Dynamic factor Value-at-Risk for large heteroskedastic portfolios

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.

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Year of publication:	2013
Authors:	Aramonte, Sirio ; Rodriguez, Giudice ; del, Marius ; Wu, Jason
Published in:	Journal of Banking & Finance. - Elsevier, ISSN 0378-4266. - Vol. 37.2013, 11, p. 4299-4309
Publisher:	Elsevier
Subject:	Risk management \| Value-at-Risk \| Dynamic factor models

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Type of publication:	Article
Classification:	C53 - Forecasting and Other Model Applications ; c58 ; G32 - Financing Policy; Capital and Ownership Structure
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010703262