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1 – 10 of 247Lijuan Cao, Zhang Jingqing, Lim Kian Guan and Zhonghui Zhao
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…
Abstract
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.
William E. Balson and Gordon Rausser
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…
Abstract
Purpose
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.
Design/methodology/approach
This paper uses modern financial methodology to evaluate risk-based margining and collateralization for the major OTC derivative portfolio of the AIG.
Findings
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.
Originality/value
There has been no published risk-based evaluations of a major OTC portfolio of derivatives for any company, let alone the AIG.
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Daniel Totouom and Margaret Armstrong
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…
Abstract
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.
David P. Stowell and Stephen Carlson
Hedge fund Magnetar Capital had returned 25 percent in 2007 with a strategy that posed significantly lower risk to investors than the S&P 500. Magnetar had made more than $1…
Abstract
Hedge fund Magnetar Capital had returned 25 percent in 2007 with a strategy that posed significantly lower risk to investors than the S&P 500. Magnetar had made more than $1 billion in profit by noticing that the equity tranche of CDOs and CDO-derivative instruments were relatively mispriced. It took advantage of this anomaly by purchasing CDO equity and buying credit default swap (CDS) protection on tranches that were considered less risky. Now it was the job of Alec Litowitz, chairman and chief investment officer, to provide guidance to his team as they planned next year's strategy, evaluate and prioritize their ideas, and generate new ideas of his own. An ocean away, Ron Beller was contemplating some very different issues. Beller's firm, Peloton Partners LLP, had been one of the top-performing hedge funds in 2007, returning in excess of 80 percent. In late January 2008 Beller accepted two prestigious awards at a black-tie EuroHedge ceremony. A month later, his firm was bankrupt. Beller shorted the U.S. housing market before the subprime crisis hit, and was paid handsomely for his bet. After the crisis began, however, he believed that prices for highly rated mortgage securities were being unfairly punished, so he decided to go long AAA-rated securities backed by Alt-A mortgage loans (between prime and subprime), levered 9x. The trade moved against Peloton in a big way on February 14, 2008, causing $17 billion in losses and closure of the firm.
This case analyzes the strategies of the two hedge funds, focusing on how money can be made and lost during a financial crisis. The role of investment banks as lenders to hedge funds such as Peloton is explored, as well as characteristics of the CDO market and an array of both mortgage-related and credit protection-related instruments that were actively used (for better or worse) by hedge funds during the credit crisis of 2007 and 2008.
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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…
Abstract
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.
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Mara Thiene, Luigi Galletto, Riccardo Scarpa and Vasco Boatto
Under investigation is Prosecco wine, a sparkling white wine from North‐East Italy. Information collection on consumer perceptions is particularly relevant when developing market…
Abstract
Purpose
Under investigation is Prosecco wine, a sparkling white wine from North‐East Italy. Information collection on consumer perceptions is particularly relevant when developing market strategies for wine, especially so when local production and certification of origin play an important role in the wine market of a given district, as in the case at hand. Investigating and characterizing the structure of preference heterogeneity become crucial steps in every successful marketing strategy. The purpose of this paper is to investigate the sources of systematic differences in consumer preferences.
Design/methodology/approach
The paper explores the effect of inclusion of answers to attitudinal questions in a latent class regression model of stated willingness to pay (WTP) for this specialty wine. These additional variables were included in the membership equations to investigate whether they could be of help in the identification of latent classes. The individual specific WTPs from the sampled respondents were then derived from the best fitting model and examined for consistency.
Findings
The use of answers to attitudinal question in the latent class regression model is found to improve model fit, thereby helping in the identification of latent classes. The best performing model obtained makes use of both attitudinal scores and socio‐economic covariates identifying five latent classes. A reasonable pattern of differences in WTP for Prosecco between CDO and TGI types were derived from this model.
Originality/value
The approach appears informative and promising: attitudes emerge as important ancillary indicators of taste differences for specialty wines. This might be of interest per se and of practical use in market segmentation. If future research shows that these variables can be of use in other contexts, it is quite possible that more attitudinal questions will be routinely incorporated in structural latent class hedonic models.
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In the convergence between the capital markets and reinsurance markets, the prime mover of insurance risk into capital markets have been investment banks. Also, among the most…
Abstract
In the convergence between the capital markets and reinsurance markets, the prime mover of insurance risk into capital markets have been investment banks. Also, among the most active leveraged underwriters of capital market credit risk are reinsurers, as opposed to hedge funds or banks. A key example of the institutional consequences of “convergence,” in particular of product design are Collateralized Debt Obligations (CDOs). CDOs combine a managed portfolio of bonds or loans with a hierarchy of claims or priority of loss payments (typical of insurance structures). Early buyers of CDOs were typically high‐yield bond portfolio managers. More recently, reinsurers have come to appreciate the “insurance nature” of these CDO structures, and multiline reinsurers have begun to support CDOs via financial guarantees.
Andrei V. Lopatin and Timur Misirpashaev
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…
Abstract
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.
Neil Fligstein and Adam Goldstein
The current crisis in the mortgage securitization industry highlights significant failures in our models of how markets work and our political will, organizational capability, and…
Abstract
The current crisis in the mortgage securitization industry highlights significant failures in our models of how markets work and our political will, organizational capability, and ideological desire to intervene in markets. This article shows that one of the main sources of failure has been the lack of a coherent understanding of how these markets came into existence, how tactics and strategies of the principal firms in these markets have evolved over time, and how we ended up with the economic collapse of the main firms. It seeks to provide some insight into these processes by compiling both historical and quantitative data on the emergence and spread of these tactics across the largest investment banks and their principal competitors from the mortgage origination industry. It ends by offering some policy proscriptions based on the analysis.
Lukasz Prorokowski and Hubert Prorokowski
This paper, based on case-studies with five universal banks from Europe and North America, aims to investigate which types of comprehensive risk measure (CRM) models are being…
Abstract
Purpose
This paper, based on case-studies with five universal banks from Europe and North America, aims to investigate which types of comprehensive risk measure (CRM) models are being used in the industry, the challenges being faced in implementation and how they are being currently rectified. Undoubtedly, CRM remains the most challenging and ambiguous measure applied to the correlation trading book. The turmoil surrounding the new regulatory framework boils down to the Basel Committee implementing a range of capital charges for market risk to promote “safer” banking in times of financial crisis. This report discusses current issues faced by global banks when complying with the complex set of financial rules imposed by Basel 2.5.
Design/methodology/approach
The current research project is based on in-depth, semi-structured interviews with five universal banks to explore the strides major banks are taking to introduce CRM modelling while complying with the new regulatory requirements.
Findings
There are three measures introduced by the Basel Committee to serve as capital charges for market risk: incremental risk charge; stressed value at risk and CRM. All of these regulatory-driven measures have met with strong criticism for their cumbersome nature and extremely high capital charges. Furthermore, with banks facing imminent implementation deadlines, all challenges surrounding CRM must be rectified. This paper provides some practical insights into how banks are finalising the new methodologies to comply with Basel 2.5.
Originality/value
The introduction of CRM and regulatory approval of new internal market risk models under Basel 2.5 has exerted strong pressure on global banks. The issues and computational challenges surrounding the implementation of CRM methodologies are currently fiercely debated among the affected banks. With little guidance from regulators, it remains very unclear how to implement, calculate and validate CRM in practice. To this end, a need for a study that sheds some light on practices with developing and computing CRM emerged. On submitting this paper to the journal, we have received news that JP Morgan is to pay four regulators $920 million as a result of a CRM-related scandal.
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