台灣股價漲跌資訊短期反應之研究─事件分析法之應用

Abstract

若市場對於資訊反應過度或不足，投資人將可利用此特性建構投資策略，賺取超額報酬。本研究以事件分析法探討類股及個股在事件後是否產生顯著之異常報酬，以判斷類股及個股對事件之反應情形，讓投資人在建構投資策略時得以參考。 由於已有許多研究證實系統風險會隨著時間變動，本研究以Bollerslev (1990) 提出的多變量自我相關條件異質變異模型（Multivariate GARCH model），使用2000年1月至2009年12月台灣經濟新報資料庫中上市公司之日資料，針對台灣八大類股指數及其中資本額前三大的股票估算隨時間變動的系統風險後，並配合CAPM模型計算預期報酬，分析在經過正事件及負事件後，短期內系統風險是否提高，以及是否出現顯著之異常報酬。 本研究以日漲跌超過6％為類股之事件，發現八大類股指數在正、負事件後均存在反應不足現象，而以連續漲停或連續跌停一至三日為個股之事件，發現部分上市公司股票在正事件後存在顯著為正之累積異常報酬，而在負事件後存在顯著為負之累積異常報酬，亦即也存在反應不足之現象。此外，無論是漲停事件或跌停事件，事件後之平均系統風險幾乎皆顯著高於事前平均水準。

If investors overreact or underreact to the news, they will be able to use the property to construct investment strategies to earn excess return. This paper applied event study to analyze whether the stock return generated significant abnormal returns. The evidence showed that systematic risk was unstable and time-varying. Therefore, this paper applied Bollerslev (1990) Bivariate GARCH model to estimate time-varying systematic risk, using the daily data in eight industries and twenty-four individual stocks of Taiwan from Jan. 2000 to Dec. 2009. This study applied CAPM model with time-varying systematic risk to calculate abnormal returns, then analyzed the short-term systemic risk and return change after positive and negative events. This research defined that the price went limit up or down for three days continuously as an event of an individual, and that the daily fluctuation was over 6% as an event of an industry index. The result shows there was significant cumulative abnormal return on stocks. The systemic risk in the post-event period was significant higher than the one in the pre-event period. The stock price revealed underreaction, but the phenomenon is different from stocks. In addition, almost all the system risk of stocks had increased significantly.