Pricing, Hedging and Managing the Risks of CLOs New York, 19th October 2011
As demonstrated by the recent credit crisis, the modeling of structured credit portfolios presents significant challenges, given the complexity of their structures and underlying market, credit and liquidity risks. Historically, simplistic black-box approaches have resulted in a lack of price transparency and limited risk capabilities for investors.
This half day workshop provides an overview of the current state-of-the-art methodologies for valuing and managing the risk of CLOs, and addresses key issues that arise in practice. The predominant pricing framework for ABS and cash CLOs, widely used by dealers and investors, is based on simple (single-scenario) bond models and matrix pricing, where the yields of these securities are expressed in a similar way to those of typical corporate bonds. Practitioners also commonly use net asset value (NAV) approaches to monitor these investments, which in practice present technical difficulties and can be resource intensive.
Finally, recent advances on second-generation, Monte Carlo models today provide more robust, practical methods for pricing, hedging and measuring the risk of structured credit portfolios. Regardless of the approach, when dealing with complex structures and markets with limited liquidity, it is important to understand all the underlying risks, acknowledge the assumptions in our models, and the limitation of the data. Thus, it is vital to develop explicit model risk and stress testing approaches which can help us understand better the behaviour and risks of individual instruments and portfolios.
Led by Dan Rosen, CEO, R2 Financial Technologies & Adjunct Professor of Mathematical Finance, University of Toronto
1)Introduction to structured credit securities and CLOs Collateral, structures and risks
2) NPV/bond Model for valuing CLOs Detailed modelling of the collateral pool and waterfall Price-yield calculation under a single-scenario Stress testing under multiple scenarios
3) Net Asset Value (NAV) Coverage ratios and NAV statistics Practical implementation of NAV approaches and collateral valuation
4) Stochastic and Monte Carlo approaches for cash and synthetic CLOs Implied factor models and Weighted Monte Carlo methods Contrast to Gaussian Copula methods Market information and model calibration in practice Hedging and risk metrics Examples: valuing cash CLOs, synthetic CLOs and CLO2
5. Concluding remarks
Dr. Dan Rosen, is the CEO of R2 FINANCIAL TECHNOLOGIES, as well as an adjunct professor in Mathematical Finance at the University of Toronto. Dr. Rosen acts as an advisor to institutions around the world and lectures extensively on valuation of structured finance and derivatives; counterparty credit risk; risk management; and on economic and regulatory capital. He has authored numerous risk management and financial engineering publications, and serves in the editorial board of several industrial and academic journals. Prior to founding R2 in 2006, he had a successful ten-year career at Algorithmics. Dr. Rosen was recently indicted in 2010 as fellow of the Fields Institute for Research in Mathematical Sciences. He holds an M.A.Sc. and Ph.D. from the University of Toronto.