Estimating factor models for multivariate volatilities: an innovation expansion method

Jiazhu Pan, Wolfgang Polonik, Qiwei Yao

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

3 Citations (Scopus)
82 Downloads (Pure)

Abstract

We introduce an innovation expansion method for estimation of factor models for conditional variance (volatility) of a multivariate time series. We estimate the factor loading space and the number of factors by a stepwise optimization algorithm on expanding the "white noise space". Simulation and a real data example are given for illustration.
Original languageEnglish
Title of host publicationProceedings of COMPSTAT 2010
EditorsL. Lechevallier, G. Saporta
Place of PublicationHeidelberg
Pages305-314
Number of pages10
DOIs
Publication statusPublished - 2010

Publication series

NameA Physica Verlag Heidelberg product

Keywords

  • dimension reduction
  • multivariate volatility
  • factor models,

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