Fitting Vast Dimensional Time-Varying Covariance Models

35 Pages Posted: 9 Mar 2009 Last revised: 7 Oct 2019

See all articles by Cavit Pakel

Cavit Pakel

Bilkent University - Department of Economics

Neil Shephard

Harvard University

Kevin Sheppard

University of Oxford - Department of Economics; University of Oxford - Oxford-Man Institute of Quantitative Finance

Robert F. Engle

New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER); New York University (NYU) - Volatility and Risk Institute

Date Written: September 12, 2017

Abstract

Building models for high dimensional portfolios is important in risk management and asset allocation. Here we propose a novel and fast way of estimating models of time-varying covariances that overcome an undiagnosed incidental parameter problem which has troubled existing methods when applied to hundreds or even thousands of assets. Indeed we can handle the case where the cross-sectional dimension is larger than the time series one. The theory of this new strategy is developed in some detail, allowing formal hypothesis testing to be carried out on these models. Simulations are used to explore the performance of this inference strategy while empirical examples are reported which show the strength of this method. The out of sample hedging performance of various models estimated using this method are compared.

Keywords: Composite likelihood, dynamic conditional correlations, multivariate ARCH models, volatility

Suggested Citation

Pakel, Cavit and Shephard, Neil and Sheppard, Kevin Keith and Engle, Robert F., Fitting Vast Dimensional Time-Varying Covariance Models (September 12, 2017). NYU Working Paper No. FIN-08-009, Available at SSRN: https://ssrn.com/abstract=1354497

Cavit Pakel

Bilkent University - Department of Economics ( email )

Ankara, 06800
Turkey

Neil Shephard

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

Kevin Keith Sheppard

University of Oxford - Department of Economics ( email )

Manor Road Building
Manor Road
Oxford, OX1 3BJ
United Kingdom

University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )

Eagle House
Walton Well Road
Oxford, Oxfordshire OX2 6ED
United Kingdom
+44 1865 616 613 (Phone)

HOME PAGE: http://www.oxford-man.ox.ac.uk

Robert F. Engle (Contact Author)

New York University (NYU) - Department of Finance ( email )

Stern School of Business
44 West 4th Street
New York, NY 10012-1126
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

New York University (NYU) - Volatility and Risk Institute ( email )

44 West 4th Street
New York, NY 10012
United States

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