The Experts below are selected from a list of 42279 Experts worldwide ranked by ideXlab platform
Nader Naifar - One of the best experts on this subject based on the ideXlab platform.
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Credit Default Sharing Instead of Credit Default Swaps: Toward a More Sustainable Financial System
Journal of Economic Issues, 2014Co-Authors: Nader NaifarAbstract:The central cause of all recent financial crises (including the Asian financial crisis, the European debt crisis, and the subprime mortgage crisis) was the debt crisis. The primary objective of this study is to examine the principles of risk-sharing promoted by Islamic finance as a possible reform of or complement to the current financial system. The secondary objective of this paper is to explain how and why the famous Credit Default swaps (CDSs) markets expanded and why they contributed to the recent financial crisis. In addition, I propose a new financial instrument to hedge Default risk (Credit Default sharing) based on the principles of risk-sharing and Islamic insurance, takaful (sharing responsibility and mutual cooperation), as a substitute for CDSs. I explain that Credit Default sharing can reduce counterparty risk, improve banks' monitoring incentives, reduce systemic risk and contagion in financial systems, and eliminate "empty Creditors."
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THE DETERMINANTS OF Credit Default SWAP RATES: AN EXPLANATORY STUDY
International Journal of Theoretical and Applied Finance, 2006Co-Authors: Fathi Abid, Nader NaifarAbstract:The aim of this paper is to explain empirically the determinants of Credit Default swap rates using a linear regression. We document that the majority of variables, detected from the Credit risk pricing theories, explain more than 60% of the total level of Credit Default swap. These theoretical variables are Credit rating, maturity, riskless interest rate, slope of the yield curve and volatility of equities. The estimated coefficients for the majority of these variables are consistent with theory and they are significant both statistically and economically. We conclude that Credit rating is the most determinant of Credit Default swap rates.
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Credit‐Default swap rates and equity volatility: a nonlinear relationship
The Journal of Risk Finance, 2006Co-Authors: Fathi Abid, Nader NaifarAbstract:Purpose – The aim of this paper is to study the impact of equity returns volatility of reference entities on Credit‐Default swap rates using a new dataset from the Japanese market.Design/methodology/approach – Using a copula approach, the paper models the different relationships that can exist in different ranges of behavior. It studies the bivariate distributions of Credit‐Default swap rates and equity return volatility estimated with GARCH (1,1) and focus on one parameter Archimedean copula.Findings – First, the paper emphasizes the finding that pairs with higher rating present a weaker dependence coefficient and then, the impact of equity returns volatility on Credit‐Default swap rates is higher for the lowest rating class. Second, the dependence structure is positive and asymmetric indicating that protection sellers ask for higher Credit‐Default swap returns to compensate the higher Credit risk incurred by low rating class.Practical implications – The paper has several practical implications that are ...
Shajeehan Kathirgamanathan - One of the best experts on this subject based on the ideXlab platform.
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IJCNN - Credit Default swap pricing using artificial neural networks
The 2010 International Joint Conference on Neural Networks (IJCNN), 2010Co-Authors: Khaled Bashir Shaban, Abdunnaser Younes, Robert Lam, Michael Allison, Shajeehan KathirgamanathanAbstract:The Credit derivatives market has experienced unprecedented growth over the past few years. As such, there is a growing interest in tools for pricing the most prominent Credit derivative, the Credit Default swap. In this paper, we present several artificial neural networks that predict real-world Credit Default swap prices. In addition to the input parameters used by analytical pricing strategies, these networks explore the use of historic Credit Default swap prices and equity prices. It was found that the inclusion of historic parameters has increased the accuracy of the network's prediction of Credit Default swap prices‥
Marek Rutkowski - One of the best experts on this subject based on the ideXlab platform.
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Hedging of a Credit Default swaption in the CIR Default intensity model
Finance and Stochastics, 2010Co-Authors: Tomasz R. Bielecki, Monique Jeanblanc, Marek RutkowskiAbstract:An important issue arising in the context of Credit Default swap (CDS) rates is the construction of an appropriate model in which a family of options written on Credit Default swaps, referred to hereafter as Credit Default swaptions, can be valued and hedged. The goal of this work is to exemplify the usefulness of some abstract hedging results, which were obtained previously by the authors, for the valuation and hedging of the Credit Default swaption in a particular hazard process setup, namely, the CIR Default intensity model.
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Valuation of Credit Default Swaptions and Credit Default Index Swaptions
2009Co-Authors: Marek RutkowskiAbstract:The paper provides simple and rigorous, albeit fairly general, derivations of valuation formulae for Credit Default swaptions and Credit Default index swaptions. Results of this work cover as special cases the pricing formulae derived previously by Jamshidian [Finance and Stochastics 8 (2004) 343–371], Pedersen [Quantitative Credit Research (2003)], Brigo and Morini (2005), and Morini and Brigo (2007). Most results presented in this work are completely independent of a particular convention regarding the specification of the fee and protection legs and thus they can also be used for valuation of other Credit derivatives that exhibit similar features (for instance, options on CDO tranches). The main tools are a judicious choice of the reference filtration and a suitable specification of the risk-neutral dynamics for the pre-Default (loss-adjusted) fair market spread.
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pricing and trading Credit Default swaps in a hazard process model
Annals of Applied Probability, 2008Co-Authors: Tomasz R. Bielecki, Monique Jeanblanc, Marek RutkowskiAbstract:In the paper we study dynamics of the arbitrage prices of Credit Default swaps within a hazard process model of Credit risk. We derive these dynamics without postulating that the immersion property is satisfied between some relevant filtrations. These results are then applied so to study the problem of replication of general Defaultable claims, including some basket claims, by means of dynamic trading of Credit Default swaps.
Alan White - One of the best experts on this subject based on the ideXlab platform.
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the relationship between Credit Default swap spreads bond yields and Credit rating announcements
Journal of Banking and Finance, 2004Co-Authors: John C Hull, Mirela Predescu, Alan WhiteAbstract:A company’s Credit Default swap spread is the cost per annum for protection against a Default by the company. In this paper we analyze data on Credit Default swap spreads collected by a Credit derivatives broker. We first examine the relationship between Credit Default spreads and bond yields and reach conclusions on the benchmark risk-free rate used by participants in the Credit derivatives market. We then carry out a series of tests to explore the extent to which Credit rating announcements by Moody’s are anticipated by participants in the Credit Default swap market.
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The Valuation of Credit Default Swap Options
The Journal of Derivatives, 2003Co-Authors: John Hull, Alan WhiteAbstract:One of the major financial market developments of the last few years has been extending derivatives technology to the realm of Credit risk, with the “plain vanilla” product being the Credit Default swap (CDS). And as with earlier derivative innovations, more exotic flavors are rapidly being created. In this article, Hull and White present the basic valuation theory for forwards and options on Credit Default swaps. The two key aspects of risk in a CDS are the probability of a Default and the recovery rate given a Default. Interestingly, in calibrating the CDS forward and option models to market CDS spreads, the trade-off between the two risk elements makes model valuations quite insensitive to the specific assumption about recovery.
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Valuing Credit Default Swaps Ii: Modeling Default Correlations
2000Co-Authors: John Hull, Alan WhiteAbstract:This paper extends the analysis in Valuing Credit Default Swaps I: No Counter party Default Risk to provide a methodology for valuing Credit Default swaps that takesaccount of counterparty Default risk and allows the payoff to be contingent on Defaults by multiple reference entities. It develops a model of Default correlations between different corporate or sovereign entities. The model is applied to the valuation of vanilla Credit Default swaps when the seller may Default and to the valuation of basket Credit Default swaps.
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Valuing Credit Default Swaps I: No Counterparty Default Risk
2000Co-Authors: John Hull, Alan WhiteAbstract:This paper provides a methodology for valuing Credit Default swaps when the payoff is contingent on Default by a single reference entity and there is no counterparty Defaultrisk. The paper tests the sensitivity of Credit Default swap valuations to assumptions about the expected recovery rate. It also tests whether approximate no-arbitrage arguments give accurate valuations and provides an example of the application of the methodology to real data. In a companion paper entitled Valuing Credit Default Swaps II: Modeling Default Correlation, the analysis is extended to cover situations where the payoff is contingent on Default by multiple reference entities and situations where there is counterparty Defaultrisk.
Khaled Bashir Shaban - One of the best experts on this subject based on the ideXlab platform.
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IJCNN - Credit Default swap pricing using artificial neural networks
The 2010 International Joint Conference on Neural Networks (IJCNN), 2010Co-Authors: Khaled Bashir Shaban, Abdunnaser Younes, Robert Lam, Michael Allison, Shajeehan KathirgamanathanAbstract:The Credit derivatives market has experienced unprecedented growth over the past few years. As such, there is a growing interest in tools for pricing the most prominent Credit derivative, the Credit Default swap. In this paper, we present several artificial neural networks that predict real-world Credit Default swap prices. In addition to the input parameters used by analytical pricing strategies, these networks explore the use of historic Credit Default swap prices and equity prices. It was found that the inclusion of historic parameters has increased the accuracy of the network's prediction of Credit Default swap prices‥
