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ADVANCED CREDIT RISK MEASUREMENT AND MODELLING TECHNIQUES for effective portfolio credit risk management NEW YORK, 5 & 6 SEPTEMBER 2002 LONDON, 19 & 20 SEPTEMBER 2002
COURSE HIGHLIGHTS:
COURSE LEADERS:
• Compare and contrast the leading portfolio credit risk modelling techniques
Colin Burke, ABBEY NATIONAL TREASURY SERVICES
• Default modelling with copula functions
Paul Hawkins, MERRILL LYNCH INTERNATIONAL
• Predicting and determining loss given default
Alla Gil, CITIGROUP Frank Iacono, LEHMAN BROTHERS INC. Ludger Overbeck, DEUTSCHE BANK AG
• Analyse new trends in portfolio capital management
Dr. Dmitry Pugachevsky, BEAR STEARNS & CO.
• Structure and evaluate synthetic CDOs
Bob Selvaggio, AMBAC FINANCIAL GROUP, INC.
Dr. Philipp J. Schönbucher, UNIVERSITY OF BONN
PRACTICAL WORKED EXAMPLES AND CASE STUDIES: • Construct the loss distribution function and calculate the expected loss for a real portfolio of corporate names • Parameterise and calibrate a sample portfolio using comparative credit risk models • Construct a calibrated spread curve • Derive default probabilities from equity prices • Use historical simulation to evaluate the performance of a traditional synthetic CDO
www.risktraining.com/crm
ADVANCED CR PORTFOLIO CR NEW YORK, 5 & 6 September 2002 NEW YORK, Thursday 5 September 2002 8.45 MODELLING DEFAULT RISK USING ASSET-BASED APPROACHES · Structural models: Merton model - examining key assumptions and limitations - term structure of credit spreads - empirical evidence - recovery rates and absolute priority · Commercial implementation of the model: The KMV approach CASE STUDY: Deriving default probabilities from equity prices: How it works and why it “missed” with Enron Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN 10.15 Morning break 10.45 ANALYSING SPREAD-BASED MODELS OF DEFAULT RISK · Credit spread curves and implied default probabilities - extracting information from market prices · Practical application of a transition matrix model for modelling portfolio credit risk · Recovery modelling - the impact of recovery rate on implied probabilities · Models of the default time - Poisson and Cox processes · Default modelling with copula functions · Correlated defaults in spread-based models PRACTICAL WORKED EXAMPLE: Constructing a calibrated spread curve Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN 12.15 Lunch break 1.15 ESTIMATING AND MODELLING RECOVERY RATES · Regularities in historical recovery rates · Predicting loss given default: LossCalcTM · Loss given default and recovery correlation risk - how to determine loss given default - internal assumptions on LGD - overcoming the problems of a lack of data - robustness results Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN 2.00 FACTOR MODELS OF PORTFOLIO CREDIT RISK · Conditionally independent defaults: The Binomial distribution · The one-factor Vasicek model and its resulting returns distributions · Multi factor models · Calibration and estimation · Econometric estimation PRACTICAL WORKED EXAMPLE: Calibrating a factor model to historical default frequencies Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN
3.15 Afternoon break 3.45 MODELS FOR PORTFOLIO CREDIT RISK MANAGEMENT: UNDERSTANDING THE ANALYTICS, CALIBRATION AND PERFORMANCE OF THE LEADING ALTERNATIVE APPROACHES · A critical examination of leading portfolio credit risk modelling techniques - CreditMetrics - CreditRisk+ - KMV/Moody's - Generalised framework, common ground and key differences · Selecting the most appropriate model for your portfolio · How does each model use market information? · An analysis of the new models for portfolio credit risk management PRACTICAL WORKED EXAMPLE: Parameterisation and calibration of a sample portfolio using comparative credit risk models Bob Selvaggio, Managing Director, Risk Analysis and Reporting AMBAC FINANCIAL GROUP, INC. 5.30 End of day one
NEW YORK, Friday 6 September 2002 8.45 CAPITAL MANAGEMENT FOR CREDIT RISKY PORTFOLIOS · New trends in portfolio capital management · Integration of market and credit risk · Generalising value-at-risk approach · Measuring capital required to cover the portfolio risks · Minimising portfolio capital needs · Different ways to implement transition from current to optimal portfolio PRACTICAL WORKED EXAMPLE: Construct the loss distribution function and calculate the expected loss of a portfolio. Identify market and credit risk numbers for the portfolio and discover the changes necessary to minimise the required capital. Analyse the various transactions used to implement the required changes Alla Gil, Managing Director, Head of Strategic Risk Advisory and Modelling Group CITIGROUP 10.15 Morning break 10.35 EFFECTIVE PRICING OF CREDIT DERIVATIVES FOR PORTFOLIO CREDIT RISK MANAGEMENT · Constructing spot/forward credit curves to price credit derivatives · Examining alternative methods to price credit default swaps · Components of the credit spread and the impact of liquidity
www.risktraining.com/crm
EDIT RISK MEASUREMENT AND MODELLING TE REDIT RISK MANAGEMENT LONDON, Thursday 19 September 2002 · Evaluating the key components of theoretical credit swap pricing · Overcoming the problems of a lack of data - selecting the most accurate and appropriate data source for pricing - assessing data quality and completeness - overcoming the problems in estimating historical volatility · Applying credit derivatives to manage portfolio credit risk PRACTICAL WORKED EXAMPLE: Pricing a credit derivative basket Alla Gil, Managing Director, Head of Strategic Risk Advisory and Modelling Group CITIGROUP
8.45 MODELLING DEFAULT RISK USING ASSET-BASED APPROACHES · Structural models: Merton model - examining key assumptions and limitations - term structure of credit spreads - empirical evidence - recovery rates and absolute priority · Commercial implementation of the model: The KMV approach CASE STUDY: Deriving default probabilities from equity prices: How it works and why it “missed” with Enron Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN
12.05 Lunch break 10.15 Morning break 1.05 MODELLING DEFAULT CORRELATION FOR PORTFOLIO CREDIT RISK MEASUREMENT · Event correlation · Importance of correlation - extreme cases - uncorrelated and perfectly correlated credits · Comparison of different structural approaches - Merton approach: Single- and multi-period - normal copula - t-Student copula - Hull-White approach · Sources of correlation data PRACTICAL WORKED EXAMPLE: The effect of copula specification on default probabilities and loss distributions
10.45 ANALYSING SPREAD-BASED MODELS OF DEFAULT RISK · Credit spread curves and implied default probabilities - extracting information from market prices · Practical application of a transition matrix model for modelling portfolio credit risk · Recovery modelling - the impact of recovery rate on implied probabilities · Models of the default time - Poisson and Cox processes · Default modelling with copula functions · Correlated defaults in spread-based models PRACTICAL WORKED EXAMPLE: Constructing a calibrated spread curve
Dmitry Pugachevsky, Managing Director, Head of Credit Derivatives Analytics BEAR STEARNS & CO.
Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN
3.00 Afternoon break
12.15 Lunch break
3.30 USING HISTORICAL SIMULATION TO MEASURE THE RELATIVE VALUE OF SYNTHETIC CDO TRANCHES · Overview of synthetic CDO market and structures · Interpreting the cohort default data · Sampling the data to simulate default experience in a model reference portfolio · Applying the resulting loss distribution to a model of synthetic CDO structures · Evaluating measures of risk and reward for the underlyings and the tranches - expected loss - variability of loss - variation in these measures over time · Recognising the weaknesses of this approach
1.15 ESTIMATING AND MODELLING RECOVERY RATES · Regularities in historical recovery rates · Predicting loss given default: LossCalcTM · Loss given default and recovery correlation risk - how to determine loss given default - internal assumptions on LGD - overcoming the problems of a lack of data - robustness results Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN
PRACTICAL WORKED EXAMPLE: Using historical simulation based on rating cohort data to evaluate the performance of a traditional synthetic CDO, referencing a diversified portfolio of high-grade corporate entities Frank Iacono, Senior Vice President LEHMAN BROTHERS INC. 5.00 End of course
2.00 FACTOR MODELS OF PORTFOLIO CREDIT RISK · Conditionally independent defaults: The Binomial distribution · The one-factor Vasicek model and its resulting returns distributions · Multi factor models · Calibration and estimation · Econometric estimation PRACTICAL WORKED EXAMPLE: Calibrating a factor model to historical default frequencies Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN
www.risktraining.com/crm
ECHNIQUES FOR EFFECTIVE LONDON, 19 & 20 September 2002
3.15 Afternoon break 3.45 MODELS FOR PORTFOLIO CREDIT RISK MANAGEMENT: UNDERSTANDING THE ANALYTICS, CALIBRATION AND PERFORMANCE OF THE LEADING ALTERNATIVE APPROACHES · A critical examination of leading portfolio credit risk modelling techniques - KMV/CreditMetrics - CreditRisk+ - Generalised framework, common ground and key differences · Sensitivity to portfolio composition: Selecting the most appropriate model for your portfolio · Implementation issues - overcoming the problem of a lack of data PRACTICAL WORKED EXAMPLE: Parameterisation and calibration of a sample portfolio using comparative credit risk models Colin Burke, Senior Quantitative Analyst ABBEY NATIONAL TREASURY SERVICES 5.30 End of day one
· Overcoming the problems of a lack of data - selecting the most accurate and appropriate data source for pricing - assessing data quality and completeness - overcoming the problems in estimating historical volatility · Applying credit derivatives to manage portfolio credit risk PRACTICAL WORKED EXAMPLE: Pricing a credit derivative basket Alla Gil, Managing Director, Head of Strategic Risk Advisory and Modelling Group CITIGROUP 12.05 Lunch break 1.05 MODELLING DEFAULT CORRELATION FOR PORTFOLIO CREDIT RISK MEASUREMENT · Default correlations: Small but dangerous · Use of copulas in modelling default correlation - conditional copulas/default time copulas · Copulas vs. correlation · Sources of correlation data · Generation of correlated random variates for portfolio modelling · Ability-to-pay correlations vs. event correlations · New results on correlation estimates based on asset time series and default data CASE STUDY: Stressed default probabilities in a portfolio of correlated credits
LONDON, Friday 20 September 2002 8.45 CAPITAL MANAGEMENT FOR CREDIT RISKY PORTFOLIOS · New trends in portfolio capital management · Integration of market and credit risk · Generalising value-at-risk approach · Measuring capital required to cover the portfolio risks · Minimising portfolio capital needs · Different ways to implement transition from current to optimal portfolio PRACTICAL WORKED EXAMPLE: Construct the loss distribution function and calculate the expected loss of a portfolio. Identify market and credit risk numbers for the portfolio and discover the changes necessary to minimise the required capital. Analyse the various transactions used to implement the required changes Alla Gil, Managing Director, Head of Strategic Risk Advisory and Modelling Group CITIGROUP 10.15 Morning break 10.35 EFFECTIVE PRICING OF CREDIT DERIVATIVES FOR PORTFOLIO CREDIT RISK MANAGEMENT · Constructing spot/forward credit curves to price credit derivatives · Examining alternative methods to price credit default swaps · Components of the credit spread and the impact of liquidity · Evaluating the key components of theoretical credit swap pricing
Ludger Overbeck, Head of Risk Research and Development DEUTSCHE BANK AG 3.00 Afternoon break 3.30 EXECUTING SYNTHETIC SECURITISATIONS AND CBO/CLOs TO TRANSFER PORTFOLIO CREDIT RISK · Cash vs. synthetic - how to choose the most appropriate approach for your transaction · What is a synthetic securitisation? · How to structure a synthetic securitisation - new structural developments for synthetic securitisations - rating agency modelling of synthetics · Putting synthetic securitisations to effective use - understanding the advantages of synthetic securitisations - who benefits from synthetics? · Modelling and pricing synthetic securitisations CASE STUDY: Leonardo - Aircraft portfolio risk transfer Paul Hawkins, Vice President, Securitisation & Portfolio Credit Derivatives MERRILL LYNCH INTERNATIONAL 5.00 End of course
www.risktraining.com/crm
COURSE LEADERS Colin Burke, ABBEY NATIONAL TREASURY SERVICES (London course) Colin Burke is a Senior Quantitative Analyst at Abbey National Treasury Services specialising in credit portfolio and economic capital modelling. As such he has designed and developed Monte Carlo simulation and default correlation models and applied these to portfolio analysis and CDO structuring and analysis. He has also built and tested sovereign default models. Prior to joining ANTS, Colin has held a number of positions at Barclays and ING Barings. He holds a BSc and Ph.D. in Physics from King's College, London. Alla Gil, CITIGROUP (London and New York courses) Alla Gil is a Managing Director and the Head of Strategic Risk Advisory and Modelling Group at Citigroup. In this role she is responsible for the development of the new risk assessment and mitigation methodologies and advising the senior management of major Citigroup's clients on currency risk, interest rate risk, credit risk as well as asset/liability, and economic capital management and optimisation. Prior to Citigroup Alla spent 3 years at Goldman Sachs developing interest rate derivatives models and 2.5 years at CIBC developing credit derivatives models. Paul Hawkins, MERRILL LYNCH INTERNATIONAL (London course) Paul Hawkins is a Vice President with responsibilities structuring and marketing balance-sheet transactions within Merrill Lynch's Securitisation and Portfolio Credit Derivatives group. He was a Structurer for the groundbreaking Leonardo and Stratus synthetic aircraft transactions and Igloo French loan synthetic securitisation. Prior to joining Merrill Lynch, Paul worked in a quantitative capacity with the Credit Derivatives group at Citibank, N.A. and Salomon Smith Barney where he modelled and structured large portfolio synthetic securitisations. Paul holds a Ph.D. in Quantitative Finance at Imperial College, University of London, on optimising credit portfolios using economic capital, and an MA in Mathematics from Cambridge University. Frank Iacono, LEHMAN BROTHERS INC. (New York course) Frank Iacono is a Senior Vice President of Lehman Brothers, Inc. in the Structured Credit Trading Group in New York. Mr. Iacono's responsibilities include structuring and trading of portfolio credit derivatives, including “baskets” and synthetic Collateralised Debt Obligation (“CDO”) products. Prior to joining Lehman, Mr. Iacono was a Vice President in the Structured Credit Products Group of Chase Securities, Inc. (1998-2001) and a Consultant at Capital Market Risk Advisors (1994 - 1998), Inc., a leading risk management and financial engineering consulting firm. Mr. Iacono received a Juris Doctor, cum laude from Harvard Law School, and a Bachelor of Science, summa cum laude, from Yale University.
Ludger Overbeck, DEUTSCHE BANK AG (London course) Ludger Overbeck is Head of Risk Research and Development, CIB/Credit Risk Management at Deutsche Bank AG, Frankfurt, since May 2000. His main projects include: Credit portfolio models for RAROC purpose; analytic support for portfolio management; analytic support for exposure management; integration of market and credit risk; risk assessment for CLOs and basket credit derivatives and analytic support for operational risk. Prior to this he was responsible for Group Market Risk Management, methodology and policy for credit risk and portfolio models. Ludger also lectures at the universities in Bonn (Department of Applied Mathematics) and Frankfurt (Department of Business and Economics). Dmitry Pugachevsky, BEAR STEARNS & CO. (New York course) Dmitry Pugachevsky is a Managing Director and the Head of Credit Derivatives Analytics of Bear Stearns Co. Prior to joining Bear Stearns in 2001, he worked for eight years with analytics groups of Bankers Trust and Deutsche Bank, developing models for credit, fixed income, and equity derivatives. Dr. Pugachevsky received his Ph.D. in Applied Mathematics from Carnegie Mellon University. He has published several papers on modelling credit and fixed income derivatives and co-authored a pioneering research on passport options. Philipp Schönbucher, UNIVERSITY OF BONN (London & New York courses) Dr. Philipp J. Schönbucher is Assistant Professor at the Department of Statistics of the Faculty of Economics at the University of Bonn. He holds degrees in Mathematics (Oxford) and Economics (Bonn) and a Ph.D. in Economics. His publications include papers on credit risk modelling, credit derivatives pricing, stochastic volatility modelling, option pricing in illiquid markets, real options and term structure models. His main area of research is credit risk modelling and credit derivatives pricing in which he has been active since 1996. Furthermore, he is author of a book on “Credit Derivatives Pricing Models” (to appear 2002), and he is consultant and professional trainer to a number of leading financial institutions. Bob Selvaggio, AMBAC FINANCIAL GROUP, INC. (New York course) Bob Selvaggio is a Managing Director of Ambac Financial Group, Inc. He is responsible for portfolio credit and market risk management and the attribution of economic capital. Prior to joining Ambac in May 1998, Dr. Selvaggio served as a Financial Economist at Thomson McKinnon Securities, and then held a number of positions at the Chase Manhattan Bank including Senior Asset/Liability Analyst, Head of Fixed Income and Mortgage Research, and Managing Director of Treasury Analytics. A graduate of the University of Pennsylvania, Bob holds a Ph.D. in Economics from Brown University. He is a member of the American Economic Association and National Association of Business Economists, and is a BAI Certified Risk Professional.
www.risktraining.com/crm
ADVANCED CREDIT RISK MEASUREMENT AND MODELLING TECHNIQUES for effective portfolio credit risk management Code : A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
NEW YORK, 5 & 6 SEPTEMBER 2002 LONDON, 19 & 20 SEPTEMBER 2002
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Registration details Advanced Credit Risk Measurement... Advanced Credit Risk Measurement...
New York, 5 & 6 September 2002 London, 19 & 20 September 2002
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COURSE HIGHLIGHTS:
COURSE LEADERS:
• Compare and contrast the leading portfolio credit risk modelling techniques
Colin Burke, ABBEY NATIONAL TREASURY SERVICES
• Default modelling with copula functions
Paul Hawkins, MERRILL LYNCH INTERNATIONAL
• Predicting and determining loss given default
Alla Gil, CITIGROUP Frank Iacono, LEHMAN BROTHERS INC. Ludger Overbeck, DEUTSCHE BANK AG
• Analyse new trends in portfolio capital management
Dr. Dmitry Pugachevsky, BEAR STEARNS & CO.
• Structure and evaluate synthetic CDOs
Bob Selvaggio, AMBAC FINANCIAL GROUP, INC.
Dr. Philipp J. Schönbucher, UNIVERSITY OF BONN
PRACTICAL WORKED EXAMPLES AND CASE STUDIES: • Construct the loss distribution function and calculate the expected loss for a real portfolio of corporate names • Parameterise and calibrate a sample portfolio using comparative credit risk models • Construct a calibrated spread curve • Derive default probabilities from equity prices • Use historical simulation to evaluate the performance of a traditional synthetic CDO
www.risktraining.com/crm
ADVANCED CR PORTFOLIO CR NEW YORK, 5 & 6 September 2002 NEW YORK, Thursday 5 September 2002 8.45 MODELLING DEFAULT RISK USING ASSET-BASED APPROACHES · Structural models: Merton model - examining key assumptions and limitations - term structure of credit spreads - empirical evidence - recovery rates and absolute priority · Commercial implementation of the model: The KMV approach CASE STUDY: Deriving default probabilities from equity prices: How it works and why it “missed” with Enron Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN 10.15 Morning break 10.45 ANALYSING SPREAD-BASED MODELS OF DEFAULT RISK · Credit spread curves and implied default probabilities - extracting information from market prices · Practical application of a transition matrix model for modelling portfolio credit risk · Recovery modelling - the impact of recovery rate on implied probabilities · Models of the default time - Poisson and Cox processes · Default modelling with copula functions · Correlated defaults in spread-based models PRACTICAL WORKED EXAMPLE: Constructing a calibrated spread curve Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN 12.15 Lunch break 1.15 ESTIMATING AND MODELLING RECOVERY RATES · Regularities in historical recovery rates · Predicting loss given default: LossCalcTM · Loss given default and recovery correlation risk - how to determine loss given default - internal assumptions on LGD - overcoming the problems of a lack of data - robustness results Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN 2.00 FACTOR MODELS OF PORTFOLIO CREDIT RISK · Conditionally independent defaults: The Binomial distribution · The one-factor Vasicek model and its resulting returns distributions · Multi factor models · Calibration and estimation · Econometric estimation PRACTICAL WORKED EXAMPLE: Calibrating a factor model to historical default frequencies Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN
3.15 Afternoon break 3.45 MODELS FOR PORTFOLIO CREDIT RISK MANAGEMENT: UNDERSTANDING THE ANALYTICS, CALIBRATION AND PERFORMANCE OF THE LEADING ALTERNATIVE APPROACHES · A critical examination of leading portfolio credit risk modelling techniques - CreditMetrics - CreditRisk+ - KMV/Moody's - Generalised framework, common ground and key differences · Selecting the most appropriate model for your portfolio · How does each model use market information? · An analysis of the new models for portfolio credit risk management PRACTICAL WORKED EXAMPLE: Parameterisation and calibration of a sample portfolio using comparative credit risk models Bob Selvaggio, Managing Director, Risk Analysis and Reporting AMBAC FINANCIAL GROUP, INC. 5.30 End of day one
NEW YORK, Friday 6 September 2002 8.45 CAPITAL MANAGEMENT FOR CREDIT RISKY PORTFOLIOS · New trends in portfolio capital management · Integration of market and credit risk · Generalising value-at-risk approach · Measuring capital required to cover the portfolio risks · Minimising portfolio capital needs · Different ways to implement transition from current to optimal portfolio PRACTICAL WORKED EXAMPLE: Construct the loss distribution function and calculate the expected loss of a portfolio. Identify market and credit risk numbers for the portfolio and discover the changes necessary to minimise the required capital. Analyse the various transactions used to implement the required changes Alla Gil, Managing Director, Head of Strategic Risk Advisory and Modelling Group CITIGROUP 10.15 Morning break 10.35 EFFECTIVE PRICING OF CREDIT DERIVATIVES FOR PORTFOLIO CREDIT RISK MANAGEMENT · Constructing spot/forward credit curves to price credit derivatives · Examining alternative methods to price credit default swaps · Components of the credit spread and the impact of liquidity
www.risktraining.com/crm
EDIT RISK MEASUREMENT AND MODELLING TE REDIT RISK MANAGEMENT LONDON, Thursday 19 September 2002 · Evaluating the key components of theoretical credit swap pricing · Overcoming the problems of a lack of data - selecting the most accurate and appropriate data source for pricing - assessing data quality and completeness - overcoming the problems in estimating historical volatility · Applying credit derivatives to manage portfolio credit risk PRACTICAL WORKED EXAMPLE: Pricing a credit derivative basket Alla Gil, Managing Director, Head of Strategic Risk Advisory and Modelling Group CITIGROUP
8.45 MODELLING DEFAULT RISK USING ASSET-BASED APPROACHES · Structural models: Merton model - examining key assumptions and limitations - term structure of credit spreads - empirical evidence - recovery rates and absolute priority · Commercial implementation of the model: The KMV approach CASE STUDY: Deriving default probabilities from equity prices: How it works and why it “missed” with Enron Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN
12.05 Lunch break 10.15 Morning break 1.05 MODELLING DEFAULT CORRELATION FOR PORTFOLIO CREDIT RISK MEASUREMENT · Event correlation · Importance of correlation - extreme cases - uncorrelated and perfectly correlated credits · Comparison of different structural approaches - Merton approach: Single- and multi-period - normal copula - t-Student copula - Hull-White approach · Sources of correlation data PRACTICAL WORKED EXAMPLE: The effect of copula specification on default probabilities and loss distributions
10.45 ANALYSING SPREAD-BASED MODELS OF DEFAULT RISK · Credit spread curves and implied default probabilities - extracting information from market prices · Practical application of a transition matrix model for modelling portfolio credit risk · Recovery modelling - the impact of recovery rate on implied probabilities · Models of the default time - Poisson and Cox processes · Default modelling with copula functions · Correlated defaults in spread-based models PRACTICAL WORKED EXAMPLE: Constructing a calibrated spread curve
Dmitry Pugachevsky, Managing Director, Head of Credit Derivatives Analytics BEAR STEARNS & CO.
Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN
3.00 Afternoon break
12.15 Lunch break
3.30 USING HISTORICAL SIMULATION TO MEASURE THE RELATIVE VALUE OF SYNTHETIC CDO TRANCHES · Overview of synthetic CDO market and structures · Interpreting the cohort default data · Sampling the data to simulate default experience in a model reference portfolio · Applying the resulting loss distribution to a model of synthetic CDO structures · Evaluating measures of risk and reward for the underlyings and the tranches - expected loss - variability of loss - variation in these measures over time · Recognising the weaknesses of this approach
1.15 ESTIMATING AND MODELLING RECOVERY RATES · Regularities in historical recovery rates · Predicting loss given default: LossCalcTM · Loss given default and recovery correlation risk - how to determine loss given default - internal assumptions on LGD - overcoming the problems of a lack of data - robustness results Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN
PRACTICAL WORKED EXAMPLE: Using historical simulation based on rating cohort data to evaluate the performance of a traditional synthetic CDO, referencing a diversified portfolio of high-grade corporate entities Frank Iacono, Senior Vice President LEHMAN BROTHERS INC. 5.00 End of course
2.00 FACTOR MODELS OF PORTFOLIO CREDIT RISK · Conditionally independent defaults: The Binomial distribution · The one-factor Vasicek model and its resulting returns distributions · Multi factor models · Calibration and estimation · Econometric estimation PRACTICAL WORKED EXAMPLE: Calibrating a factor model to historical default frequencies Philipp J. Schönbucher, Assistant Professor, Department of Statistics UNIVERSITY OF BONN
www.risktraining.com/crm
ECHNIQUES FOR EFFECTIVE LONDON, 19 & 20 September 2002
3.15 Afternoon break 3.45 MODELS FOR PORTFOLIO CREDIT RISK MANAGEMENT: UNDERSTANDING THE ANALYTICS, CALIBRATION AND PERFORMANCE OF THE LEADING ALTERNATIVE APPROACHES · A critical examination of leading portfolio credit risk modelling techniques - KMV/CreditMetrics - CreditRisk+ - Generalised framework, common ground and key differences · Sensitivity to portfolio composition: Selecting the most appropriate model for your portfolio · Implementation issues - overcoming the problem of a lack of data PRACTICAL WORKED EXAMPLE: Parameterisation and calibration of a sample portfolio using comparative credit risk models Colin Burke, Senior Quantitative Analyst ABBEY NATIONAL TREASURY SERVICES 5.30 End of day one
· Overcoming the problems of a lack of data - selecting the most accurate and appropriate data source for pricing - assessing data quality and completeness - overcoming the problems in estimating historical volatility · Applying credit derivatives to manage portfolio credit risk PRACTICAL WORKED EXAMPLE: Pricing a credit derivative basket Alla Gil, Managing Director, Head of Strategic Risk Advisory and Modelling Group CITIGROUP 12.05 Lunch break 1.05 MODELLING DEFAULT CORRELATION FOR PORTFOLIO CREDIT RISK MEASUREMENT · Default correlations: Small but dangerous · Use of copulas in modelling default correlation - conditional copulas/default time copulas · Copulas vs. correlation · Sources of correlation data · Generation of correlated random variates for portfolio modelling · Ability-to-pay correlations vs. event correlations · New results on correlation estimates based on asset time series and default data CASE STUDY: Stressed default probabilities in a portfolio of correlated credits
LONDON, Friday 20 September 2002 8.45 CAPITAL MANAGEMENT FOR CREDIT RISKY PORTFOLIOS · New trends in portfolio capital management · Integration of market and credit risk · Generalising value-at-risk approach · Measuring capital required to cover the portfolio risks · Minimising portfolio capital needs · Different ways to implement transition from current to optimal portfolio PRACTICAL WORKED EXAMPLE: Construct the loss distribution function and calculate the expected loss of a portfolio. Identify market and credit risk numbers for the portfolio and discover the changes necessary to minimise the required capital. Analyse the various transactions used to implement the required changes Alla Gil, Managing Director, Head of Strategic Risk Advisory and Modelling Group CITIGROUP 10.15 Morning break 10.35 EFFECTIVE PRICING OF CREDIT DERIVATIVES FOR PORTFOLIO CREDIT RISK MANAGEMENT · Constructing spot/forward credit curves to price credit derivatives · Examining alternative methods to price credit default swaps · Components of the credit spread and the impact of liquidity · Evaluating the key components of theoretical credit swap pricing
Ludger Overbeck, Head of Risk Research and Development DEUTSCHE BANK AG 3.00 Afternoon break 3.30 EXECUTING SYNTHETIC SECURITISATIONS AND CBO/CLOs TO TRANSFER PORTFOLIO CREDIT RISK · Cash vs. synthetic - how to choose the most appropriate approach for your transaction · What is a synthetic securitisation? · How to structure a synthetic securitisation - new structural developments for synthetic securitisations - rating agency modelling of synthetics · Putting synthetic securitisations to effective use - understanding the advantages of synthetic securitisations - who benefits from synthetics? · Modelling and pricing synthetic securitisations CASE STUDY: Leonardo - Aircraft portfolio risk transfer Paul Hawkins, Vice President, Securitisation & Portfolio Credit Derivatives MERRILL LYNCH INTERNATIONAL 5.00 End of course
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COURSE LEADERS Colin Burke, ABBEY NATIONAL TREASURY SERVICES (London course) Colin Burke is a Senior Quantitative Analyst at Abbey National Treasury Services specialising in credit portfolio and economic capital modelling. As such he has designed and developed Monte Carlo simulation and default correlation models and applied these to portfolio analysis and CDO structuring and analysis. He has also built and tested sovereign default models. Prior to joining ANTS, Colin has held a number of positions at Barclays and ING Barings. He holds a BSc and Ph.D. in Physics from King's College, London. Alla Gil, CITIGROUP (London and New York courses) Alla Gil is a Managing Director and the Head of Strategic Risk Advisory and Modelling Group at Citigroup. In this role she is responsible for the development of the new risk assessment and mitigation methodologies and advising the senior management of major Citigroup's clients on currency risk, interest rate risk, credit risk as well as asset/liability, and economic capital management and optimisation. Prior to Citigroup Alla spent 3 years at Goldman Sachs developing interest rate derivatives models and 2.5 years at CIBC developing credit derivatives models. Paul Hawkins, MERRILL LYNCH INTERNATIONAL (London course) Paul Hawkins is a Vice President with responsibilities structuring and marketing balance-sheet transactions within Merrill Lynch's Securitisation and Portfolio Credit Derivatives group. He was a Structurer for the groundbreaking Leonardo and Stratus synthetic aircraft transactions and Igloo French loan synthetic securitisation. Prior to joining Merrill Lynch, Paul worked in a quantitative capacity with the Credit Derivatives group at Citibank, N.A. and Salomon Smith Barney where he modelled and structured large portfolio synthetic securitisations. Paul holds a Ph.D. in Quantitative Finance at Imperial College, University of London, on optimising credit portfolios using economic capital, and an MA in Mathematics from Cambridge University. Frank Iacono, LEHMAN BROTHERS INC. (New York course) Frank Iacono is a Senior Vice President of Lehman Brothers, Inc. in the Structured Credit Trading Group in New York. Mr. Iacono's responsibilities include structuring and trading of portfolio credit derivatives, including “baskets” and synthetic Collateralised Debt Obligation (“CDO”) products. Prior to joining Lehman, Mr. Iacono was a Vice President in the Structured Credit Products Group of Chase Securities, Inc. (1998-2001) and a Consultant at Capital Market Risk Advisors (1994 - 1998), Inc., a leading risk management and financial engineering consulting firm. Mr. Iacono received a Juris Doctor, cum laude from Harvard Law School, and a Bachelor of Science, summa cum laude, from Yale University.
Ludger Overbeck, DEUTSCHE BANK AG (London course) Ludger Overbeck is Head of Risk Research and Development, CIB/Credit Risk Management at Deutsche Bank AG, Frankfurt, since May 2000. His main projects include: Credit portfolio models for RAROC purpose; analytic support for portfolio management; analytic support for exposure management; integration of market and credit risk; risk assessment for CLOs and basket credit derivatives and analytic support for operational risk. Prior to this he was responsible for Group Market Risk Management, methodology and policy for credit risk and portfolio models. Ludger also lectures at the universities in Bonn (Department of Applied Mathematics) and Frankfurt (Department of Business and Economics). Dmitry Pugachevsky, BEAR STEARNS & CO. (New York course) Dmitry Pugachevsky is a Managing Director and the Head of Credit Derivatives Analytics of Bear Stearns Co. Prior to joining Bear Stearns in 2001, he worked for eight years with analytics groups of Bankers Trust and Deutsche Bank, developing models for credit, fixed income, and equity derivatives. Dr. Pugachevsky received his Ph.D. in Applied Mathematics from Carnegie Mellon University. He has published several papers on modelling credit and fixed income derivatives and co-authored a pioneering research on passport options. Philipp Schönbucher, UNIVERSITY OF BONN (London & New York courses) Dr. Philipp J. Schönbucher is Assistant Professor at the Department of Statistics of the Faculty of Economics at the University of Bonn. He holds degrees in Mathematics (Oxford) and Economics (Bonn) and a Ph.D. in Economics. His publications include papers on credit risk modelling, credit derivatives pricing, stochastic volatility modelling, option pricing in illiquid markets, real options and term structure models. His main area of research is credit risk modelling and credit derivatives pricing in which he has been active since 1996. Furthermore, he is author of a book on “Credit Derivatives Pricing Models” (to appear 2002), and he is consultant and professional trainer to a number of leading financial institutions. Bob Selvaggio, AMBAC FINANCIAL GROUP, INC. (New York course) Bob Selvaggio is a Managing Director of Ambac Financial Group, Inc. He is responsible for portfolio credit and market risk management and the attribution of economic capital. Prior to joining Ambac in May 1998, Dr. Selvaggio served as a Financial Economist at Thomson McKinnon Securities, and then held a number of positions at the Chase Manhattan Bank including Senior Asset/Liability Analyst, Head of Fixed Income and Mortgage Research, and Managing Director of Treasury Analytics. A graduate of the University of Pennsylvania, Bob holds a Ph.D. in Economics from Brown University. He is a member of the American Economic Association and National Association of Business Economists, and is a BAI Certified Risk Professional.
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ADVANCED CREDIT RISK MEASUREMENT AND MODELLING TECHNIQUES for effective portfolio credit risk management Code : A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
NEW YORK, 5 & 6 SEPTEMBER 2002 LONDON, 19 & 20 SEPTEMBER 2002
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Registration details Advanced Credit Risk Measurement... Advanced Credit Risk Measurement...
New York, 5 & 6 September 2002 London, 19 & 20 September 2002
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