Volatility and Return Transmission among Cement Industry Stock Prices: an Application of Multivariate FIGARCH Modeling in High Frequency Financial time Series
Long memory in asset returns and volatilities is a new research area, both in theoretical and empirical modeling of high frequent financial time series. The most popular techniques of time series modeling with long memory is the ARFIMA-FIGARCH, but this fractionality in the integration of time serie...
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| Format: | Article |
| Language: | fas |
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Allameh Tabataba'i University Press
2011-06-01
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| Series: | فصلنامه پژوهشهای اقتصادی ایران |
| Subjects: | |
| Online Access: | https://ijer.atu.ac.ir/article_3201_5385c0561ac82aa4f9186f2923892b78.pdf |
| _version_ | 1797369369791037440 |
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| author | Gholamreza Keshavarz Haddad Seyed Babak Ebrahimi Akbar Jafar Abadi |
| author_facet | Gholamreza Keshavarz Haddad Seyed Babak Ebrahimi Akbar Jafar Abadi |
| author_sort | Gholamreza Keshavarz Haddad |
| collection | DOAJ |
| description | Long memory in asset returns and volatilities is a new research area, both in theoretical and empirical modeling of high frequent financial time series. The most popular techniques of time series modeling with long memory is the ARFIMA-FIGARCH, but this fractionality in the integration of time series modeling has not been extended to the Multivariate GARCH models yet. The present paper aims to extend the BEKK’s MGARCH models to take into account the presence of long memory in daily financial time series. Although the proposed procedure is highly non-linear in the fractionality parameters with a serious computational burden, it estimates all the parameters of mean and variance equations in a nonlinear framework and finds a unique solution, by numerical optimization procedures. In the empirical part of the paper a multivariate FIGARCH is used to check the transmission of volatility among the automobile industry, machinery leasing and equipment indices in the Tehran Stock Exchange. The results confirm the existence of short memory in both conditional means and conditional variances, and moreover the magnitude of estimated d parameter is remarkably different from those of resulted from GPH and single ARFIMA-FIGARCH. Empirical findings of the MFIGARCH specification were compared with those of BEKK, and the comparison shows that MFIGARCH estimations are consistent with theoretical considerations. Moreover, our findings confirm the presence of lead and lag effects and information flow between the returns and volatilities of automobile industries and machinery leasing stock prices, and a multilateral information transmission from machinery leasing’s stock towards the Auto industry and machinery parts manufacturing share prices is observed. |
| first_indexed | 2024-03-08T17:45:41Z |
| format | Article |
| id | doaj.art-3524d0645c47473ba97921a538e60c16 |
| institution | Directory Open Access Journal |
| issn | 1726-0728 2476-6445 |
| language | fas |
| last_indexed | 2024-03-08T17:45:41Z |
| publishDate | 2011-06-01 |
| publisher | Allameh Tabataba'i University Press |
| record_format | Article |
| series | فصلنامه پژوهشهای اقتصادی ایران |
| spelling | doaj.art-3524d0645c47473ba97921a538e60c162024-01-02T10:28:52ZfasAllameh Tabataba'i University Pressفصلنامه پژوهشهای اقتصادی ایران1726-07282476-64452011-06-0116471291623201Volatility and Return Transmission among Cement Industry Stock Prices: an Application of Multivariate FIGARCH Modeling in High Frequency Financial time SeriesGholamreza Keshavarz Haddad0Seyed Babak Ebrahimi1Akbar Jafar Abadi2Ph.D in Economics, Associate Professor, Faculty of Economics, Sharif University of Technology, Graduate School of Management and EconomicsPh.D. Candidate of Iran University Science & Technology, Department of Industrial EngineeringSenior Research ExpertLong memory in asset returns and volatilities is a new research area, both in theoretical and empirical modeling of high frequent financial time series. The most popular techniques of time series modeling with long memory is the ARFIMA-FIGARCH, but this fractionality in the integration of time series modeling has not been extended to the Multivariate GARCH models yet. The present paper aims to extend the BEKK’s MGARCH models to take into account the presence of long memory in daily financial time series. Although the proposed procedure is highly non-linear in the fractionality parameters with a serious computational burden, it estimates all the parameters of mean and variance equations in a nonlinear framework and finds a unique solution, by numerical optimization procedures. In the empirical part of the paper a multivariate FIGARCH is used to check the transmission of volatility among the automobile industry, machinery leasing and equipment indices in the Tehran Stock Exchange. The results confirm the existence of short memory in both conditional means and conditional variances, and moreover the magnitude of estimated d parameter is remarkably different from those of resulted from GPH and single ARFIMA-FIGARCH. Empirical findings of the MFIGARCH specification were compared with those of BEKK, and the comparison shows that MFIGARCH estimations are consistent with theoretical considerations. Moreover, our findings confirm the presence of lead and lag effects and information flow between the returns and volatilities of automobile industries and machinery leasing stock prices, and a multilateral information transmission from machinery leasing’s stock towards the Auto industry and machinery parts manufacturing share prices is observed.https://ijer.atu.ac.ir/article_3201_5385c0561ac82aa4f9186f2923892b78.pdfreturnvolatilitylong memorymultivariate figarch |
| spellingShingle | Gholamreza Keshavarz Haddad Seyed Babak Ebrahimi Akbar Jafar Abadi Volatility and Return Transmission among Cement Industry Stock Prices: an Application of Multivariate FIGARCH Modeling in High Frequency Financial time Series فصلنامه پژوهشهای اقتصادی ایران return volatility long memory multivariate figarch |
| title | Volatility and Return Transmission among Cement Industry Stock Prices: an Application of Multivariate FIGARCH Modeling in High Frequency Financial time Series |
| title_full | Volatility and Return Transmission among Cement Industry Stock Prices: an Application of Multivariate FIGARCH Modeling in High Frequency Financial time Series |
| title_fullStr | Volatility and Return Transmission among Cement Industry Stock Prices: an Application of Multivariate FIGARCH Modeling in High Frequency Financial time Series |
| title_full_unstemmed | Volatility and Return Transmission among Cement Industry Stock Prices: an Application of Multivariate FIGARCH Modeling in High Frequency Financial time Series |
| title_short | Volatility and Return Transmission among Cement Industry Stock Prices: an Application of Multivariate FIGARCH Modeling in High Frequency Financial time Series |
| title_sort | volatility and return transmission among cement industry stock prices an application of multivariate figarch modeling in high frequency financial time series |
| topic | return volatility long memory multivariate figarch |
| url | https://ijer.atu.ac.ir/article_3201_5385c0561ac82aa4f9186f2923892b78.pdf |
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