AbstractThis thesis includes estimating the probability of informed trading, PIN, developed by Easley, Kiefer and O’Hara (1996, 1997a, 1997b), for a large sample of listed firms in China from 2002 to 2008, and I use PIN to explore two independent research questions in corporate finance.
First, the probability of informed trading is applied to explain the discount in value for firms with diversified business operations. Although aiming to increase firm value, the corporate diversification decision usually results in a firm value discount, for a variety of reasons, one of which is the transparency problem. My study directly tests the relation between the information asymmetry revealed from the stock market and the firm value discount due to diversification decision. The results show that the corporate diversification decisions result in a lower firm value in China, mainly because the diversified firms suffer from a higher level of information asymmetry or a lower level of transparency. After controlling for the measure of information asymmetry, the strategy of diversification itself does not reduce firm value.
Second, the probability of informed trading is applied to explain the payperformance sensitivity of CEO compensation in Chinese listed firms. The payperformance sensitivity measures the change in managerial compensation based on the change in shareholder wealth. A higher information asymmetry helps and encourages shareholders to spend more on incentivizing the management team. My results show that higher level information asymmetry is associated with higher payperformance sensitivity of CEOs in China. The result also holds if information asymmetry is approximated by analysts’ forecast errors.
According to the estimates of PIN in this thesis, Chinese firms are shown to exhibit a higher level of information asymmetry than what has been found in the U.S. market. The thesis ends with a brief discussion of the results and what future research could follow.
|Date of Award
|Michael Arthur FIRTH (Supervisor) & Yuanyuan ZHANG (Supervisor)