On the estimation of non linear functions in stochastic volatility models. Issue 2 (17th January 2021) - Albano, Giuseppina; Giordano, Francesco; Perna, Cira
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.