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Credit risk in derivatives has two types of exposure: current and potential. Current exposure is determined by a contract’s market price while potential exposure can be estimated using probability analytical tests. Credit risk changes as the underlying contract variables change over time. The concave shape of the credit risk curve is due to the opposing forces of diffusion and amortization effects.
When assessing credit risk in derivatives, investors must deal with two types of credit exposure, current exposure and potential exposure. A contract’s market price, which indicates the replacement cost in the event of a counterparty default, determines its current credit risk. Investors can calculate estimates of future replacement costs, or potential exposure, using a variety of probability analytical tests, such as option pricing models, historical simulation studies, and Monte Carlo studies. These tests provide two ways to estimate potential exposure, maximum exposure and expected exposure. The credit risk in derivatives changes over the life of the contract as the underlying contract variables change.
Current credit risk in derivatives is the easiest analysis to complete, as the current value of a contract determines current exposure. For example, if an investor enters into a $200 million dollar (USD) five-year interest rate swap in which the counterparty will pay him a five percent fixed rate 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 foreclosure. The mark value for the market of a four-year trade is 4.25 percent one year later. If the counterparty misses one year on the contract, the current exposure, or replacement cost, is 0.75 percent per annum for four years and any unpaid swap payments due.
Credit risk in derivatives can also be assessed by tracking the volatility of underlying variables, such as commodity prices, equity prices, and currency exchange rates, and simulating the effect of such changes 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 expected 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 the derivative involved. Predicted values for maximum and expected exposures can be plotted on a graph with percentage of notional value at risk on the y-axis and elapsed years on the x-axis. Such graphs of credit risk in derivatives show a concave or hump-backed curve starting at zero percent risk.
When credit risk in derivatives is plotted over time, the concave shape of the curve comes from two opposing forces. Initially, the curve rises and credit risk increases over a period due to a diffusion effect, that is, the tendency of variables to change substantially from the initial value. However, this force is mitigated over time by an amortization effect, in which the impact of a change in a variable diminishes as the contract approaches its expiration date. In other words, the passage of time increases the probability that replacement cost will increase, but this is offset by the fact that the passage of time reduces the years during which any lost cash flows would need to be replaced.
Smart Asset.
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