Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/29041
Title: Semiparametric estimation of multi-asset portfolio tail risk
Authors: Dias, Alexandra
First Published: 23-Jul-2014
Publisher: Elsevier
Citation: Alexandra Dias, Semiparametric Estimation of Multi-Asset Portfolio Tail Risk, Journal of Banking & Finance, Available online 23 July 2014
Abstract: When correlations between assets turn positive, multi-asset portfolios can become riskier than single assets. This article presents the estimation of tail risk at very high quantiles using a semiparametric estimator which is particularly suitable for portfolios with a large number of assets. The estimator captures simultaneously the information contained in each individual asset return that composes the portfolio, and the interrelation between assets. Noticeably, the accuracy of the estimates does not deteriorate when the number of assets in the portfolio increases. The implementation is as easy for a large number of assets as it is for a small number. We estimate the probability distribution of large losses for the American stock market considering portfolios with ten, fifty and one hundred assets of stocks with different market capitalization. In either case, the approximation for the portfolio tail risk is very accurate. We compare our results with well known benchmark models.
DOI Link: 10.1016/j.jbankfin.2014.05.033
ISSN: 0378-4266
Links: http://hdl.handle.net/2381/29041
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2014 Elsevier B.V. All rights reserved. Original: http://www.sciencedirect.com/science/article/pii/S0378426614002556 Policy checked with SHERPA/ROMEO on ingest.
Appears in Collections:Published Articles, School of Management

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