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We have developed a new family of Archimedean copula processes for modeling the dynamic dependence between default times in a large portfolio of names and for pricing synthetic CDO tranches. After presenting a general procedure for constructing these processes, we focus on a specific one with lower tail dependence as in the Clayton copula. Using CDS data as on July 2005, we show that the base correlations given by this model at the standard detachment points are very similar to those quoted in the market for a maturity of 5 years.

This article describes a new approach to compute values and sensitivities of synthetic collateralized debt obligation (CDO) tranches in the market-standard, single-factor, Gaussian copula model with base correlation. We introduce a novel decomposition of the conditional expected capped portfolio loss process into “intrinsic value” and “time value” components, derive a closed form solution for the intrinsic value, and describe a very efficient computational scheme for the time value, taking advantage of a curious time stability of this quantity.

In August 2007 the Mainsail II SIV-Lite was frozen by its trustee as a result of the ongoing credit crisis. The state of Maine held $20 million of Mainsail commercial paper in its Cash Pool portfolio, a short-term portfolio that puts temporary, excess state revenues to work. When word of the potential loss became public, the Treasurer came under attack. The case introduces the functions of a state Treasury department, with particular emphasis on the investment objectives and guidelines for the cash pool as well as its composition. The case reviews the events leading up to and including August 2007, the month when the credit markets first began to seize and when the financial crisis effectively began. It examines securitization, structured finance, and the Mainsail SIV-Lite structure in some detail.

Recently, domestic market participants have a growing interest in synthetic Collateralized Debt Obligation (CDO) as a security to reduce credit risk and create new profit. Therefore, the valuation method and hedging strategy for synthetic CDO become an important issue. However, there is no won-denominated credit default swap transactions, which are essential for activating synthetic CDO transaction‘ In addition, there is no transparent market information for the default probability, asset correlation, and recovery rate, which are critical variables determining the price of synthetic CDO.

This study first investigates the method of estimating the default probability, asset correlation coefficient, and recovery rate. Next, using five synthetiC CDO pricing models‘ widely used OFGC (One-Factor Non-Gaussian Copula) model. OFNGC (One-Factor Non-Gaussian Copula) model such as OFDTC (One-Factor Double T-distribution Copula) model of Hull and White (2004) or NIGC (Normal Inverse Gaussian Copula) model of Kalemanova et al.(2005), SC<Stochastic Correlation) model of Burtschell et al.(2005), and FL (Forward Loss) model of Bennani (2005), I Investigate and compare three points: 1) appropriateness for portfolio loss distribution, 2) explanation for standardized tranche spread, 3) sensitivity for delta-neutral hedging strategy. To compare pricing models, parameter estimation for each model is preceded by using the term structure of iTraxx Europe index spread and the tranch spreads with different maturities and exercise prices Remarkable results of this study are as follows. First, the probability for loss interval determining mezzanine tranche spread is lower in all models except SC model than OFGC model. This result shows that all mαdels except SC model in some degree solve the implied correlation smile phenomenon, where the correlation coefficient of mezzanine tranche must be lower than other tranches when OFGC model is used. Second, in explaining standardized tranche spread, NIGC model is the best among various models with respect to relative error. When OFGC model is compared with OFDTC model, OFOTC model is better than OFGC model in explaining 5-year tranche spreads. But for 7-year or 10-year tranches, OFDTC model is better with respect to absolute error while OFGC model is better with respect to relative error. Third, the sensitivity sign of senior tranctle spread with respect to asset correlation is sometime negative in NIG model while it is positive in other models. This result implies that a long position may be taken by the issuers of synthet.ic COO as a correlation delta-neutral hedging strategy when OFGC model is used, while a short position may be taken when NIGC model is used.

Analyzing how the post-Soviet transition interacts with the crisis of market finance exhibits a new “greed-based economic system” in the making. Asset grabbing is at its core and hinders capital accumulation. All the various privatization schemes have triggered off asset grabbing, asset stripping, and asset tunneling. A global contagion of such behavior has spread the power and cohesion of managers/shareholders (oligarchs) worldwide. Financial asset grabbing is less straightforward, though much widespread, and operates in financial markets through new financial products, securitization, firms buying their own shares, hedge funds, stock price manipulation, short selling, and the distribution of stock options.Shadow banking, and more generally a global informal economy, results from grabbing strategies in financial markets that breach the formal rules of capitalism. In alleviating and circumventing the rules, the oligarchy paves the way for economic malpractices and crime, calling capitalist laws into question.In such context, systemic greed underlies unconstrained maximization of relative wealth, for which asset grabbing is a rational means, in a winner-take-all economy. At the present stage of our research, a greed-based economy cannot yet be theoretically defined as a transition either to a new phase of capitalism or to another different system.

This paper studies the pricing of collateralized debt obligation (CDO) using Monte Carlo and analytic methods. Both methods are developed within the framework of the reduced form model. One-factor Gaussian Copula is used for treating default correlations amongst the collateral portfolio. Based on the two methods, the portfolio loss, the expected loss in each CDO tranche, tranche spread, and the default delta sensitivity are analyzed with respect to different parameters such as maturity, default correlation, default intensity or hazard rate, and recovery rate. We provide a careful study of the effects of different parametric impact. Our results show that Monte Carlo method is slow and not robust in the calculation of default delta sensitivity. The analytic approach has comparative advantages for pricing CDO. We also employ empirical data to investigate the implied default correlation and base correlation of the CDO. The implication of extending the analytical approach to incorporating Levy processes is also discussed.

The case introduces students to the nature of collateralized debt obligations (CDO) and the CDO origination process, with emphasis on the corporate structure of the special purpose vehicles, cash flows to various CDO tranches, and motivation behind CDO origination. Students will learn to quantitatively evaluate the risk-return profile of CDO tranches with emphasis on the equity tranche (also known as “toxic waste”). This is ideal for MBA and advanced undergraduate level courses on financial markets, financial institutions, and investments. In the case, an associate at the Debt Capital Markets desk of Lehman Brothers prepares a CDO issuance for Western Asset. Western Asset had been contacted by a group of commercial banks eager to sell senior secured bank loans and high-yield corporate bonds to lower their capital requirements and free up capital for additional lending.

Risk-based clearing has been proposed by Rausser et al. (2010) for over-the-counter (OTC) derivatives. This paper aims to illustrate the application of risk-based margins to a case study of the mortgage-backed securities derivative portfolio of the American International Group (AIG) during the period 2005-2008. There exists sufficient publicly available information to examine AIG’s derivative portfolio and how that portfolio would depend on conjectural changes in margin requirements imposed on its OTC derivative positions. Generally, such data on OTC derivative portfolio positions are unavailable in the public domain, and thus, the AIG data provide a unique opportunity for an objective evaluation.

This paper uses modern financial methodology to evaluate risk-based margining and collateralization for the major OTC derivative portfolio of the AIG.

This analysis reveals that a risk-based margin procedure would have led to earlier margin calls of greater magnitude initially than the collateral calls actually faced by AIG Financial Products (AIGFP). The total margin ultimately required by the risk-based procedure, however, is similar in magnitude to the collateral calls faced by AIGFP by August 2008. It is likely that a risk-based clearing procedure applied to AIG’s OTC contracts would have led to the AIG undertaking significant hedging and liquidation of their OTC positions well before the losses built up to the point they had, perhaps avoiding the federal government’s orchestrated restructuring that occurred in September 2008.

There has been no published risk-based evaluations of a major OTC portfolio of derivatives for any company, let alone the AIG.

We propose a new model for the dynamics of the aggregate credit portfolio loss. The model is Markovian in two dimensions with the state variables being the total accumulated loss Lt and the stochastic default intensity λt. The dynamics of the default intensity are governed by the equation dλt=κ(ρ(Lt,t)−λt)dt+σλtdWt. The function ρ depends both on time t and accumulated loss Lt, providing sufficient freedom to calibrate the model to a generic distribution of loss. We develop a computationally efficient method for model calibration to the market of synthetic single tranche collateralized debt obligations (CDOs). The method is based on the Markovian projection technique which reduces the full model to a one-step Markov chain having the same marginal distributions of loss. We show that once the intensity function of the effective Markov chain consistent with the loss distribution implied by the tranches is found, the function ρ can be recovered with a very moderate computational effort. Because our model is Markovian and has low dimensionality, it offers a convenient framework for the pricing of dynamic credit instruments, such as options on indices and tranches, by backward induction. We calibrate the model to a set of recent market quotes on CDX index tranches and apply it to the pricing of tranche options.