Event Studies: Detecting Abnormal Returns

• Main Authors: Ren-Chung Yang, 楊仁彰
• Other Authors: Shen-Yuan Chen
• Format: Others
• Language: zh-TW
• Published: 2001
• Online Access: http://ndltd.ncl.edu.tw/handle/68718889830658767277

碩士 === 銘傳大學 === 金融研究所 === 89 === Event studies offer useful evidence on how stock prices respond to information. Long-run abnormal returns research focus on delayed stock price reaction and abnormal performances, which are persisting for years following the specific events. To understand how information transmits to stock prices, it must observe long-run stock performance. This paper use firms listed on Taiwan Stock Market with available data on the monthly return, different pricing model, testing statistics, and estimating benchmark, to test which methods are better on long-run abnormal returns estimation. 1. Using Cumulating Abnormal Return or Buy-and-Hold Abnormal Return to estimate long-run abnormal returns on Taiwan stock market is misspecified. 2. Estimating long-run abnormal returns by reference portfolios can improve skewness bias in random sample. Due to different industry characters, it still is misspecified in nonrandom sample, and become worst when events are clustering than events are not clustering. 3. Time series statistics in estimating event month abnormal return perform well in random sample when it uses test period standard deviation, but is misspecified in any other situation.