Identifying Realized Jumps on Financial Markets
This paper extends the jump detection method based on bi-power variation and swap variance measures to identify realized jumps on financial markets and to estimate parametrically the jump intensity, mean, and variance. Such an approach does not require specifying and estimating the underlying drift and diffusion functions. Finite sample evidence suggests that the jump parameters can be accurately estimated and that the statistical inferences can be reliable relative to the maximum likelihood estimation, under the appropriate choice of jump detection test level and assuming that jumps are rare and large. The bi-power variation approach performs slightly better than the swap variance approach when the jump contribution to total variance is small. Applications to equity market, treasury bond, individual stock, and exchange rate reveal important differences in jump frequencies and volatilities across asset classes over time. For high investment grade credit spread indices, the estimated jump volatility has a better forecasting power than interest rate factors, volatility factors including option-implied volatility, and Fama-French risk factors.
Realized Jumps Realized Variance Jump-Diffusion Process Bi-Power Variation Variance Swap Contract Jump Volatility Credit Risk Premium
George Tauchen Hao Zhou
Department of Economics, Duke University, Box 90097, Durham NC 27708 Division of Research and Statistics, Federal Reserve Board, Mail Stop 91, Washington DC 20551 USA
国际会议
昆明
英文
1-49
2005-07-05（万方平台首次上网日期，不代表论文的发表时间）