…
The document distinguishes three return measures used to assess a security or portfolio. Active return compares an investment’s return with the market return. Excess return compares it with the risk-free rate, while market excess return is the market’s…