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On the estimation of non linear functions in stochastic volatility models

Author

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  • Giuseppina Albano
  • Francesco Giordano
  • Cira Perna

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.

Suggested Citation

  • Giuseppina Albano & Francesco Giordano & Cira Perna, 2021. "On the estimation of non linear functions in stochastic volatility models," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 50(2), pages 387-399, January.
    • Handle: RePEc:taf:lstaxx:v:50:y:2021:i:2:p:387-399
    DOI: 10.1080/03610926.2019.1635700
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