Dr. Chien-Feng Huang, professor of Department of Computer Science and Information Engineering, and Dr. Chih-Hsiang Chang, professor of Department of Finance analyze the IPO Investor Decision-Making Model by using AI technology.
Their research also was published in the SSCI International Journal “IAS(Investment Analysts Journal” and won IAS Journal Award 2017.
The study investigates whether the difference of the IPO issuing companies’ fundamentals impacts their price performance after listing and the significance of the disposition effect. Empirical results show that the IPO issuing companies’ fundamentals drive their first-day post-listing returns, one-year post-listing returns, and the significance of disposition effect. Additionally, the heuristic used to determine whether the IPO of an issuing company with superior fundamentals is a good one with price appreciation potential shows that IPOs with best (worst) fundamentals have higher (lower) first-day post-listing returns; and investors are more unwilling (willing) to sell the losing (gaining) IPOs with the best (worst) fundamentals. Furthermore, investors’ disposition behaviour has a limited impact on one-year post-listing returns, and the window-dressing in the issuing company’s financial statements before listing is useless to the improvement of an IPO’s long-term price performance.