A Semiparametric Approach to Value-at-Risk, Expected Shortfall and Optimum Asset Allocation in Stock-Bond Portfolios

Xiangjin B. Chen (), Param Silvapulle () and Mervyn Silvapulle ()

No 14/13, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: This paper investigates stock-bond portfolios' tail risks such as value-at-risk (VaR) and expected shortfall (ES), and the way in which these measures have been affected by the global financial crisis. The semiparametric t-copula is found to be adequate for modelling stock-bond joint distributions of G7 countries and Australia. Empirical results show that weak (negative) dependence has increased for seven countries after the crisis, while it has decreased for Italy. However, both VaR and ES have increased for all eight countries. Before the crisis, the minimum portfolio VaR and ES were achieved at an interior solution only for the US, the UK, Australia, Canada and Italy. After the crisis, the corner solution was found for all eight countries. Evidence of "flight to quality" and "safety first" investor behaviour was found to be strong, after the global financial crisis. The semiparametric t-copula adequately forecasts the outer-sample VaR. These findings have implications for global financial regulators and the Basel Committee, whose central focus is currently on increasing the capital requirements as a consequence of the recent global financial crisis.

Keywords: Copula; semiparametric method; value-at-Risk; investment decision (search for similar items in EconPapers)
Date: 2013
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