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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.

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.

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.

Both consumer and corporate credit ratings agencies played a major role in the US subprime mortgage crisis. Equifax, Experian, and TransUnion deployed a formalized scoring system to assess individuals in mortgage origination, mortgage pools then were assessed for securitization by Moody's, S&P, and Fitch relying on expert judgment aided by formal models. What can we learn about the limits of formalization from the crisis? We discuss five problems responsible for the rating failures – reactivity, endogeneity, learning, correlated outcomes, and conflict of interest – and compare the way consumer and corporate rating agencies tackled these difficulties. We conclude with some policy lessons.

Directors help determine the strategic direction of a corporation and are responsible for ensuring the institution has a good system of internal control. Banking institutions without a strategic direction emphasizing sound lending practices that promote the long-run financial health and viability of the institution will be sued more frequently than peer institutions. Institutions that do not have a good system of internal control will also be sued more frequently. Hence, legal expense is a bank corporate governance measure. We compare the performance of bank legal expense and a widely cited corporate governance index in a regression framework to determine which better predicts bank performance. The regressions indicate legal expense is a much better predictor, hence a better measure of bank corporate governance. Regulators should require legal expense reporting and rank institutions by the ratio of legal expense to assets to help identify institutions with weak governance. Seven case studies illustrate the role of legal expense in corporate governance.