Credit risk is the risk resulting from uncertainty in a counterparty’s ability or willingness to meet its contractual obligations. This can materialize in default risk (the risk of loss when the counterparty fails to meet its obligations when due) and spread risk (the risk that a change in an obligor’s credit quality affects the value of a debt security and hence the credit spread). Over the last decade this credit risk has become a major concern to financial institutions and regulatory bodies, spurred by the worrisome developments in Asia, Russia and South- America over the last years. Consequently, the probing analysis and effective management of credit risks attached to portfolios of corporate bonds, loans and derivatives has gained great importance.
Several questions arise: What are the components of credit risk and how does credit risk affect the value of a loan? How can credit risk on the portfolio level be estimated? What is the contribution of individual instruments to the overall credit risk exposure and what are the effects of changes in the portfolio mix towards concentration or diversification? What vehicles can be used to transfer credit risk to third parties? The course aims at answering these questions, providing a clear and detailed understanding of the analysis, modelling, evaluation and management of portfolio credit risks.
Expected and potential credit losses have three ingredients: the current or potential credit exposure (the replacement cost of the transaction), the recovery rate (how much of the loan can be recovered if the borrower defaults), and the probability that the borrower will default while the loan is outstanding. We’ll discuss the estimation of each of these ingredients, emphasizing the market risk effect on the size of the potential credit exposure and the measurement of default probabilities. In the latter context, we pay attention to historical default rates as proxies for default probabilities and to credit risk ratings, as issued by ratings agencies like Moody’s, Standard & Poor’s and FitchIBCA. In modelling default probabilities over time, transition matrices serve a special role since they indicate the probability that a loan (or its issuer) will migrate from one credit risk class to another, indicating an amelioration or deterioration of credit quality. This leads in a natural way to the portfolio approach to credit risk analysis, since credit quality moves across loans will be correlated in a larger or smaller degree. Recognizing portfolio effects allows a proper quantification of the benefits of loan diversification and the costs of portfolio concentrations. In this respect the current BIS capital adequacy rules prove to be perverse, discarding both portfolio and market risk effects. The new capital adequacy framework under design leaves more room for the application of internal ratings and internal risk management systems.
After analyzing credit risk, the question rises how credit risk is incorporated in loan prices. We’ll outline state-of-the-art corporate bond pricing models and show how structural models and the more recently developed reduced form models yield insight in risk-adjusted loan pricing. Aside from credit risk in debt instruments, we’ll focus on measuring credit risk in derivative instruments, like swaps and forwards.
At the end of 1990, Bankers Trust developed the concepts of basket credit default options, credit swaps and total return swaps. Since then, the market for credit derivatives has shown a tremendous growth, both in volume and in the range of available products. Credit derivatives offer a systematic way of evaluating and transferring credit risk.
Circumventing some of the disadvantages of cash market transactions, banks and other financial institutions can use credit derivatives to dynamically manage their credit risk exposure to selected counterparties. In addition, credit derivatives allow lenders and investors to achieve credit exposures not otherwise available to them.
We will provide a typology of credit derivatives and show how they can be priced and be applied to adjust credit risk exposures.