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.)
Peter M Robinson and
Paolo Zaffaroni
STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE
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.
Keywords: Long memory; two-shock model; stochastic volatility (search for similar items in EconPapers)
Date: 1997-01
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:cep:stiecm:320
Access Statistics for this paper
More papers in STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE
Bibliographic data for series maintained by ().