Colak, Gonul, Fu, Mengchuan and Hasan, Iftekhar (2020) Why are some Chinese firms failing in the US capital markets? A machine learning approach. Pacific Basin Finance Journal, 61. a101331 1-22. ISSN 0927-538X

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Abstract

We study the market performance of Chinese companies listed in the U.S. stock exchanges using machine learning methods. Predicting the market performance of U.S. listed Chinese firms is a challenging task due to the scarcity of data and the large set of unknown predictors involved in the process. We examine the market performance from three different angles: the underpricing (or short-term market phenomena), the post-issuance stock underperformance (or long-term market phenomena), and the regulatory delistings (IPO failure risk). Using machine learning techniques that can better handle various data problems, we improve on the predictive power of traditional estimations, such as OLS and logit. Our predictive model highlights some novel findings: failed Chinese companies have chosen unreliable U.S. intermediaries when going public, and they tend to suffer from more severe owners-related agency problems.

Item Type:	Article
Schools and Departments:	University of Sussex Business School > Accounting and Finance
SWORD Depositor:	Mx Elements Account
Depositing User:	Mx Elements Account
Date Deposited:	22 Feb 2022 09:03
Last Modified:	22 Feb 2022 10:00
URI:	http://sro.sussex.ac.uk/id/eprint/104489

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