2.6 Summary

This chapter has provided some context and background to counterparty risk, examining its importance in financial markets and links to other risk types. A number of basic points, such as the nature of the derivatives market and VAR methods, have been described. The need to mitigate counterparty risk, and the potential dangers in doing so, have also been introduced. The next chapter will define counterparty risk in more detail.

Notes

1. For a continuous distribution, VAR is simply a quantile (a quantile gives a value on a probability distribution where a given fraction of the probability falls below that level).

2. The precise relationship is that the capital is defined by the largest of the previous day's VAR and the average of the last 60 days multiplied by the supervisory factor of three or more.

3. Certain implementations of a VAR model (notably the so-called variance/covariance approach) may make normal distribution assumptions but these are done for reasons of simplification and the VAR idea itself does not require them.

4. The recent fundamental review of the trading book (see http://www.bis.org/publ/bcbs219.pdf) has recommended replacing VAR with a preferable measure of risk commonly known as expected shortfall.

5. Fischer Black had died in 1995.

6. Most VAR models tend to calculate this measure and then scale to the required 10-day horizon.

7. Between one and six violations is reasonable at the 95% confidence level, as discussed in more detail in Section 17.4.3. ...

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