Multivariate rotated ARCH models
This paper introduces a new class of multivariate volatility models which is easy to estimate using covariance targeting, even with rich dynamics. We call them rotated ARCH (RARCH) models. The basic structure is to rotate the returns and then to fit them using a BEKK-type parameterization of the tim...
| Principais autores: | , , |
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| Formato: | Working paper |
| Publicado em: |
University of Oxford
2012
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| _version_ | 1826268280688476160 |
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| author | Noureldin, D Shephard, N Sheppard, K |
| author_facet | Noureldin, D Shephard, N Sheppard, K |
| author_sort | Noureldin, D |
| collection | OXFORD |
| description | This paper introduces a new class of multivariate volatility models which is easy to estimate using covariance targeting, even with rich dynamics. We call them rotated ARCH (RARCH) models. The basic structure is to rotate the returns and then to fit them using a BEKK-type parameterization of the time-varying covariance whose long-run covariance is the identity matrix. The extension to DCC-type parameterizations is given, introducing the rotated conditional correlation (RCC) model. Inference for these mdoels is computationally attractive, and the asymptotics are standard. The techniques are illustrated using data on some SJIA stocks. |
| first_indexed | 2024-03-06T21:07:15Z |
| format | Working paper |
| id | oxford-uuid:3ce5270c-f1b7-4302-bdc1-3df0d0cf53a5 |
| institution | University of Oxford |
| last_indexed | 2024-03-06T21:07:15Z |
| publishDate | 2012 |
| publisher | University of Oxford |
| record_format | dspace |
| spelling | oxford-uuid:3ce5270c-f1b7-4302-bdc1-3df0d0cf53a52022-03-26T14:16:17ZMultivariate rotated ARCH modelsWorking paperhttp://purl.org/coar/resource_type/c_8042uuid:3ce5270c-f1b7-4302-bdc1-3df0d0cf53a5Bulk import via SwordSymplectic ElementsUniversity of Oxford2012Noureldin, DShephard, NSheppard, KThis paper introduces a new class of multivariate volatility models which is easy to estimate using covariance targeting, even with rich dynamics. We call them rotated ARCH (RARCH) models. The basic structure is to rotate the returns and then to fit them using a BEKK-type parameterization of the time-varying covariance whose long-run covariance is the identity matrix. The extension to DCC-type parameterizations is given, introducing the rotated conditional correlation (RCC) model. Inference for these mdoels is computationally attractive, and the asymptotics are standard. The techniques are illustrated using data on some SJIA stocks. |
| spellingShingle | Noureldin, D Shephard, N Sheppard, K Multivariate rotated ARCH models |
| title | Multivariate rotated ARCH models |
| title_full | Multivariate rotated ARCH models |
| title_fullStr | Multivariate rotated ARCH models |
| title_full_unstemmed | Multivariate rotated ARCH models |
| title_short | Multivariate rotated ARCH models |
| title_sort | multivariate rotated arch models |
| work_keys_str_mv | AT noureldind multivariaterotatedarchmodels AT shephardn multivariaterotatedarchmodels AT sheppardk multivariaterotatedarchmodels |