Optimal Right and Wrong Way Risk
Ignacio Ruiz, Ricardo Pach’on, Piero del Boca
This paper provides a comprehensive study on Right and Wrong Way Risk. In this paper, the authors…
- First explain the underlying source of this risk and how it applies to CVA as well as other credit metrics, together with a review of the available methodologies.
- Further to it, they provide a critique of the different models and their view as to which is the optimal framework, and why. This is done from the standpoint of a practitioner, with special consideration of practical implementation and utilisation issues.
- After that, they extend the current state-of-the-art research in the chosen methodology with a comprehensive empirical analysis of the market-credit dependency structure. They utilise 150 case studies, providing evidence of what is the real market-credit dependency structure, and giving calibrated model parameters as of January 2013.
- Next, using these realistic calibrations, they carry out an impact study of right-way and wrong-way risk in real trades, in all relevant asset classes (equity, FX and commodities) and trade types (swaps, options and futures). This is accomplished by calculating the change in all major credit risk metrics that banks use (CVA, initial margin, exposure measurement and capital) when this risk is taken into account.
- All this is done both for collateralised and uncollateralised trades.
- Finally, based on this impact study, the authors explain why a good right and wrong way risk model (as opposed to “any” model that gives a result) is central to financial institutions, furthermore describing the consequences of not having one.
The results show how these credit metrics can vary quite significantly, both in the “right” and the “wrong” ways. This analysis also illustrates the effect of collateral; for example, how a trade can have wrong-way risk when uncollateralised, but right-way risk when collaterallised.