Noise Trading, Return Volatility and Price Performance of IPOs

Abstract

This study investigates long-run price performance of IPOs not only by circumventing newlisting and portfolio-rebalancing bias but also via the geometric Brownian motion model by decomposing average cross-sectional price performance into mean and volatility components to adjust the right-skewed distribution of long-run buy-and-hold returns. Meanwhile, based on the relationship between noise trading as well as volatility and mean component, this study also examines the existence of noise trading and its effect on price performance after offering. By examining 280 IPOs, the results show that as a whole, the magnitude of underpricing of IPOs in Taiwan is not much which is about 5%. In addition, the deterioration of long-term price performance is not severe. Nevertheless, noise trading exists in the IPO stage in traditional firms but not in hi-tech firms. In terms of firm characteristics, the reason that noise trading is not pervasive in hi-tech firms should be related to fewer retail investors in early aftermarket.