Application of RQMC for CDO Pricing with Stochastic Correlations under Nonhomogeneous Assumptions

In consideration of that the correlation between any two assets of the asset pool is always stochastic in the actual market and that collateralized debt obligation (CDO) pricing models under nonhomogeneous assumptions have no semianalytic solutions, we designed a numerical algorithm based on randomi...

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Main Authors: Shuanghong Qu, Lingxian Meng, Hua Li
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2022/3243450
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author Shuanghong Qu
Lingxian Meng
Hua Li
author_facet Shuanghong Qu
Lingxian Meng
Hua Li
author_sort Shuanghong Qu
collection DOAJ
description In consideration of that the correlation between any two assets of the asset pool is always stochastic in the actual market and that collateralized debt obligation (CDO) pricing models under nonhomogeneous assumptions have no semianalytic solutions, we designed a numerical algorithm based on randomized quasi-Monte Carlo (RQMC) simulation method for CDO pricing with stochastic correlations under nonhomogeneous assumptions and took Gaussian factor copula model as an example to conduct experiments. The simulation results of RQMC and Monte Carlo (MC) method were compared from the perspective of variance changes. The results showed that this numerical algorithm was feasible, efficient, and stable for CDO pricing with stochastic correlation under nonhomogeneous assumptions. This numerical algorithm is expected to be extended to other factor Copula models for CDO pricing with stochastic correlations under nonhomogeneous assumptions.
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institution Kabale University
issn 1099-0526
language English
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publisher Wiley
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series Complexity
spelling doaj-art-879a0c0f62344cf991da5995141dfa6e2025-02-03T05:49:23ZengWileyComplexity1099-05262022-01-01202210.1155/2022/3243450Application of RQMC for CDO Pricing with Stochastic Correlations under Nonhomogeneous AssumptionsShuanghong Qu0Lingxian Meng1Hua Li2College of Mathematics and Information ScienceCollege of Mathematics and Information ScienceSchool of Mathematics and StatisticsIn consideration of that the correlation between any two assets of the asset pool is always stochastic in the actual market and that collateralized debt obligation (CDO) pricing models under nonhomogeneous assumptions have no semianalytic solutions, we designed a numerical algorithm based on randomized quasi-Monte Carlo (RQMC) simulation method for CDO pricing with stochastic correlations under nonhomogeneous assumptions and took Gaussian factor copula model as an example to conduct experiments. The simulation results of RQMC and Monte Carlo (MC) method were compared from the perspective of variance changes. The results showed that this numerical algorithm was feasible, efficient, and stable for CDO pricing with stochastic correlation under nonhomogeneous assumptions. This numerical algorithm is expected to be extended to other factor Copula models for CDO pricing with stochastic correlations under nonhomogeneous assumptions.http://dx.doi.org/10.1155/2022/3243450
spellingShingle Shuanghong Qu
Lingxian Meng
Hua Li
Application of RQMC for CDO Pricing with Stochastic Correlations under Nonhomogeneous Assumptions
Complexity
title Application of RQMC for CDO Pricing with Stochastic Correlations under Nonhomogeneous Assumptions
title_full Application of RQMC for CDO Pricing with Stochastic Correlations under Nonhomogeneous Assumptions
title_fullStr Application of RQMC for CDO Pricing with Stochastic Correlations under Nonhomogeneous Assumptions
title_full_unstemmed Application of RQMC for CDO Pricing with Stochastic Correlations under Nonhomogeneous Assumptions
title_short Application of RQMC for CDO Pricing with Stochastic Correlations under Nonhomogeneous Assumptions
title_sort application of rqmc for cdo pricing with stochastic correlations under nonhomogeneous assumptions
url http://dx.doi.org/10.1155/2022/3243450
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