How Do I Assess Credit Risk in Derivatives?

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  • Written By: Toni Henthorn
  • Edited By: W. Everett
  • Last Modified Date: 15 April 2017
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When assessing the credit risk in derivatives, investors must deal with two types of credit exposure, current exposure and potential exposure. The mark-to-market price of a contract, which indicates the replacement cost in the event of a default by the counterparty, determines its current credit risk. Investors can calculate estimates of future replacement costs, or the potential exposure, by using a variety of probability analytical tests, such as option valuation models, historical simulation studies, and Monte Carlo studies. These tests provide two ways to estimate potential exposure, the maximum exposure and the expected exposure. Credit risk in derivatives changes over the life of the contract as the variables of the underlying contract change.

The current credit risk in derivatives is the easiest analysis to complete, since the current value of a contract determines the current exposure. For example, if an investor enters into a $200 million U.S. Dollar (USD), five-year interest rate swap in which the counterparty will pay him a fixed rate of five percent and he will pay the counterparty a floating rate of the London Interbank Offered Rate (LIBOR), then the current replacement cost is zero at the time of execution. The mark-to-market value of a four-year swap is 4.25 percent one year later. If the counterparty defaults one year into the contract, the current exposure, or replacement cost, is one 0.75 percent per year for four years and any unpaid swap payments due.


Credit risk in derivatives may also be assessed by replicating the volatility of the underlying variables, such as commodity prices, stock prices, and currency exchange rates, and simulating the effect of such shifts on the value of the derivative. An investor can model the maximum potential risk by examining such extreme adverse movements in the underlying variables that it would be highly unlikely that the situation could be worse than the maximum predicted risk. Expected exposure, on the other hand, deals with the best estimates of actual risk, using historical data, cash flow patterns of the underlying asset, and the nature of derivative involved. The predicted values for both maximum and expected exposures can be plotted on a graph with the percent of the notional value at risk on the y-axis and the years elapsed on the x-axis. Such graphs of the credit risk in derivatives show a concave or hump-backed curve that begins at zero percent risk.

When credit risk in derivatives is plotted over time, the concave configuration of the curve stems from two opposing forces. Initially, the curve rises and the credit risk increases for a period due to a diffusion effect, that is, the tendency for variables to change substantially from the initial value. This force is mitigated as time passes, however, by an amortization effect, in which the impact that a change in a variable has diminishes as the contract approaches its expiration date. In other words, the passage of time increases the likelihood that the replacement cost will increase, but this is offset by the fact that passage of time reduces the years over which any lost cash flow would need to be replaced.


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