Stochastic volatility jump

In mathematical finance, the stochastic volatility jump (SVJ) model is suggested by Bates.[1] This model fits the observed implied volatility surface well. The model is a Heston process with an added Merton log-normal jump.

Model

The model assumes the following correlated processes:

dS=\mu S\,dt+\sqrt{\nu} S\,dZ_1+(e^{\alpha +\delta \varepsilon} -1)S \, dq
d\nu =-\lambda (\nu - \overline{\nu}) \, dt+\eta \sqrt{\nu} \, dZ_2
\operatorname{corr}(dZ_1, dZ_2) =\rho

[where S = Price of Security, μ = constant drift (i.e. expected return), t = time, Z1 = Standard Brownian Motion etc.]

References

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