Inference for Stochastic Volatility models: a sequential approach
نویسندگان
چکیده
In this paper we propose a sequential Monte Carlo algorithm to estimate a stochastic volatility model with leverage effect. Our idea relies on the auxiliary particle filter method that allows to sequentially evaluate the parameters and the latent processes involved in the dynamic. An empirical application on simulated data is presented to study some empirical properties of the algorithm implemented.
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