Semiparametric estimation of multi-asset portfolio tail risk

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.JEL classification: C51, G01, G11, G17.

Modelling Systemically Important Banks vis-à-vis the Basel Prudential Guidelines

“…Others, such as the paper of Brownlees and Engle (2017), introduced systemic risk measure (SRISK) to capture the expected capital shortage of a firm given its degree of leverage and marginal expected shortfall (MES) as the expected loss that an equity investor in a financial firm would experience if the overall market declines substantially. There are also alternatives using extreme value theory (EVT) to investigate contagion risk, such as the papers of Rocco (2014), Dias (2014), and Akhter and Daly (2017). Moreover, for comparison among models, Benoit et al (2011) tried to compare the theoretical systemic risk measures, and others, such as Brämer and Gischer (2013), identified the domestic systemically important banks (D-SIBs) in the Australian context using a modified Basel-indicator-based guideline.…”

Asymmetric dependence in international currency markets

“…Contagion refers to the risk that a shock in an asset leads to increased volatility and comovements of other assets (see also Forbes and Rigobon, (2002); Boyson et al (2010); and Allen et al (2012)). Indeed, the performance of global emerging market currencies shifted and altered contemporaneously during the peak of the financial crisis as never before in the recent history (see also Dias (2014); and Tolikas (2014) for informative readings on financial assets dramatic losses), providing anecdotal evidence for and resembling to contagion.…”