Working Papers

"Mind the Gap: The Non-Fundamental Role of Earnings Days", with Azi Ben-Rephael and Steffen Hitzemann

Revise and Resubmit

Abstract: We construct a new measure that captures the disparity between the market reaction to earnings information and the earnings surprise ("Return-Earnings Gap", "REG"). High REG positively predicts analyst forecast errors and a build-up of firm mispricing (overvaluation) over several quarters. Future analyst errors are particularly increased and accompanied by stronger mispricing when REG provides confirming information. A simple model for the dynamic expectation formation between different market participants corroborates these findings. Overall, our results reveal how the market’s (mis)reaction feeds back into the belief formation of analysts and investors, leading to a slow correction of firm mispricing.

Presented at: Rutgers Business School, Texas A&M, AFA Ph.D. Student Poster Session 2022, Midwest Finance Association Annual Meeting 2022, TBEAR Network Asset Pricing Workshop 2022, China International Conference in Finance 2022, Research in Behavioral Finance Conference 2022, Financial Management Association Annual Meeting 2022, Finance Down Under Conference 2023, Annual Bristol Financial Markets Conference 2023

"Do Stocks Lead Bonds? New Evidence from Corporate Bond ETFs", with Hao Jiang and Sophia Li

Abstract: We study the dynamic information flows between stock and corporate bond markets. Using accurately measured returns on corporate bond exchange-traded funds (ETFs), we find that returns on a portfolio of stocks of firms issuing the bonds in the ETFs positively predict corporate bond ETF returns, but not vice versa. The return predictability is stronger for ETFs tracking the indices of corporate bonds with lower credit ratings and higher yields.  By contrast, a randomly formed stock portfolio does not predict the ETF returns. These results are consistent with the notion of gradual information diffusion across asset markets.

Presented at: Rutgers Business School, Financial Management Association Annual Meeting 2022, 6th Shanghai-Edinburgh Fintech Conference, 2023 XJTLU AI and Big Data in Accounting and Finance Conference, 36th Australasian Finance and Banking Conference

"Analysts' Revision Ratio", with Azi Ben-Rephael

Abstract: We construct a measure that captures changes in analysts' expectations based on their earnings forecast revisions at different horizons. Our measure RevRatio is higher when analysts revise their annual forecast more than the quarterly forecast. For positive revisions, higher RevRatio results in significant subsequent reversals consistent with analysts' excessive optimism. For negative revisions, higher RevRatio results in modest price continuation. This asymmetry is consistent with recent market-level evidence on motivated beliefs and suggests that negative information incorporation is consistent with firm fundamentals. Our findings are robust to the inclusion of analyst revisions and consensus biases across multiple horizons.

"Does Sustainable Investing Dull Stock Reactions to Cash Flow News?", with Steffen Hitzemann, An Qin, Stanislav Sokolinski, and Andrea Tamoni

Abstract: The growing importance of sustainability criteria for investment decisions suggests that cash-flow news may become less significant in determining stock prices. We examine this proposition through earnings announcements, showing that stocks owned by sustainable investors are 45%–58% less sensitive to earnings news. This reduced sensitivity is accompanied by lower trading volume and persists post-announcement, indicating a lasting impact on price formation rather than temporary mispricing. We investigate the reasons behind the weaker earnings response and find that it cannot be explained by differences in earnings news content, market anticipation, or ownership by other investor types. Calibrating a flexible present value framework reveals that lower earnings persistence in high-sustainable-ownership stocks accounts for a large part of the effect. However, our analysis also implies a 1%–3% reduced discount rate for stocks with high sustainable ownership in order to fully align the model-implied price response with the observed data.

Miscellaneous Academic Publications

"A Comparative Static Analysis Approach to Derive Greek Letters: Theory and Applications", with Cheng-Few Lee

in Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning (eds. Cheng-Few Lee and John C. Lee), Chapter 86, pp. 2965-2999. World Scientific, 2020.

"Impacts of Time Aggregation on Beta Value and R2 Estimations Under Additive and Multiplicative Assumptions: Theoretical Results and Empirical Evidence", with Cheng-Few Lee and Yushan Tang

in Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning (eds. Cheng-Few Lee and John C. Lee), Chapter 114, pp. 3947-3984. World Scientific, 2020.