Semiparametric estimation of multi-asset portfolio tail risk

Alexandra Dias*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)398-408
Number of pages11
JournalJournal of Banking and Finance
Early online date23 Jul 2014
Publication statusPublished - 1 Dec 2014


  • Multi-asset portfolios
  • Multivariate extreme value theory
  • Risk management
  • Tail probability
  • Tail risk
  • Value-at-Risk

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