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Robust inference in single firm/single event analyses
Affiliation:1. Central Bank of Chile, Agustinas 118, 8340454 Santiago, Chile;2. Hunter College & Graduate Center, City University of New York, 695 Park Ave, New York NY 10065, United States;1. Department of Accounting, Antai College of Economics and Management, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai, 200030, China;2. Department of Accounting, Business School, National University of Singapore, Mochtar Riady Building, BIZ 1, # 07-30, 15 Kent Ridge Drive, 119245, Singapore;3. Institute of Accounting and Finance, Shanghai University of Finance and Economics, No.777 Guoding Road, Shanghai 200433, China;1. School of Accounting, Southwestern University of Finance and Economics, No. 555, Liutai Avenue, Wenjiang District, Chengdu, Sichuan, 611130, China;2. School of Computing and Information Systems, Singapore Management University, Singapore;3. School of Management, Fudan University, 670 Guoshun Road, Yangpu District, Shanghai, 200433, China;4. Silberman College of Business, Fairleigh Dickinson University, 285 Madison Avenue, Madison, NJ 07940, United States
Abstract:Single firm/single event (SFSE) studies are relevant in corporate finance. Since inference on abnormal returns in this context necessarily relies on the time series variance of these abnormal returns, the implied problem of heteroscedasticity is obvious, although hard to solve. We analyze robust inference in an SFSE setting using Monte Carlo and resampling experiments. Estimation is biased when the calibration and event period occur in different volatility regimes. We develop a unique specification test for these structural breaks. The most robust inference is obtained by using intraday data and a multiplicative component GARCH estimator.
Keywords:Event studies  Inference  Monte Carlo simulation  Volatility  Structural breaks
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