Why Are Some Chinese Firms Failing in the US Capital Markets? A Machine Learning Approach

53 Pages Posted: 2 Aug 2021

See all articles by Gonul Colak

Gonul Colak

University of Sussex ; Hanken School of Economics

Mengchuan Fu

Bentley University

Iftekhar Hasan

Fordham University ; Bank of Finland; University of Sydney

Date Written: July 27, 2021


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 technique 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.

Keywords: initial public offerings, machine learning, China, underpricing, delistings, long-run returns, cross-listings, prediction

JEL Classification: C4, C53, C54, G30, G32, G33

Suggested Citation

Colak, Gonul and Fu, Mengchuan and Hasan, Iftekhar, Why Are Some Chinese Firms Failing in the US Capital Markets? A Machine Learning Approach (July 27, 2021). Pacific-Basin Finance Journal, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3894428

Gonul Colak (Contact Author)

University of Sussex ( email )

Jubilee Building
Brighton, BN1 9SN
United Kingdom

Hanken School of Economics ( email )

P.O. Box 479
Arkadiankatu 22
FI-00100 Helsinki, 00100

Mengchuan Fu

Bentley University ( email )

175 Forest Street
Waltham, MA 02145
United States
02453 (Fax)

Iftekhar Hasan

Fordham University ( email )

NEW YORK, NY 10023
United States

Bank of Finland ( email )

P.O. Box 160
Helsinki 00101

University of Sydney ( email )

P.O. Box H58
Sydney, NSW 2006

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