Chinese_Firms_ML_Final.pdf (987.65 kB)
Why are some Chinese firms failing in the US capital markets? A machine learning approach
journal contribution
posted on 2023-06-10, 02:41 authored by Gonal ColakGonal Colak, Mengchuan Fu, Iftekhar HasanWe 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.
History
Publication status
- Published
File Version
- Accepted version
Journal
Pacific Basin Finance JournalISSN
0927-538XPublisher
ElsevierExternal DOI
Volume
61Page range
1-22Article number
a101331Department affiliated with
- Accounting and Finance Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2022-02-22First Open Access (FOA) Date
2022-02-22First Compliant Deposit (FCD) Date
2022-02-21Usage metrics
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