Weikai Li Department of Finance The Hong Kong University of Science and Technology Clear Water Bay, Kowloon, Hong Kong SAR, PRC

Email: [email protected] Phone: +852-6577-9764

EDUCATION 2013- present Hong Kong University of Science and Technology

Hong Kong

PhD student in Finance 2011-2012

Tulane University, A. B. Freeman School of Business

New Orleans, LA

MSc in Finance 2007-2012

Zhejiang University, College of Economics B.A. in Economics

RESEARCH INTERESTS Empirical Asset Pricing; Merger & Acquisitions; Behavioral Finance WORKING PAPER “Is China’s Housing Price a Bubble?” with Qifei Zhu, 2011 TEACHING AND RESEARCH EXPERIENCE Teaching Assistant 2013 Fall

Research Assistant 2013 - present 2012 Fall 2011 Fall

Teaching Assistant FINA 5290: Derivative Analysis

Research Assistant for Prof. Laura Liu, HKUST Research Assistant for Prof. Jonathan Batten, HKUST Research Assistant for Prof. David A. Lesmond, Tulane University

FELLOWSHIPS, HONORS AND AWARDS 2012 – present HKUST Postgraduate Studentship 2010

Sumitomo Mitsui Banking Corporation Scholarship

2011

SHU PING outstanding scholarship

2009

National Scholarship (top 1% students for academic excellence)

2009

First-class Scholarship, Zhejiang University

2009

First Prize in calculus competition in Zhejiang Province

LANGUAGE & COMPUTER SKILLS Language: Native in Mandarin, Fluent in English

Hangzhou, China

Computer Skills: SAS, STATA, MATLAB, C programming Database: CRSP, COMPUSTAT, I/B/E/S, Thomson Reuters, Bloomberg, DataStream PAPER ABSTRACTS “Is China’s Housing Price a Bubble?” with Qifei Zhu, 2011 Rising housing price is one of biggest concern in recent China. But whether there exists significant price bubble in nation-wide housing market is still in debate. In this paper, we try to address this question by analyzing the ratio of price to various fundamental factors, by comparing with other countries in the same period, by dissecting into different regions and by comparing the equilibrium price implied by economic development and urbanization with actual price. Our finding tends to support that no remarkable house price bubble exists nationwide, where rising price is well based on fundamentals. However, regional differences do exist. In mega cities like Beijing and Shanghai, price soared far away from equilibrium value. While house price in inland cities like Nanchang and Zhengzhou experienced much smaller price increase and underperformed for a long period. We also find that land price, GDP per capita, personal disposable income and population density are the variables most important in explaining cross-sectional and time series price differences. Lastly, we summarize the regulation policies carried out by government to curb the rising price and doubt the effectiveness of these policies. “Misvaluations and Merger & Acquisitions: evidence from China,” 2011 The empirical results regarding to stock market’s reaction to acquiring firms’ announcement are mixed. Different theories have been proposed to reconcile the empirical observations with different incentives to make M & A decisions. In this paper, I employed the behavioral approach, examining the relationship between market valuations of acquirers’ equity with announcement effect. By testing dataset of 123 Merger & Acquisitions activities in China from 1997-2007, I find strong support that when equity market is overvalued, stock market react to M &A announcements negatively and vice versa. The story behind is that in China, largest shareholders usually control the company and daily operations. When their stocks are overvalued, they can’t sell to profit because laws usually force a period of lockup. The only way they can benefit from market overvaluation is to use the overvalued equities to acquire other companies’ hard assets. A simple model was calibrated to derive the conditions under which the M & A decisions will be made. Greater overvaluation of acquirers’ stock leads to more negative synergies and stock price movement. Also, higher concentration of ownership makes the problems severer. Further regression tests verified the model’s predictions.