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Nonlinear Time Series with Long Memory: A Model for Stochastic Volatility - (Now published in 'Journal of Statistical Planning and Inference', 68 (1998), pp.359-371.)

Author

Listed:
  • Peter M Robinson
  • Paolo Zaffaroni

Abstract

We introduce a nonlinear model of stochastic volatility within the class of ?product type? models. It allows different degrees of dependence for the ?raw? series and for the ?squared? series, for instance implying weak dependence in the former and long memory in the latter. We discuss its main statistical properties with respect to the common set of stylized facts characterizing financial assets? returns time series dynamics, and apply it to several series of asset returns.

Suggested Citation

  • Peter M Robinson & Paolo Zaffaroni, 1997. "Nonlinear Time Series with Long Memory: A Model for Stochastic Volatility - (Now published in 'Journal of Statistical Planning and Inference', 68 (1998), pp.359-371.)," STICERD - Econometrics Paper Series 320, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    • Handle: RePEc:cep:stiecm:320
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