Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/17683
Title: RISK MEASUREMENT FOR PORTFOLIOS AND CDO TRANCHES
Authors: MA LANFANG
Keywords: integrated risk;dynamic multi-period model;parameter analysis; CDO tranches;VaR;Average VaR
Issue Date: 22-Jan-2008
Source: MA LANFANG (2008-01-22). RISK MEASUREMENT FOR PORTFOLIOS AND CDO TRANCHES. ScholarBank@NUS Repository.
Abstract: Since the disclosure of the sub-prime problem two years ago, crisis has spread out from mortgage sector to global financial markets and real economies. Many countries have entered downturn cycles due to the unprecedented global financial crisis. Under such stressed market conditions, reasonable portfolio risk measurement models become more relevant than ever before in bank industry. Currently the most commonly accepted portfolio risk measurement model is the one factor Gaussian copula model, which is a static single period model. However, during the on-going financial crisis, we have witnessed the evolution of the market environment, such as sharply increased asset return correlations, default rates and more volatile markets of all asset classes; we have also realized the more significant impacts of systemic risks which have features of dynamic persistence and autocorrelations. All these features and observations obviously cannot be captured by the static single period model. In this study, we generalize a benchmark static single period model to a dynamic multi-period model, which not only can capture the market evolution by allowing for flexible term structures of all market parameters but also can capture the autocorrelation and dynamic persistence of the systemic risk factors. With this dynamic multi-period model, we analyze portfolio risk from two separate but closely related angles: the point of view from credit portfolio holders and the point of view from Collateralized Debt Obligations (CDO) tranche investors with references to the same portfolio. As a portfolio holder, we focus on the risk measures value at risk (VaR), average VaR (AVaR) and the statistics of the portfolio value distribution such as mean and standard deviation (STD); while as a CDO tranche investor, our concerns are the tranche hitting probability and expected tranche loss. Within the dynamic multi-period framework, we comparatively analyze these risk measures undernormal market conditions and stressed market conditions; we conduct parameter analysis not only to single period related parameters but also multi-period related parameters; we then move to scenario analysis where all parameters are adjustable to illustrate the flexibility and capability of the dynamic multi-period model. To our knowledge this is one of the most comprehensive studies which explores portfolio risks not only on credit portfolio level but also on CDO tranche level. With the generalized dynamic multi-period model, stress testing and scenario analysis can be done to an inhomogeneous underlying pool and CDO tranches on top of it, which should be able to shed some light under current gloomy market sentiments.
URI: http://scholarbank.nus.edu.sg/handle/10635/17683
Appears in Collections:Master's Theses (Open)

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