Research
Working papers
Director appointment from shareholder connection: Evidence from common ownership
Presentation: ICGS 2023, SGF 2023, FMCG 2023
In this paper, I investigate the role of shareholder connection in the director appointment. I use common ownership as proxy of shareholder connection between the director and the dual-holding investors. I find the shareholder connection actually helps the director candidate more likely to be appointed. Firms with governance problems tend to hire the director with shareholder connection, after controlling other firm characteristics. On the side of shareholders, in the short -term, shareholders regard such director appointment as good news and experience an increase in their stock wealth. In the long-term, the voting support from shareholders positively relates to the strength of shareholder connection in the appointment. I also find the director appointments with shareholder connection bring improvements in corporate governance for firms, rather than improvements in operating performance. Directors also benefit from the appointments with more external job opportunities and internal compensation increase.
Geography Spillover of CEO forced turnover
(with Shan Zhao)
Presentation: France Inter Business Schools Seminar in Finance 2020, AFFI 2020, EFMA 2020
This paper analyzes the reaction of peer firms to nearby CEO force turnover and shows that this nearby shock can increase peers’ probability of resigning their CEOs. The negative peer reaction is consistent with excess monitoring, which may harm firm value. The reaction is stronger for small and well-performed peer firms. However, we find that independent directors with senior experience can weaken the negative reaction by reducing excess monitoring. Our results indicate that independent directors can be valuable monitors and resist the negative externality of this geography spillover.
Selected Work-in-Process
Selected Publications
The information value of M&A press releases
(with Florian Kiesel and Henry Leung)
Presentation: TU Darmstadt 2021, AFFI 2022, EFMA 2022, FMA Europe 2022, BRFGA 2022, AFA PhD Poster 2023
JOURNAL OF CORPORATE FINANCE, 2023
How do managers comment on merger transactions? By analyzing the initial public announcements of mergers and acquisitions (M&As) from 1995 through 2020 and extracting the linguistic sentiment from statements made by managers of target and acquirer firms, we provide new evidence on the informational value of M&A disclosures. We find that positive sentiment by the target firm results in positive returns for the target. However, when the target firm disagrees with the sentiment of the acquirer, this results in lower returns for the target. Further, when the target displays positive sentiment, this increases the likelihood of merger completion and shortens the time to completion of the deal. We decompose acquirer sentiment into manipulative and fundamental components and demonstrate that acquirer CEOs with low confidence produce M&A statements that are more manipulative. This suggests that, while sentiment in M&A disclosures contains information about fundamentals and managerial attitudes, it can be manipulated to protect the personal interests of managers.
(with Lu Wang, Jiangbin Wu, and Yanran Hong)
ENERGY ECONOMICS, 2022
Markov regime-switching technique is introduced into GARCH-MIDAS framework.
The model is developed by regime-switching both in short- and long-term volatility.
Our model does an excellent job in predicting renewable energy stock volatility.
Harnessing jump component for crude oil volatility forecasting in the presence of extreme shocks
(with Feng Ma, Yin Liao, and Yaojie Zhang)
JOURNAL OF EMPIRICAL FINANCE, 2019
We exploits additional jump-related information to revisit the predictive ability.
The three jump-related dimensions significantly improves the accuracy.
This study sheds new light on harnessing jump-related components for oil volatility forecasting.
Forecasting house prices using dynamic model averaging approach: Evidence from China
(with Yu Wei)
ECONOMIC MODELLING, 2017
We use dynamic model averaging approach to forecast the growth rate of housing price in China.
Both recursive and rolling forecasting methods are used to enhance the robustness of our results.
Google online search index is adopted as an additional predictor of housing price.