In the present paper we consider estimation procedures for stationary Stochastic Volatility models, making inferences about the latent volatility of the process. We show that a sequence of generalized least squares regressions enables us to determine the estimates. Finally, we make inferences iteratively by using the Kalman Filter algorithm.
Inference Methods for Stochastic Volatility Models / Cavicchioli, Maddalena. - In: INTERNATIONAL MATHEMATICAL FORUM. - ISSN 1312-7594. - STAMPA. - 8:(2013), pp. 369-375.
Inference Methods for Stochastic Volatility Models
CAVICCHIOLI, MADDALENA
2013
Abstract
In the present paper we consider estimation procedures for stationary Stochastic Volatility models, making inferences about the latent volatility of the process. We show that a sequence of generalized least squares regressions enables us to determine the estimates. Finally, we make inferences iteratively by using the Kalman Filter algorithm.
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