Moment based estimation of supOU processes and a related stochastic volatility model

TL;DR

This paper develops a GMM-based estimation method for supOU processes and a related stochastic volatility model, demonstrating consistency and practical effectiveness while exploring long memory effects.

Contribution

It introduces a GMM estimation approach for supOU processes and stochastic volatility models, highlighting its consistency and practical performance.

Findings

GMM estimators are consistent for supOU processes.

The method performs well in practical applications.

Long memory effects influence the estimation results.

Abstract

After a quick review of superpositions of OU (supOU) processes, integrated sup\-OU processes and the supOU stochastic volatility model we estimate these processes by using the generalized method of moments (GMM). We show that the GMM approach yields consistent estimators and that it works very well in practice. Moreover, we discuss the influence of long memory effects.