Interconnectedness and Spillover Effects amongst Stock Markets of the US, China, Germany, Japan and India using DCC-GARCH Model and Diebold Yilmaz Method
In a rapidly globalising world, economic boundaries are dissolving as stakeholders seek broader opportunities. Corporations are now multinational, and investors are increasingly turning to global stock markets to maximise gains. Volatility serves as a crucial benchmark, guiding investment decisions...
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Faculty of Management & Finance, University of Colombo
2024-12-01
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| Series: | Colombo Business Journal |
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| Online Access: | https://mgmt.cmb.ac.lk/cbj/wp-content/uploads/2024/12/7.-CBJ-V15I2-Interconnectedness-amongst-Stock-Indices.pdf |
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| author | Archana Agarwal Nidhi Dhankhar Sunita Mehla |
| author_facet | Archana Agarwal Nidhi Dhankhar Sunita Mehla |
| author_sort | Archana Agarwal |
| collection | DOAJ |
| description | In a rapidly globalising world, economic boundaries are dissolving as stakeholders seek broader opportunities. Corporations are now multinational, and investors are increasingly turning to global stock markets to maximise gains. Volatility serves as a crucial benchmark, guiding investment decisions in this interconnected landscape. The current study looks at the time-varying spillover effects of the returns of the indices from January 6, 2020, until March 15, 2024, of the five economies of the world, namely, the S&P (United States), SSE (China), Nikkei (Japan), DAX (Germany), and Nifty (India). The conditional correlations and volatility spillovers are measured using the DCC-GARCH model and the Diebold and Yilmaz method. The study concludes that the transmission of information between the indices occurs in the long run except between Germany and China. Further, Germany and the US are net transmitters of volatility spillover, while China, Japan, and India are net receivers. The total spillover among the indices of these five economies is 39.37%. |
| format | Article |
| id | doaj-art-362067eed624478d8c265c2859515089 |
| institution | Kabale University |
| issn | 1800-363X 2579-2210 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Faculty of Management & Finance, University of Colombo |
| record_format | Article |
| series | Colombo Business Journal |
| spelling | doaj-art-362067eed624478d8c265c28595150892025-01-04T08:24:56ZengFaculty of Management & Finance, University of ColomboColombo Business Journal1800-363X2579-22102024-12-0115216218910.4038/cbj.v15i2.197Interconnectedness and Spillover Effects amongst Stock Markets of the US, China, Germany, Japan and India using DCC-GARCH Model and Diebold Yilmaz MethodArchana Agarwal0Nidhi Dhankhar1https://orcid.org/0009-0002-4402-0938Sunita Mehla2Department of Commerce, Sri Aurobindo College (E), University of Delhi, IndiaDepartment of Business Management, CCS HAU Hisar, IndiaDepartment of Business Management, CCS HAU Hisar, IndiaIn a rapidly globalising world, economic boundaries are dissolving as stakeholders seek broader opportunities. Corporations are now multinational, and investors are increasingly turning to global stock markets to maximise gains. Volatility serves as a crucial benchmark, guiding investment decisions in this interconnected landscape. The current study looks at the time-varying spillover effects of the returns of the indices from January 6, 2020, until March 15, 2024, of the five economies of the world, namely, the S&P (United States), SSE (China), Nikkei (Japan), DAX (Germany), and Nifty (India). The conditional correlations and volatility spillovers are measured using the DCC-GARCH model and the Diebold and Yilmaz method. The study concludes that the transmission of information between the indices occurs in the long run except between Germany and China. Further, Germany and the US are net transmitters of volatility spillover, while China, Japan, and India are net receivers. The total spillover among the indices of these five economies is 39.37%.https://mgmt.cmb.ac.lk/cbj/wp-content/uploads/2024/12/7.-CBJ-V15I2-Interconnectedness-amongst-Stock-Indices.pdfdcc-garch modeldiebold and yilmaz methoddynamic connectednesstransmission of informationvolatility spillover |
| spellingShingle | Archana Agarwal Nidhi Dhankhar Sunita Mehla Interconnectedness and Spillover Effects amongst Stock Markets of the US, China, Germany, Japan and India using DCC-GARCH Model and Diebold Yilmaz Method Colombo Business Journal dcc-garch model diebold and yilmaz method dynamic connectedness transmission of information volatility spillover |
| title | Interconnectedness and Spillover Effects amongst Stock Markets of the US, China, Germany, Japan and India using DCC-GARCH Model and Diebold Yilmaz Method |
| title_full | Interconnectedness and Spillover Effects amongst Stock Markets of the US, China, Germany, Japan and India using DCC-GARCH Model and Diebold Yilmaz Method |
| title_fullStr | Interconnectedness and Spillover Effects amongst Stock Markets of the US, China, Germany, Japan and India using DCC-GARCH Model and Diebold Yilmaz Method |
| title_full_unstemmed | Interconnectedness and Spillover Effects amongst Stock Markets of the US, China, Germany, Japan and India using DCC-GARCH Model and Diebold Yilmaz Method |
| title_short | Interconnectedness and Spillover Effects amongst Stock Markets of the US, China, Germany, Japan and India using DCC-GARCH Model and Diebold Yilmaz Method |
| title_sort | interconnectedness and spillover effects amongst stock markets of the us china germany japan and india using dcc garch model and diebold yilmaz method |
| topic | dcc-garch model diebold and yilmaz method dynamic connectedness transmission of information volatility spillover |
| url | https://mgmt.cmb.ac.lk/cbj/wp-content/uploads/2024/12/7.-CBJ-V15I2-Interconnectedness-amongst-Stock-Indices.pdf |
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