Gavin (Guanhao) Feng (City University of Hong Kong): Mosaics of Predictability

The Stanford AFTLab invites you to the AI & Big Data in Finance Research Forum (ABFR) webinar:

The webinar is on June 26, 9-10am Pacific Time (12-1pm ET)

Presenter: Gavin (Guanhao) Feng (City University of Hong Kong) 

Discussant: Allan Timmermann (UCSD) 

Zoom webinar link: https://stanford.zoom.us/j/93287277919?pwd=e06HPYJNKv1aKakabrYdWLM1cFYtev.1

Meeting ID: 932 8727 7919

Passcode: 681721

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Title: Mosaics of Predictability

Authors: Will Cong (Cornell University), Gavin (Guanhao) Feng (City University of Hong Kong), Jingyu He (City University of Hong Kong) and Yuanzhi Wang (City University of Hong Kong)

Abstract: We postulate that return predictability is an intrinsic and time-varying asset characteristic potentially related to the cross section of expected returns, instead of just an attribute of the chosen predictors or models. We develop a tree-based clustering method to gauge heterogeneous return predictability by grouping a panel of asset returns using high-dimensional asset characteristics and market-wide predictors. Our approach tells what types of assets exhibit greater return predictability under what market conditions, and empirically reveals substantial predictability heterogeneity in the U.S. equity market. Stocks with high earnings surprises, high earnings-to-price ratios, and low trading volumes exhibit the strongest predictability; predictability diminishes sharply with low market dividend yield but peaks with high dividend yield and low market liquidity. Out-of-sample, a new anomaly linked to investors' model misspecification easily generates monthly excess alphas exceeding 1%, and investing in highly predictable clusters significantly outperforms conventional benchmarks with Sharpe ratios approaching 2.

Bio of speaker: Gavin (Guanhao) Feng focuses on developing methodological solutions, including machine learning, Bayesian statistics, and financial econometrics, to address big data challenges in empirical asset pricing. His work has been published in leading journals such as the Journal of Finance, Journal of Financial Economics, Journal of Financial and Quantitative Analysis, Journal of Econometrics, and International Economic Review. He is the principal investigator for various external research grants, such as the HKRGC ECS and GRF grants, and the NSFC youth science fund. Gavin’s research has been acknowledged by practitioners, receiving research awards from INQUIRE Europe, Hong Kong Institute for Monetary and Financial Research, and the AQR Insight Award. Gavin is an associate professor of finance and statistics at the City University of Hong Kong. He earned his Ph.D. and MBA from the University of Chicago. 

Bio of discussant: Allan Timmermann is a Distinguished Professor at UCSD and holds the Dr. Harry M. Markowitz Endowed Chair in Finance and Investing. His research uses a mix of economic theory, data analytics, and econometric techniques to understand and predict the behavior of investors and prices in financial markets. His publications address topics such as whether financial returns are predictable and its implications for investors’ portfolio strategies, whether risk premia have vanished, whether mutual funds and pension funds add value through their investment decisions, and whether “star” fund managers exist. Timmermann has developed new statistical methods in areas such as forecasting under structural breaks, forecast combinations, Bayesian forecasting methods, and identification of luck versus skill in economic forecasting. He serves as the managing Co-editor of the Journal of Financial Econometrics and as an Associate Editor of leading journals in finance and econometrics including the Journal of Financial Economics, Review of Asset Pricing, Journal of Business and Economic Statistics, Journal of Economic Dynamics and Control, Journal of Applied Econometrics, Econometrics Journal, Journal of Asset Management, and Journal of Forecasting. Timmermann earned his Ph.D. from the University of Cambridge, a masters degree from London School of Economics and a Cand. Polit degree from University of Copenhagen.