Stock return variances: The arrival of information and the reaction of traders |
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| Affiliation: | 1. Faculty of Management and Economics, Dalian University of Technology, Dalian 116024, China;2. Department of Accountancy and Finance, University of Otago, 60 Clyde Street, 9016 Dunedin, New Zealand;3. Hull University Business School, University of Hull, HU6 7RX, United Kingdom;4. College of Management and Economics, Tianjin University, Tianjin 300072, China;5. China Center for Social Computing and Analytics, Tianjin 300072, China;1. Business School and Center of Finance and Investment Management, Hunan University, Changsha 410082, China;2. School of Economics and Management, Sichuan Normal University, Chengdu 610101, China;3. Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA;1. Anderson Graduate School of Management, University of California, Los Angeles, 110 Westwood Plaza, Suite C420, Los Angeles, CA 90095, USA;2. Robert H. Smith School of Business, University of Maryland, 4466 Van Munching Hall, College Park, MD 20742, USA;1. London Business School, Regent’s Park, London NW1 4SA, UK;2. Centre for Economic Policy Research, London EC1V 0DX, UK;3. European Corporate Governance Institute, Rue Ducale 1, 1000 Bruxelles, Belgium;4. Simon Business School, University of Rochester, Rochester, NY 14627, USA;5. Kelley School of Business, Indiana University, Bloomington, IN 47405, USA |
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| Abstract: | Asset prices are much more volatile during exchange trading hours than during non-trading hours. This paper considers three explanations for this phenomenon: (1) volatility is caused by public information which is more likely to arrive during normal business hours; (2) volatility is caused by private information which affects prices when informed investors trade; and (3) volatility is caused by pricing errors that occur during trading. Although a significant fraction of the daily variance is caused by mispricing, the behavior of returns around exchange holidays suggests that private information is the principle factor behind high trading-time variances. |
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