Is volatility clustering of asset returns asymmetric? |
| |
Institution: | 1. Department of Economics, Ryerson University, Toronto, Ontario M5B 2K3, Canada;2. Department of Economics, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada;3. School of Accounting & Finance and Department of Statistics & Actuarial Science, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada;1. Department of Economics, University of Haifa, Haifa 31905, Israel;2. Research Department, Federal Reserve Bank Boston, 600 Atlantic Avenue, Boston, MA 02210, USA;1. Schools of Economics: Interdisciplinary Center, Tel-Aviv University and CEPR, Israel;2. Zicklin School of Business, Baruch College, United States |
| |
Abstract: | Volatility clustering is a well-known stylized feature of financial asset returns. This paper investigates asymmetric pattern in volatility clustering by employing a univariate copula approach of Chen and Fan (2006). Using daily realized kernel volatilities constructed from high frequency data from stock and foreign exchange markets, we find evidence that volatility clustering is highly nonlinear and strongly asymmetric in that clusters of high volatility occur more often than clusters of low volatility. To the best of our knowledge, this paper is the first one to address and uncover this phenomenon. In particular, the asymmetry in volatility clustering is found to be more pronounced in the stock markets than in the foreign exchange markets. Further, the volatility clusters are shown to remain persistent for over a month and asymmetric across different time periods. Our findings have important implications for risk management. A simulation study indicates that models which accommodate asymmetric volatility clustering can significantly improve the out-of-sample forecasts of Value-at-Risk. |
| |
Keywords: | Volatility clustering Univariate time series copulas Realized kernel volatility Value-at-Risk |
本文献已被 ScienceDirect 等数据库收录! |
|