Credit Valuation Adjustment (CVA): Model Validation Considerations

Transcription

1 Credit Valuation Adjustment (CVA): Model Validation Considerations A presentation to the ABA Model Validation working group Alexey Surkov, Partner asurkov@deloitte.com Regulatory & Capital Markets Consulting Deloitte & Touche LLP May 14, 2009

2 Disclaimer This presentation contains general information only and Deloitte is not, by means of this presentation, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. This presentation is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor. As used in this document "Deloitte" means Deloitte & Touche LLP, a subsidiary of Deloitte LLP. Please see for a detailed description of the legal structure of Deloitte LLP and its subsidiaries. 1

3 Agenda Background Considerations for Counterparty Credit Risk Models Common Model Validation Issues 2

4 Background Credit Risk: Risk of loss due to an obligor s failure to perform on its obligations (e.g. in the event of a bankruptcy) Fair value measurement of an asset should include the impact of the counterparty s credit standing (e.g. risky bond) Fair value measurement of a liability should include the impact of the reporting entity s own credit standing Counterintuitive result: As an entity s credit standing declines, the fair value of its liabilities decreases with a resulting gain in earnings (and vice-versa) Credit enhancements can mitigate credit risk (for example, cash collateral, can be unilateral or bilateral) If netting is permitted, credit risk can be mitigated 3

5 Current Exposure and Potential Exposure Current Exposure What would be the Firm s expected loss if the derivative cash flows were known with certainty or if the counterparty defaulted today? Potential Exposure Given a range of potential future market moves, what would be the entity s average, or expected, loss over the life of the contract? And what would be the counterparty s expected loss if the entity defaulted sometime prior to contract maturity? Credit Risk is defined as loss due to an obligor s failure to perform on its obligations (such as in the event of a bankruptcy) 4

6 Potential Positive Exposure C/party Default Consider an example of a vanilla fixed-for-floating interest-rate swap, with a par (zero) or negative value at inception Risk of credit loss exists even if the fair value of the instrument today is zero or negative Today s potential for future market moves give rise to this potential exposure Consider four possible scenarios for a derivative instrument: Positive Future Market Value (Asset) Counterparty Default Occurs by Time t: Fair Value Loss Counterparty Default Does Not Occur NO IMPACT (No Default) Negative Future Market Value (Liability) NO IMPACT (Counterparty creditors have full claim) NO IMPACT (No Default) 5

7 Potential Negative Exposure Entity Default Similar to previous example, except now we are considering the potential for the entity to default (not the counterparty) Counterintuitive result: downgrade rating = more P&L! Consider four possible scenarios for a derivative instrument: Positive Future Market Value (Asset) Entity Default Occurs by Time t: NO IMPACT (Entity has full claim) Entity Default Does Not Occur NO IMPACT (No Default) Negative Future Market Value (Liability) Fair Value Gain NO IMPACT (No Default) 6

8 Exposure Profile t 1 t 2 t 3 t 4 t 5 t 6 t 7 t 8 Time zero displays current exposure Potential future exposure exists at future points in time as well, and this may be different from current exposure: Future exposure 7

9 Credit Enhancements Collateral Bilateral or unilateral Threshold Minimum Transfer Amount Collateral lag Asset Liability Collateral Received Collateral Posted Netting Across entire counterparty portfolio By asset types (e.g. Equity Derivatives) Netted Exposure Derivative 1: Asset Can Reduce Exposure Derivative 2: Liability 8

10 Summary of Techniques Calculating the CVA Current Exposure Function of exposure size and duration Calculation techniques include discounting of net cash flows In certain cases (e.g., large asset or liability), captures the bulk of the impact Potential Exposure Function of both size and variability of exposure over time Calculation techniques: Scenario Analysis, Monte Carlo Simulation Captures remaining impact of credit risk (over current exposure) In certain cases (e.g. large asset or liability), impact may not be significant relative to that of Current Exposure 9

11 Model Validation Considerations for Counterparty Credit Risk Models Model Validation Components Theoretical Foundations Inputs and Assumptions Model Implementation (Benchmarking) Model Outputs and Reports Model Control Environment 10

12 Model Validation Considerations for Counterparty Credit Risk Models Theoretical Foundations Theoretical soundness Financial mathematics Consistency with leading and prevailing practices Examples: Use of current exposure vs. potential exposure Theoretical foundations of chosen methodology Applicability of CVA methodology to portfolio 11

13 Model Validation Considerations for Counterparty Credit Risk Models Inputs and Assumptions Market inputs Estimated inputs Assumptions Examples: Credit spread curves, yield curves, implied volatility surfaces Position data (notional, FV, number of positions) Maturity (e.g. long-dated instruments) Type of instruments (e.g. complex and volatile) Portfolio Netting Collateral Agreements (threshold, minimum transfer amount, collateral posting lag) 12

14 Model Validation Considerations for Counterparty Credit Risk Models Model Implementation (Benchmarking): Testing of implementation & calculations Independent recalculation of model outputs Reconciliation to model results Key validation step: numbers! Examples: Simulation integrity tests (e.g. consistency between CVA model and fair value model for initial exposure point) Recalculation of CVA on sample counterparty portfolio using consistent methodology Replication of intermediate calculations (e.g. hazard rates, probability of default) 13

15 Model Validation Considerations for Counterparty Credit Risk Models Model Outputs and Reports Assessment of model outputs Model results processing and aggregation Reporting and use of model outputs Examples: Fair value adjustments for financial reporting and related disclosures (e.g. FV impact of changes in credit risk) Risk/capital reports for firm-wide risk models Capital calculations and associated regulatory disclosures 14

16 Model Validation Considerations for Counterparty Credit Risk Models Model Control Environment Model Governance Documentation Benchmarking and Validation Model controls Documented Model Validation Policies and Procedures Examples: CVA model and methodology documentation Inclusion of the CVA model on the model inventory Periodic validation of CVA and benchmarking to leading practices 15

17 Examples of Common Validation Issues Model theory Inputs Consistency Testing Validation model does not consider the portfolio s credit enhancements (e.g. collateral, netting) credit spread characteristics of input data are inconsistent with exposure characteristics (e.g. use of collateralized bank loan spreads for unsecured exposures) capital model credit calculations vs. CVA model calculations not thoroughly tested after implementation (e.g. analytic comparison to results obtained using less complex methodology) no independent recalculation 16

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