CONCLUDING REMARKS
In the credit markets, all types of contracts with very few exceptions (e.g., commodities), are directly linked to counterparties. As discussed in this chapter, there are three main types of counterparties, the investor (lender), obligor (borrower) and the guarantor or protection seller.
The degree of credit quality of the guarantor must always be at a higher level than the obligor; this is not the case however for protection sellers who play the role of insurers against credit events by receiving premiums. Counterparties are characterized by a number of descriptive characteristics; most of them are used to identify the expected behavior characteristics whereas a few of them play a key role in concentration and systemic risk analysis. All counterparties have a certain probability to default at a future point in time. Structural and intensity models can be applied to identify and estimate default probabilities. Such probabilities have to be viewed in regard to risk-neutrality for pricing the credit portfolio; moreover they should also be viewed in regard to the real-world probabilities for applying stress conditions and readjust the riskfree assumptions. Default probabilities are reflected by credit ratings. Under stress conditions counterparties have certain probabilities to downgrade. Such probabilities are mapped with migration (transition) matrixes. Ratings also reflect the credit spreads. Such spreads can be used for discounting purposes, as discussed in Chapter 6 or stress testing considering the real-world probabilistic scenarios. Thus, at any time the expected impact in value, liquidity and resulting losses due to counterparty risk must be estimated. Finally, counterparties can be correlated. One of the most usable methods to identify the link between the counterparties is by their allocation and sensitivity to common or correlated market risk factors. This brings the analytics into a level of market and credit risk integration. To see how all the topics of this chapter interrelate with each other, Figure 7.9 includes in detail the main elements considered in counterparty analysis discussed above.NOTES
1. Alsoknownasassetvaluemodels.
2. H. Leland. Corporate debt value, bond covenants, and optimal capital structure. Journal of Finance, 49:1213-1252, 1994.
3. H. Leland and K. Toft. Optimal capital structure, endogenous bankruptcy, and the term structure of credit spreads. Journal of Finance, 51:987-1019, 1996.
4. The price based on such probabilities is 99% ? $100 + 1%? $0 = $99.
5. The assumption behind the portfolio of investments is that within a time horizon the overall default probability and expected losses are very low.
6. Typical value adjustments at portfolio or accounting levels are the Credit and Debt Value Adjustment methodologies denoted as CVA and DVA.
7. Applying Credit VaR Approach.
8. The identification of both Obligors' and Sectors' correlation plays key roles in different types of analysis, e.g., Concentration and Systemic Risks.