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Workshop D:


Practical Aspects of Counterparty Credit Risk

Measurement & Management


Led by Bank of America


Limited spaces available. Registration 09.00, workshop commences at 09.30 and ends at 17.00. There is time allocated for two refreshment breaks, lunch and for delegates to network and discuss issues addressed.

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INTRODUCTION AND OVERVIEW

  • Components of credit risk
  • Credit risk vs market risk
  • Counterparty credit risk vs. lending risk
  • Stochastic nature of exposure
  • Basel II treatment of counterparty risk
  • Systematic risk and credit market stress

CREDIT EXPOSURE FRAMEWORK

  • Price factors and risk factors
  • Risk factor evolution models
  • Exposure valuation conditional on scenarios
  • Exposure profiles and credit limits
  • Examples of exposure calculation
  • Netting agreements and aggregation
  • Margin agreements and collateralized exposure

MODELING MARGINS AND COLLATERALS

  • Collateral calculation for OTC derivatives and Repo loans
  • Threshold and Minimum transfer amount
  • Calculating margins (Deal Level and Portfolio)
  • Simulating future collateral calls – secondary time node
  • Calculating collateralized exposure and collateral requirement

MARKET PRICING OF COUNTERPARTY CREDIT RISK

  • Credit Valuation Adjustment (CVA)
  • Examples of CVA on Stand-alone Basis
  • Interest Rate Swaps
  • Interest Rate Caps, Floors and Swaptions
  • Modeling CVA at Portfolio Level
  • Calculating CVA in presence of Netting and/or Collateral Agreement
  • Hedging CVA with Contingent CDS
  • Accounting for Wrong/Right Way Risks
  • Risk Adjusted Return on Capital (RAROC) and Deal Pricing

RIGHT-WAY CREDIT RISK IN COMMODITY DERIVATIVES

  • Asset correlation between counterparty and commodity prices
  • Empirical evidence for ‘right-way’ risk in commodity
  • Approach in estimating the ‘right-way’ correlation
  • Moody’s KMV EDF and Distance-to-Default
  • Adjusting credit exposure and CVA for commodity ‘right-way’ risk

WRONG-WAY CREDIT RISK IN CREDIT DERIVATIVES

  • Default correlation between counterparty and underlying reference
  • Expected credit losses due to correlated defaults
  • Systematic risk driver for credit default correlation
  • Measuring double-default credit exposure for CDS and
  • CDO tranches
  • Modeling large gap risk exposure for protections with monocline insurers

 

 

Steven Zhu is currently a NY-based Senior Vice President at Bank of America, N.A., working with the Credit Analytics Group developing credit risk methodology and supporting the bank's capital markets business. Before joining the Bank of America in 2003, Steven has worked at Citibank, Bank One and Williams Co., respectively in the past 10 years since 1993. Steven specializes in the field of quantitative finance and risk management. He obtained his Ph.D. in Applied Mathematics from Brown University in 1992, and subsequently spent one-year term at MIT Sloan School of Management as a Visiting Research Scholar. He has published in the subject of applied math and quantitative finance in numerous journals, such as SIAM Journal, Economic Dynamics and Control.

 


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