Counterparty Credit Risk : Modeling Exposure Profiles with Monte Carlo Simulation

Absztrakt (kivonat)

The aim of this thesis is to provide a well-grounded overview of the current practices and challenges of handling counterparty credit risk. In the first part the differences among the main financial risks, namely (1) market risk, (2) credit risk, and (3) operational risk were defined. Market risk arises from movements in market prices, like interest rates and stock prices. Market risk was in the focus for investment banks until the 2008 credit crisis. Counterparty credit risk is a special kind of credit risk, arising from derivatives transactions. Their bilateral nature – the fact that they can be both an asset and a liability during the transaction – makes it harder to mitigate counterparty risk than ‘traditional’ credit risk arising from lending activities. The concept of the credit value adjustment (CVA) was introduced as well. CVA accounts for the fact that financial transactions are not free of default risk, something that was not considered in pricing for a long time. Operational risk is the failure of internal processes, human errors and external events. They are getting more and more focus from regulators and banks alike. The second part of the thesis shows how Monte Carlo simulation can be used for measuring potential exposure. Monte Carlo simulation is a method for generating a large sample of possible market scenarios, and using these scenarios for calculating exposure profiles. Simulations were done for single plain vanilla financial derivatives. For a long option position, the potential exposure can never be negative, and it is a monotone growing function of time. Forwards are similar, however exposure resulting from them can be negative and positive as well. Swaps have the most interesting exposure profiles. Although the longer time horizons mean higher uncertainty for them as well, as there is no exchange of large principals at the end of a transaction, amortization also plays a part. Last but not least, the beneficial effect of netting agreements is shown with a portfolio consisting of four foreign exchange forward trades.