Detecting Seasoned Equity Offerings in Taiwan Stock Exchange Market– An Experiment of the Shorting Strategy

• Main Authors: Hung-HsuanChang, 張鴻軒
• Other Authors: Hsuan-Chu Lin
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/jh93gx

碩士 === 國立成功大學 === 財務金融研究所 === 101 === Seasoned equity offering (SEO) is a common way for firms to raise capital. However, it might not be a good choice for shareholders due to the price effect and long-term underperformance. To solve the plight, I utilize the findings of prior studies to create an approach to detect the issuance of SEO and use it as a benchmark to propose a shorting strategy. Through univariate and logit analyses, I explore the characteristics of SEO firms first. Then, I screen and examine all samples to pick up firms which match the SEO firm characteristics through quartile screen and logit prediction. The empirical results show that the logit regression prediction has better predictability which is about 50% but results in insignificant negative cumulative adjusted returns (CARs). Quartile screen has worse predictability which is about 10% but results in significant negative CARs. Based on the findings, we conclude that the logit regression is better for detecting purpose and the quartile screen is better for investment purpose.