1. Unified Financial Analysis Risk & Finance Lab
Chapter 5: Counterparty
Willi Brammertz / Ioannis Akkizidis

2. Table of Content Introduction Data Credit Exposure
Credit Value Adjusted
Provisioning (IFRS 9)
Stress Scenarios and CVaR

3. Input elements Counterparties
Hello
Input elements Counterparties
Having contract and market information (leaving Behavior for later) allows generating the expected financial events (principal and interest payments, option pay-offs etc.) under any market scenario. This however assumes perfectly paying counterparties or no credit risk.
In this lecture/chapter we introduce the notion of credit risk. The first part of credit risk is to establish the exposure or, how much could be lost in case a counterparty defaults. This part, the establishment of credit exposure, is treated in this chapter. The application of probability of default is only briefly touched and will be further treated in the next chapter under behavior since it is a typically statistical element.

4. Counterparty and Behavior
Counterparty has descriptive and modeling part
Descriptive part (Data)
Characteristics
Hierarchies
Links to financial contracts
Credit enhancements
Behavioral (statistical nature)
Probability of default
Recovery rates
Recovery patterns
Used at default
This distinguishes in more detail, what is discussed in this chapter (descriptive part) and what in the next chapter (statistical part).
The descriptive part can be considered as hard facts while the statistical part is the real risk part.
Having all the descriptive elements allows deriving the exposure at default.

5. Table of Content Introduction Data Credit Exposure
Credit Value Adjusted
Provisioning (IFRS 9)
Stress Scenarios and CVaR

6. Relational Structure Counter party Data Market Data CR-Spreads
LEI
PDi
CPi RT RT
Market Data
CR-Spreads
MOC RT
Probability of
Default Data
Migration Matrix
Contract Data
CID LEI MOC
Valuation
Model
Parameters
CTi MOC CID
Book Keeping
Data
CID
Prov

7. Guarantee Obligor CNTRL: OBL Guarantor Borrower Contract(s)
This distinguishes in more detail, what is discussed in this chapter (descriptive part) and what in the next chapter (statistical part).
The descriptive part can be considered as hard facts while the statistical part is the real risk part.
Having all the descriptive elements allows deriving the exposure at default.
Contract(s)

8. Collateral (CloseOutNetting)
Obligor
CNTRL: CLO
Collateral
Borrower
This distinguishes in more detail, what is discussed in this chapter (descriptive part) and what in the next chapter (statistical part).
The descriptive part can be considered as hard facts while the statistical part is the real risk part.
Having all the descriptive elements allows deriving the exposure at default.
Contract(s)
Contract(s)

9. Table of Content Introduction Data Credit Exposure
Credit Value Adjusted
Provisioning (IFRS 9)
Stress Scenarios and CVaR

10. Three steps to expected loss
Exposure at default EAD: Gross exposure – credit enhancements = EAD
Loss given default LGD: EAD * (1 - recovery rate) = LGD
Expected loss EL: LGD * probability of default = EL
Different data quality in each step: separation necessary
Rating agencies: mix the three steps (subprime)
PD‘s must reflect uncollateralized junior debt
The first two equations describe the same as the previous slide.
Each step involves more variables of statistical nature wherefore the reliability of the results declines and risk increases. Step 1 is pure transactional data which can be measured easily and with high reliability. Step two and three add two statistical concepts.
A rating such as AAA is often a mix of all three steps, which makes rating such a difficult to handle concept.
Life would be much easier and clearer, if the three steps would be disentangeled and the rating would only describe probabilty of default.
Note: recovery rate and probability of default are described in more detail in the next chapter.
In this chapter we discuss the data needs related to EAD

11. Three steps to expected loss
Exposure at default EAD: Gross exposure – credit enhancements = EAD
Loss given default LGD: EAD * (1 - recovery rate) = LGD
Expected loss EL: LGD * probability of default = EL
The first two equations describe the same as the previous slide.
Each step involves more variables of statistical nature wherefore the reliability of the results declines and risk increases. Step 1 is pure transactional data which can be measured easily and with high reliability. Step two and three add two statistical concepts.
A rating such as AAA is often a mix of all three steps, which makes rating such a difficult to handle concept.
Life would be much easier and clearer, if the three steps would be disentangeled and the rating would only describe probabilty of default.
Note: recovery rate and probability of default are described in more detail in the next chapter.
In this chapter we discuss the data needs related to EAD

12. Gross exposure Description of counterparty:
Unique ID
Private: Age, gender, martial status etc.
Firms: Balance sheet ratios, turnover, profitability , market environment etc.
Assets outstanding per counterparty
Goss exposure := Sum of all assets
The following slides go throuhg the steps of establishing net exposure (gross exposure plus credit enhancements)
First we have purely descriptive data. Most important is the unique ID which links all contracts of a single counterparty. In addition to this, we need descriptive data which in a later step will be used first for grouping and secondly for estalishing probabilities of default. Grouping in credit risk is important due to the high correlation between members of a group (for example within the same industry).
In order to establish credit exposure it also has to be known, who is linked to whom. This is important due to the high correlation between loan default of related companies (if the mother company fails, most likely all the daughters will be affected as well).
Once it is known who owns whom, the gross exposure on any level of a conglomerate can be established.

13. From Gross Exposure to Exposure at Default
The idea of exposure has to be described step by step.
Exposure and valuation!

14. Three steps to expected loss
Exposure at default EAD: Gross exposure – credit enhancements = EAD
Loss given default LGD: EAD * (1 - recovery rate) = LGD
Expected loss EL: LGD * probability of default = EL
The first two equations describe the same as the previous slide.
Each step involves more variables of statistical nature wherefore the reliability of the results declines and risk increases. Step 1 is pure transactional data which can be measured easily and with high reliability. Step two and three add two statistical concepts.
A rating such as AAA is often a mix of all three steps, which makes rating such a difficult to handle concept.
Life would be much easier and clearer, if the three steps would be disentangeled and the rating would only describe probabilty of default.
Note: recovery rate and probability of default are described in more detail in the next chapter.
In this chapter we discuss the data needs related to EAD

15. Recovery rates Net recovery Gross recovery Recovery rates
Recovery patterns
Gross recovery
Mingles collateral and recovery
To be avoided if possible
Ariadne supports only net recovery

16. Recovery rates
Based on historical experience
Single percentage number

17. Recovery pattern
Recovery patterns

18. Three steps to expected loss
Exposure at default EAD: Gross exposure – credit enhancements = EAD
Loss given default LGD: EAD * (1 - recovery rate) = LGD
Expected loss EL: LGD * probability of default = EL
The first two equations describe the same as the previous slide.
Each step involves more variables of statistical nature wherefore the reliability of the results declines and risk increases. Step 1 is pure transactional data which can be measured easily and with high reliability. Step two and three add two statistical concepts.
A rating such as AAA is often a mix of all three steps, which makes rating such a difficult to handle concept.
Life would be much easier and clearer, if the three steps would be disentangeled and the rating would only describe probabilty of default.
Note: recovery rate and probability of default are described in more detail in the next chapter.
In this chapter we discuss the data needs related to EAD

19. From Gross Exposure to Exposure at DefaultPD
The idea of exposure has to be described step by step.
Exposure and valuation!

20. Table of Content Introduction Data Credit Exposure
Credit Value Adjusted
Provisioning (IFRS 9)
Stress Scenarios and CVaR

21. Relational Structure Contract Data CID LEI MOC Counter party Data LEI
Market Data
CR-Spreads
MOC
Valuation
Model
Parameters
CTi MOC CID RT
CPi
PDi
Book Keeping
CID
Prov
Probability of
Default Data
Migration Matrix

22. Link to CP and VMP Counter party Market Data Probability of CR-Spreads
LEI
PDi
CPi RT
Market Data
CR-Spreads
MOC RT RT
Probability of
Default Data
Migration Matrix
Contract Data
CID LEI MOC
Valuation
Model
Parameters
CTi MOC CID
Book Keeping
Data
CID
Prov

23. Risk Free discounting Counter party Data Market Data CR-Spreads
LEI
PDi
CPi RT
Market Data
CR-Spreads
MOC RT RT
Probability of
Default Data
Migration Matrix
Contract Data
CID LEI MOC
Valuation
Model
Parameters
CTi MOC CID
Book Keeping
Data
CID
Prov
Primary

24. Adding Credit Risk and Idiosyncratic Spreads
Counter party
Data
LEI
PDi
CPi RT
Market Data
CR-Spreads
MOC RT RT
Probability of
Default Data
Migration Matrix
Contract Data
CID LEI MOC
Valuation
Model
Parameters
CTi MOC CID
Book Keeping
Data
CID
Prov
Primary
Discounting: Mkt_YC(VMP, MD)+CR_SC(CP, MD)+CTi(VMP)+CPi(CP)

25. Table of Content Introduction Data Credit Exposure
Credit Value Adjusted
Provisioning (IFRS 9)
Stress Scenarios and CVaR

26. Relational Structure Provisioning
Counter party
Data
LEI
PDi
CPi RT
Market Data
CR-Spreads
MOC RT RT
Probability of
Default Data
Migration Matrix
Contract Data
CID LEI MOC
Valuation
Model
Parameters
CTi MOC CID
Book Keeping
Data
CID
Prov
Provisioning: PD(CP, RT)+PDi(CP)

27. Table of Content Introduction Data Credit Exposure
Credit Value Adjusted
Provisioning (IFRS 9)
Stress Scenarios and CVaR

28. Stress Scenarios Recovery Stress Rating Stress
Initial Position in Risk Factor, CP-table
Stress in Credit Scenario
Rating Stress

29. Credit VaR Part of Market Scenario
Original Position in Risk Factor, Market Table
VaR
Market Risk
Credit Risk
Combined Risk