On the estimation of non linear functions in stochastic volatility models

Giuseppina Albano, Francesco Giordano and Cira Perna

Communications in Statistics - Theory and Methods, 2021, vol. 50, issue 2, 387-399

Abstract: This paper focuses on the inference of suitable generally non linear functions in stochastic volatility models. In this context, in order to estimate the variance of the proposed estimators, a moving block bootstrap (MBB) approach is suggested and discussed. Under mild assumptions, we show that the MBB procedure is weakly consistent. Moreover, a methodology to choose the optimal length block in the MBB is proposed. Some examples and simulations on the model are also made to show the performance of the proposed procedure.

Date: 2021
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DOI: 10.1080/03610926.2019.1635700

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