Conducting event studies with Asia-Pacific security market data |
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| Affiliation: | 1. Department of Business Administration, National Taichung University of Science and Technology, No. 129, San-Min Rd., Taichung City 404, Taiwan, ROC;2. Department of Economics, Soochow University, No. 56, Sec.1, Kuei-yang Road, Taipei 1004, Taiwan, ROC;3. Department of Finance, Chihlee University of Technology, No. 313, Sec. 1, Wunhua Road, Banciao District, New Taipei City 22050, Taiwan, ROC;4. Department of Finance and Cooperatives Management, National Taipei University, No. 151, University Rd., New Taipei City 237, Taiwan, ROC.;1. School of Accounting and Finance, Hong Kong Polytechnic University, Hong Kong;2. College of Economics, Sungkyunkwan University, Seoul, South Korea;1. School of Finance, Zhejiang Gongshang University, No.18, Xuezheng Street, Hangzhou 310018, China;2. Department of Banking & Finance, Tamkang University, No. 151, Yingzhuan Road, Tamsui District, New Taipei City 25137, Taiwan;3. Shanghai National Accounting Institute, No.200, Panlong Road, Qingpu District, Shanghai 201702, China;1. Faculty of Business and Commerce, Kansai University;2. Graduate School of Business and Finance, Waseda University |
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| Abstract: | We investigate the effectiveness of several well-known parametric and non-parametric event study test statistics with security price data from the major Asia-Pacific security markets. Extensive Monte Carlo simulation experiments with actual daily security returns data reveal that the parametric test statistics are prone to misspecification with Asia-Pacific returns data. Two non-parametric tests, a rank test [Corrado and Zivney (Corrado, C.J., Zivney, T.L., 1992, The specification and power of the sign test in event study hypothesis tests using daily stock returns, Journal of Financial and Quantitative Analysis 27(3), 465-478)] and a sign test [Cowan (Cowan, A.R., 1992, Non-parametric event study tests, Review of Quantitative Finance and Accounting 1(4), 343–358)] were the best performers overall with market model excess returns computed using an equal weight index. |
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