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Auteurs principaux: Shiraya, Kenichiro, Suzuki, Kanji, Yamakami, Tomohisa
Format: Preprint
Publié: 2024
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Accès en ligne:https://arxiv.org/abs/2411.08246
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author Shiraya, Kenichiro
Suzuki, Kanji
Yamakami, Tomohisa
author_facet Shiraya, Kenichiro
Suzuki, Kanji
Yamakami, Tomohisa
contents Two formulations are proposed to filter out correlations in the residuals of the multivariate GARCH model. The first approach is to estimate the correlation matrix as a parameter and transform any joint distribution to have an arbitrary correlation matrix. The second approach transforms time series data into an uncorrelated residual based on the eigenvalue decomposition of a correlation matrix. The empirical performance of these methods is examined through a prediction task for foreign exchange rates and compared with other methodologies in terms of the out-of-sample likelihood. By using these approaches, the DCC-GARCH residual can be almost independent.
format Preprint
id arxiv_https___arxiv_org_abs_2411_08246
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle New approaches of the DCC-GARCH residual: Application to foreign exchange rates
Shiraya, Kenichiro
Suzuki, Kanji
Yamakami, Tomohisa
Statistical Finance
Two formulations are proposed to filter out correlations in the residuals of the multivariate GARCH model. The first approach is to estimate the correlation matrix as a parameter and transform any joint distribution to have an arbitrary correlation matrix. The second approach transforms time series data into an uncorrelated residual based on the eigenvalue decomposition of a correlation matrix. The empirical performance of these methods is examined through a prediction task for foreign exchange rates and compared with other methodologies in terms of the out-of-sample likelihood. By using these approaches, the DCC-GARCH residual can be almost independent.
title New approaches of the DCC-GARCH residual: Application to foreign exchange rates
topic Statistical Finance
url https://arxiv.org/abs/2411.08246