Yuekun Liu

Assistant Professor in Finance (Lecturer), Alliance Manchester Business School

Research Interest: Investments and Empirical Asset Pricing, with a focus on institutional investors and fund strategies.

Open to collaboration—please feel free to get in touch. 😊

You can find my CV and Papers here.

Contact: yuekun.liu@manchester.ac.uk

Research

Abstract: Evaluating market beta estimates is challenging because true betas are unobserved. We propose a new measure, gamma, which is proportional to the cross-sectional correlation between estimated and true betas, and can be derived from the covariance between estimated betas and returns. Crucially, our approach requires only minimal assumptions about the asset pricing model, does not require that true betas are correlated with expected returns, and can be applied to any beta estimator without relying on realized beta as a benchmark. Monte Carlo simulations show that gamma reliably ranks beta estimators across a wide range of asset pricing models and has high power in detecting even modest differences in accuracy. Empirically, we find that gamma produces rankings that differ markedly from traditional metrics when applied to U.S. stocks, portfolios, and actively managed equity mutual funds, revealing meaningful differences in estimation accuracy across commonly used beta estimators.

Presentations: Aalto University Finance Brownbag Seminar, Espoo, Finland, 2024, Helsinki GSE Seminar, Helsinki, Finland, 2024, 9th Annual Conference of the Society of Economic Measurement, Atlanta, Georgia, 2024, NVFEB, Rotterdam, Netherlands, 2024, AEA (poster session), San Francisco, CA, 2025, Bank of Finland, Virtual, 2025, Oxford-Man Seminar Series, Virtual, 2025, Quantitative Finance and Financial Econometrics, Marseille, Finance, 2025

CFA Society Australia Best Paper Award 2025 (Finance Down Under)

Rejected but Invited to Resubmit to the Journal of Financial and Quantitative Analysis

Abstract: Do factor investing funds successfully capture the premiums associated with academic factors? We explore this question using the growing number of factor investing funds that seek to capture those premiums. While, on average, such funds do not outperform, we find that the factor investing funds with the portfolios that most closely match their academic factors—determined using our novel, holding-based ‘active characteristic share’ measure significantly outperform those that less closely match. Furthermore, adjusting for stock size, we conclude that the answer to our question is “yes” for closely matching factor investing funds, which net of costs duplicate the paper performance of the long side of academic factors.

Presentations: University of Arkansas, Fayetteville, AR, 2022, Financial Management Association Annual, Atlanta, GA, 2022, NEOMA Business School, Virtual, 2023, CFR Cologne Seminar, Virtual, 2024, Católica Lisbon School of Business and Economics, Lisbon, Portugal, 2024, University of Manchester, Manchester, England, 2024, 4th Frontiers of Factor Investing, Lancaster, England, 2024, 16th Annual Hedge Fund Research Conference, Paris, France, 2025, Finance Down Under, Melbourne, Australia, 2025

Semifinalist for the FMA 2020 Best Paper Award in Investments.

Journal of Banking and Finance, Volume 173, April 2025

Abstract: The performance of corporate bond mutual funds tends to be estimated using models with limited empirical validation. We survey the literature to determine the models in use and develop a representative set of models. Testing that set of models, we find considerable variation in quality, with the most effective models sharing common traits. We recommend, among the tested models, the four-factor model proposed by Jones and Mo (2021). Regarding the stylized facts of corporate bond fund performance, our recommended model produces notable deviations from the prior literature and other models, including less evidence of positive alphas not attributable to luck.

Presentations: University of Arkansas, Fayetteville, AR, 2020, Financial Management Association Annual, Virtual, 2020, Midwest Financial Association, Virtual, 2021, Eastern Financial Association, Virtual, 2021, Louisiana Tech University, Ruston, LA, 2021, Montana State University, Bozeman, MT, 2021, Saginaw Valley State University, University Center, MI, 2022, Aalto University, Virtual, 2022