An Empirical Study of Pricing and Hedging Collateralized Debt Obligation
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 th...
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sg-smu-ink.lkcsb_research-19732011-01-25T06:14:30Z An Empirical Study of Pricing and Hedging Collateralized Debt Obligation Cao, Lijuan Zhang, Jingqing LIM, Kian Guan ZHAO, Zhonghui 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 2007-01-01T08:00:00Z text https://ink.library.smu.edu.sg/lkcsb_research/974 info:doi/10.1016/S0731-9053(08)22002-5 https://doi.org/10.1016/S0731-9053(08)22002-5 Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University Collateral debt obligation (CDO) pricing Monte Carlo Default correlation Copula Finance and Financial Management Portfolio and Security Analysis |
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Collateral debt obligation (CDO) pricing Monte Carlo Default correlation Copula Finance and Financial Management Portfolio and Security Analysis Cao, Lijuan Zhang, Jingqing LIM, Kian Guan ZHAO, Zhonghui An Empirical Study of Pricing and Hedging Collateralized Debt Obligation |
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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 |
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text |
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Cao, Lijuan Zhang, Jingqing LIM, Kian Guan ZHAO, Zhonghui |
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Cao, Lijuan Zhang, Jingqing LIM, Kian Guan ZHAO, Zhonghui |
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Cao, Lijuan |
title |
An Empirical Study of Pricing and Hedging Collateralized Debt Obligation |
title_short |
An Empirical Study of Pricing and Hedging Collateralized Debt Obligation |
title_full |
An Empirical Study of Pricing and Hedging Collateralized Debt Obligation |
title_fullStr |
An Empirical Study of Pricing and Hedging Collateralized Debt Obligation |
title_full_unstemmed |
An Empirical Study of Pricing and Hedging Collateralized Debt Obligation |
title_sort |
empirical study of pricing and hedging collateralized debt obligation |
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Institutional Knowledge at Singapore Management University |
publishDate |
2007 |
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https://ink.library.smu.edu.sg/lkcsb_research/974 https://doi.org/10.1016/S0731-9053(08)22002-5 |
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