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 paper offers a factor-based explanation for the low-volatility anomaly. It applies an Adaptive Multi-Factor model, estimated with the Groupwise Interpretable Basis Selection algorithm, to identify basis assets associated with low- and high-volatility…
This study proposes a way to estimate the return associated with an individual stock’s risk that is not shared with similar stocks, even when the underlying risk factors are unknown. It constructs a peer replication portfolio by projecting each stock’s…
The document describes momentum portfolios ranked with reward-risk measures derived from the classical tempered stable distribution. It compares these portfolios with traditional momentum across asset classes and markets, assessing returns alongside…
This empirical study examines what drives variance, skewness and kurtosis risk premia for long-term equity investors. It uses profit and loss from a class of swaps on variance and higher moments of log returns as estimators, choosing contracts with…
The paper studies how to identify the smallest subset of risky assets that can span the mean-variance efficient frontier of a larger universe. It sets out conditions for identifying that subset and introduces an estimation and inference procedure designed to…
The document evaluates how asset characteristics jointly predict returns and how they can be used to build portfolios for investors with different risk preferences. It frames performance in terms of out-of-sample power utility and certainty equivalents, then…
This study models the decline of factor alpha as hyperbolic, deriving the form from a game-theoretic equilibrium model and comparing it with linear and exponential alternatives. Tests use eight Fama–French factors from 1963 to 2024. The authors report that…
This work studies factor models for the cross-section of daily returns across cryptocurrencies and other digital assets with exchange market data. It identifies a leading factor that appears to make a strong contribution to cryptoasset returns. The document…
This paper studies customer momentum, a return pattern in which a firm’s performance is positively related to the earlier performance of its customers. It reports that the effect is distinct from conventional price momentum and earnings momentum, while being…
This study replicates a deep-learning statistical-arbitrage approach that trades residuals from asset-pricing factor models. It applies the original method to a more recent out-of-sample period, using U.S. equity data from 2016 to 2024. The workflow follows…
The paper studies how cross-sectional momentum and contrarian portfolio returns change over time in Chinese stock markets. It evaluates their risk-premium relationship using the Capital Asset Pricing Model and the Fama–French three-factor model, then…
This study replicates prior research on reference-dependent preferences and stock returns in China, using Capital Gains Overhang (CGO) as a proxy for investors’ unrealized gains or losses. It examines how CGO interacts with five risk measures: market beta,…
The document develops a model for how firm characteristics can shape asset returns in equilibrium. It assumes investors' demands depend separately on firm characteristics and asset log-prices, while asset supply is exogenous and not driven by factors. With…
The document describes a cross-sectional seasonal effect: stocks that performed well in a particular calendar month tend to outperform again in that same month in later years. January is reported as the strongest month, but the pattern is said to extend…
The document describes an equity factor strategy that tilts a global stock portfolio toward companies whose ESG ratings have risen and away from those whose ratings have fallen. ESG momentum is measured over the prior 12 months, and the portfolio is…
This document describes a U.S. equity long-short strategy that first selects firms with the highest annual growth in total assets, then ranks those stocks by momentum. Asset growth uses the change from year t-2 to t-1, with July as the cutoff. Each month,…
The document describes a monthly cross-sectional strategy across 22 commodity futures. It calculates each contract’s skewness over the prior 12 months, buys three commodities with the lowest skewness, and shorts three with the highest, using equal weights…
The document describes a monthly strategy that blends momentum across equity factors with a broad market portfolio. It forms fast and slow signals from each factor’s recent one-month and twelve-month returns, ranks signal magnitudes to allocate factor…
The document describes a monthly, equal-weighted stock strategy that ranks NYSE, AMEX, and NASDAQ listings by short interest as a share of shares outstanding. It buys the lowest-short-interest decile and sells the highest-short-interest decile. The proposed…
This document describes a monthly equity strategy based on how similar the positive language in companies’ latest 10-K or 10-Q filings is to prior language. It uses a vendor’s cosine-similarity measure, ranks covered stocks into deciles, buys the…
The document describes a cross-sectional commodity futures strategy based on return asymmetry. It defines an IE measure as the difference between the counts of unusually large positive and negative daily returns, using a rolling 260-day window. At each month…
The document describes a U.S. stock market strategy that sorts companies by market capitalization and then ranks them by return on assets (ROA). ROA is calculated from quarterly income and assets from the prior quarter. The portfolio buys the three highest…
The net current asset value (NCAV) rule compares a company’s current assets, less all liabilities, with its market value; it excludes long-term assets. Graham’s rationale is that a sufficiently large discount may offer liquidation-value protection. The…
This strategy selects U.S. listed stocks with the lowest short-interest ratios, equally weights the first percentile of the ranked universe, and rebalances monthly. It uses the long side of the short-interest effect: a low level of shorting may indicate…