This issue of The Journal of Risk includes contributions that enhance our understanding of risk-weighted assets in the context of value-at-risk as well as the estimation of this popular risk measure on the basis of multivariate returns over long holding periods. The issue also includes a practical evaluation of credit default swaps (CDSs), and an assessment of the dynamic correlation between credit risk and funding liquidity before, during and after the financial crisis of 2007-9.Risk-weighted assets figure prominently in regulatory capital guidelines (Basel II) and yet, given their firm-specific generation, are subject to potential model risk. In the first paper in this issue, "Modeling risk-weighted assets and the risk sensitivity of related capital requirements", Ernst Eberlein, Dilip Madan and Wim Schoutens offer an approach based on option data to complement the proprietary data that is used in the industry for model validation. In so doing, they develop a method that puts capital requirements within a systemic context that also incorporates some procyclicality in risk-weighted asset evaluations.
In the second paper in this issue, "Approximating the multivariate distribution of time-aggregated stock returns under GARCH" by Jean-Guy Simonato, a new method is presented that significantly reduces the time required to simulate value-at-risk estimates when returns are over substantially longer horizons than the standard daily scale. This technique is particularly significant given its accuracy within the context of very large computational complexity for problems of even a modest size.
The issue's third paper, "Dynamic linkages in credit risk: modeling the time-varying correlation between the money and derivatives markets over the crisis period" by Weiou Wu and David McMillan, contains empirical evidence linking funding liquidity and credit risk. In particular, the authors estimate the correlation between the TED spread, which measures the difference between short-term US Treasury and interbank interest rates, and CDS spreads. They find that this correlation became strongly positive during the financial crisis in 2008, in contrast to its prior levels at or slightly below zero.
In our fourth and final paper, "The valuation of credit default swaps including investor-counterparty-reference entity default correlation", Gunter Meissner, Dallyn Mesarch and Alexey Olkov propose a discrete model for assessing the effect of default correlation between the underlying asset, the investor and the counterparty on CDS pricing. This approach is particularly suitable for practical implementation as it is consistent with the periodic payments associated with CDS contracts. Furthermore, based on a numerical study, the authors show that default intensity has a much stronger impact on CDS spread than default correlation with other CDS entities.
Warrington College of Business Administration,
University of Florida