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Estimating Factor Models for Multivariate Volatilities: An Innovation Expansion Method

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Proceedings of COMPSTAT'2010

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.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Statistics, University of Strathclyde, 26 Richmond Street, Glasgow, G1 1XH, UK

    Jiazhu Pan

  2. Division of Statistics, University of California at Davis, Davis, CA, 95616, USA

    Wolfgang Polonik

  3. Department of Statistics, London School of Economics, London, WC2A 2AE, UK

    Qiwei Yao

Authors
  1. Jiazhu Pan
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  2. Wolfgang Polonik
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  3. Qiwei Yao
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Corresponding author

Correspondence to Jiazhu Pan .

Editor information

Editors and Affiliations

  1. Centre de Recherche INRIA Paris-Rocquenc, Domaine de Voluceau, Le Chesnay cedex, 78153, France

    Yves Lechevallier

  2. , chaire de statistique appliquée, CNAM, rue Saint Martin 292, Paris, 75003, France

    Gilbert Saporta

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Pan, J., Polonik, W., Yao, Q. (2010). Estimating Factor Models for Multivariate Volatilities: An Innovation Expansion Method. In: Lechevallier, Y., Saporta, G. (eds) Proceedings of COMPSTAT'2010. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2604-3_28

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