Ebook Counterparty Risk in the Over-The- Counter Derivatives Market
The over-the-counter (OTC) derivatives market has grown sizably in the past two years. Notional amounts of all categories of the OTC contracts reached almost $600 trillion at the end of December 2007. These include foreign exchange contracts, interest rate contracts, equity linked contracts, commodity contracts, and credit default swaps (CDS) contracts. Interest rate contracts continue to be the largest segment of this market comprising 66 percent of all OTC derivative market or about $400 trillion. Growth in the credit derivatives segment has been the fastest and the volume has more than doubled in the last year to about $60 trillion.
In this paper we are interested in counterparty risk that may stem from the OTC derivatives markets. The financial market turmoil of recent months has highlighted the importance of such risk. The risk is measured by losses that may result via the OTC derivative contracts to the financial system from the default (or fail) of one or more banks or broker dealers. Thus, in order to quantify counterparty risk, we calculate (expected) losses absorbed by the system under two different scenarios (described in Section II.D). For the estimation of (expected) losses, we define (i) the exposure of the financial system to specific financial institutions (FIs); and (ii) propose a novel methodology to estimate the probability that given that a particular institution (counterparty) fails to deliver, other institutions in the system would also fail to deliver.
With respect to a measure for exposure, we explain that the notional value of contracts does not provide any measure of exposure to quantify counterparty risk. Furthermore, gross market values of these contracts (essentially the total value of all the derivatives that are in and-out of the money) also do not provide any basis for counterparty risk measure. In fact, we discuss the importance of “netting” within and across all categories of OTC derivative contracts and, reducing this netted amount by the “assigned” cash collateral to come up with a relevant measure for exposure to counterparty risk. With respect to the probability measure, in order to estimate such conditional probabilities, our methodology accounts for linear(correlations) and non-linear distress dependence (DD) among the FI’s that have obligations in the OTC market, and how it changes in periods of distress. These are key technical improvements over models that account only for linear dependence, or assume dependence fixed throughout the economic cycle.
There has been very little (if any) research that looks at the full gamut of OTC derivatives market. Most of the recent discussion has been limited to credit derivatives (or the CDS market), that represents only 10 percent of the overall OTC derivatives market. One of the most cited recent works is by Barclays Bank where they acknowledge that “counterparty risk is theoretically present in all asset classes: FX derivatives, interest rate swaps, equity derivatives, commodity derivatives, and credit derivatives.” However, they limit their scope only to credit derivatives. They conclude that losses stemming from counterparty risk in credit derivatives market only could range from $36–$47 billion; these would largely stem from re-pricing—or gap risk—from a counterparty fail. Furthermore, they are cautious in not extrapolating their results to the other OTC derivative market. Other research has generally been of a less rigorous analytical nature. A good example includes Bloomberg Magazine’s July 2008 article, “The Risk Nightmare” that (again) limits the counterparty risk discussion to the credit derivative market only.
A market measure of counterparty risk index is provided by Credit Derivative Research (CDR). The index measures the average CDS spread of the largest 15 credit derivative counterparties and thus, it does not take into account distress dependence among counterparties. This is a key element to take into account if risks are to be estimated adequately. Nor does the CDR index take into account a measure of counterparty liability (i.e., the “exposure”). In contrast, we account for distress dependence—see Section II for details—where the joint and conditional probabilities of default are derived for the portfolio of banks and prime-brokers.
Section II presents our definition of counterparty risk, exposure to counterparty risk, as well as the methodology proposed to measure the probability that, given that a particular institution (counterparty) fails to deliver, other institutions in the system would also fail to deliver. In Section III, we present potential loss estimates for the banking system. As explained further below, the potential loss estimates calculated in this paper should not be confused with the losses estimated in the IMF’s October 2008 Global Financial Stability Report (GFSR), which are conceptually and methodologically quite different. Section IV concludes by summarizing our results in a policy framework for the stability of the banking system, and provides suggestions for reforms in addition to the steps that are presently discussed by regulators.
Contents
I. Introduction
II. Definitions and Methodology
- A. Counterparty Risk
B. Exposure of the Financial System to Counterparty Risk
C. Distress Dependence in the Financial System and Conditional Probability of Distress of Specific Financial Institutions
D. Loss Scenarios
III. Counterparty Risk: Empirical Estimation
- A. Counterparty Risk Exposure
B. Conditional Probability of Distress of Financial Institutions
IV. Conclusion and Policy Implications
References
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