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GARCH - BEKK Approach to Volatility Behavior and Spillover : Evidence from India, China, Hong Kong, and Japan


Affiliations
1 Assistant Professor, Guru Gobind Singh Indraprastha University, Sector 16C, Dwarka, Delhi - 110 078, India
2 Research Scholar, Guru Gobind Singh Indraprastha University, New Delhi, India

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The present study investigated the volatility behavior and its spillover in stock markets of four Asian countries namely : India, China, Hong Kong, and Japan. ARCH, GARCH (1, 1), and bivariate GARCH - BEKK model was applied to examine and explore the volatility behavior and its spillover from one country to another. The results of the study indicated that the Chinese market suffered the greatest fluctuation and the Indian financial market was the most stable market amongst the chosen markets. A strong regional economic integration and analogous growth pattern was observed between Hong Kong and India. The results further hinted that previous volatility had more impact on the current volatility in comparison to the shocks or news coming to the markets as GARCH coefficient was found to be much larger than ARCH coefficient for each of the markets. The stock market of China was less sensitive to its past shocks ; whereas, the stock market of Japan was the most sensitive to its own past shocks. The GARCH coefficient was highest for China. Therefore, it may be concluded that volatility was more persistent in Chinese markets. According to GARCH - BEKK, information was shared swiftly between stock markets of all the countries, however, with a varied degree. The cross market ARCH effect was strongest between China and Japan followed by Hong Kong and Japan, and it was weakest for China and India. Persistency of cross market volatility was highest for the pair of China and India followed by Hong Kong and India, and lowest for China and Japan.

Keywords

Volatility, Volatility Spillovers, GARCH-BEKK Models, ARCH Effect, GARCH Effect

C58, C49, F65, F63

Paper Submission Date : September 5, 2017 ; Paper sent back for Revision : March 3, 2018 ; Paper Acceptance Date : March 22, 2018.

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  • GARCH - BEKK Approach to Volatility Behavior and Spillover : Evidence from India, China, Hong Kong, and Japan

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Authors

Ashish Kumar
Assistant Professor, Guru Gobind Singh Indraprastha University, Sector 16C, Dwarka, Delhi - 110 078, India
Swati Khanna
Research Scholar, Guru Gobind Singh Indraprastha University, New Delhi, India

Abstract


The present study investigated the volatility behavior and its spillover in stock markets of four Asian countries namely : India, China, Hong Kong, and Japan. ARCH, GARCH (1, 1), and bivariate GARCH - BEKK model was applied to examine and explore the volatility behavior and its spillover from one country to another. The results of the study indicated that the Chinese market suffered the greatest fluctuation and the Indian financial market was the most stable market amongst the chosen markets. A strong regional economic integration and analogous growth pattern was observed between Hong Kong and India. The results further hinted that previous volatility had more impact on the current volatility in comparison to the shocks or news coming to the markets as GARCH coefficient was found to be much larger than ARCH coefficient for each of the markets. The stock market of China was less sensitive to its past shocks ; whereas, the stock market of Japan was the most sensitive to its own past shocks. The GARCH coefficient was highest for China. Therefore, it may be concluded that volatility was more persistent in Chinese markets. According to GARCH - BEKK, information was shared swiftly between stock markets of all the countries, however, with a varied degree. The cross market ARCH effect was strongest between China and Japan followed by Hong Kong and Japan, and it was weakest for China and India. Persistency of cross market volatility was highest for the pair of China and India followed by Hong Kong and India, and lowest for China and Japan.

Keywords


Volatility, Volatility Spillovers, GARCH-BEKK Models, ARCH Effect, GARCH Effect

C58, C49, F65, F63

Paper Submission Date : September 5, 2017 ; Paper sent back for Revision : March 3, 2018 ; Paper Acceptance Date : March 22, 2018.




DOI: https://doi.org/10.17010/ijf%2F2018%2Fv12i4%2F122791