- Predictability Of Time-Varying Jump Premiums: Evidence Based On Calibration
- Kent Wang, Yuqiang Guo
- Australian Journal of Management 2014, Vol. 39(3) 369– 394
- 2301 20160221 () Views:24475
- This study supplies new evidence regarding the predictive power of jumps for conditional market returns
and volatilities. We change the constant jump intensity as in the Liu et al. and Du models with time-varying
intensity following an autoregressive conditional jump intensity process and a squared Bessel process, and
apply calibrated jump premiums to predict excess market returns and volatilities. We show that all calibrated
jump premiums have significant predictive power in-sample and out-of-sample. We find that in the US
market Liu et al.’s model forecasts excess returns and volatilities better. The autoregressive conditional
jump intensity process of jump intensity predicts excess returns better, and the squared bessel process
forecasts volatilities better. In the Australian market we find that the model with autoregressive conditional
jump intensity process of jump intensity predicts Australian market returns and volatilities better.
- JEL-Codes: C13; C14; G10; G12
- Keywords: Equity premium, jump intensity, jump premium, stock return predictability, volatility predictability
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