Journal of Banking & Finance Vol. 37 No. 11 2013

Dynamic factor Value-at-Risk for large heteroskedastic portfolios

Sirio Aramonte^1,2; Marius del Giudice Rodriguez; Jason Wu^1,2

¹ Federal Reserve Board of Governors · ² Federal Reserve

Abstract

We propose a methodology that can efficiently measure the Value-at-Risk (VaR) of large portfolios with time-varying volatility and correlations by bringing together the established historical simulation framework and recent contributions to the dynamic factor models literature. We find that the proposed methodology performs well relative to widely used VaR methodologies, and is a significant improvement from a computational point of view.

DOI

10.1016/j.jbankfin.2013.07.038

Volume

37

Issue

11

Pages

4299-4309

Language

en

Sources

openalex crossref bibtex:phds-export.bib

Cite

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