Jun Pan

This paper presents a model for asset returns incorporating both stochastic volatility and jump effects. The return process is driven by two types of randomness: small random shocks and large jumps. The stochastic volatility process is affected by both types of randomness in returns. Specifically, in the absence of large jumps, volatility is driven by the small random shocks in returns through a GARCH(1,1) model, while the occurrence of a jump event breaks the persistence in the volatility process, and resets it to an unknown deterministic level. Model estimation is performed on daily returns of Samp;P~500 index using the maximum-likelihood method. The empirical results are discussed.

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