## Electronic Journal of Statistics

### Weak dependence and GMM estimation of supOU and mixed moving average processes

#### Abstract

We consider a mixed moving average (MMA) process $X$ driven by a Lévy basis and prove that it is weakly dependent with rates computable in terms of the moving average kernel and the characteristic quadruple of the Lévy basis. Using this property, we show conditions ensuring that sample mean and autocovariances of $X$ have a limiting normal distribution. We extend these results to stochastic volatility models and then investigate a Generalized Method of Moments estimator for the supOU process and the supOU stochastic volatility model after choosing a suitable distribution for the mean reversion parameter. For these estimators, we analyze the asymptotic behavior in detail.

#### Article information

Source
Electron. J. Statist., Volume 13, Number 1 (2019), 310-360.

Dates
First available in Project Euclid: 9 February 2019

https://projecteuclid.org/euclid.ejs/1549681240

Digital Object Identifier
doi:10.1214/18-EJS1523

Mathematical Reviews number (MathSciNet)
MR3910486

Zentralblatt MATH identifier
1406.60028

#### Citation

Curato, Imma Valentina; Stelzer, Robert. Weak dependence and GMM estimation of supOU and mixed moving average processes. Electron. J. Statist. 13 (2019), no. 1, 310--360. doi:10.1214/18-EJS1523. https://projecteuclid.org/euclid.ejs/1549681240

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