Welcome to this week’s collection of links to the latest research and insights on quant investing. Below, you’ll find a curated list where each title links to the source for more information. Thank you for reading!
Empirical Asset Pricing
Same-Weekday Momentum (Da and Zhang)
A significant portion of stock momentum strategies is found to be explained by same-weekday momentum, attributed to seasonal patterns in fund flows and institutional trading.
Navigating Federal Reserve Policy with IFED (Rankin)
The paper presents an investment strategy that uses Federal Reserve policy signals to tilt an equity portfolio, and which has delivered a meaningful alpha out-of-sample over several years.
Monetary Policy Expectation Skewness and Stock Market Returns (Jiang et al.)
The cross-sectional skewness in short-rate forecasts is found to predict stock returns out-of-sample.
Factor Selection and Structural Breaks (Chib and Smith)
The authors develop a method for detecting breaks in factor selection over time, finding that only the market and the profitability factor are selected post 2005.
Factor Momentum in the Corporate Bond Market (Jiang et al.)
This paper constructs 10 factors for U.S. corporate bonds and finds evidence of time-series momentum among corporate bond factors.
Three Models of the Liquidity Premium (Baz et al.)
This paper provides an in-depth discussion on the liquidity premium and how to best measure it.
Social Media and Finance (Cookson et al.)
This is a survey article, providing a in-depth review of research on social media and finance.
Debtor carry (Eriksen and Kjaer)
The paper introduces a debtor FX carry strategy that mitigates crash risk while maintaining high risk-adjusted returns.
Lecture Notes
Machine learning and data science (Toomet)
Great lecture notes by Ott Toomet at the University of Washington.
Advanced course in Asset Management (Roncalli)
Great lecture notes by Thierry Roncalli covering topics such as portfolio optimization, Risk budgeting, Factor investing, ESG investing, ML optimization algos, and more.
Machine Learning and Large Language Models
Application of deep learning for factor timing in asset management (Panda et al.)
This paper evaluates the ability of a range of models, from OLS to neural networks, to time equity factors.
Dividend Forecasting in the Age of Machine Learning (Wang et al.)
The authors explore the ability of tree-based models to predict dividends and find them to generate superior dividend forecasts compared to relying on analyst forecasts or historical dividends.
Options
Better opt out: Revisiting the predictive power of options-implied signals (Honarvar and Howard)
The paper finds that the predictive power of options-implied signals for stock returns has significantly declined post-2008, and identifies look-ahead biases when backtesting option signals.
Transaction Costs and Cost Mitigation in Option Investment Strategies (O´Donovan and Yu)
Many proposed option strategies are shown to be unprofitable after transaction costs, but the authors suggest ways to mitigate costs and restore profitability to some strategies.
Blogs
A Simple Trick for Dealing with Overlapping Data (Robot Wealth)
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Brilliant!