Keywords: Jump-Diffusion Process, Realized variance, bi-power variation, realized jumps, jump volatility, credit risk premium.
Abstract: This paper extends the jump detection method based on bi-power variation to identify
realized jumps on financial markets and to estimate parametrically the jump intensity,
mean, and variance. Finite sample evidence suggests that jump parameters can be accurately
estimated and that the statistical inferences can be reliable, assuming that jumps are rare
and large. Applications to equity market, treasury bond, and exchange rate reveal important
differences in jump frequencies and volatilities across asset classes over time. For investment
grade bond spread indices, the estimated jump volatility has more forecasting power than interest
rate factors and volatility factors including option-implied volatility, with control for systematic
risk factors. A market jump risk factor seems to capture the low frequency movements in credit spreads.
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Last update: November 9, 2006