The Study of the Long Memory in Volatility of Renewable Energy Exchange-Traded Funds (ETFs)

Malinda, Maya and Chen, Jo-Hui (2016) The Study of the Long Memory in Volatility of Renewable Energy Exchange-Traded Funds (ETFs). Journal of Economics, Business and Management, 4 (4). pp. 1-6. ISSN 2301-3567

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Abstract

This research applied original price return and adjustment price return for both renewable and unrenewable energy ETFs. Comparing the long memory in volatility and asymmetric volatility of renewable and unrenewable energy ETFs, this study used three models, fractional autoregressive integrated moving average (ARFIMA), a combination of ARFIMA and fractionally integrated exponentially generalized autoregressive conditional heteroscedasticity (ARFIMA-FIEGARCH) and ARFIMA with hyperbolic generalized autoregressive conditional heteroscedasticity (ARFIMA-HYGARCH) models. The results show that by using the adjustment price return data samples, then the results are similar with original price return ETFs. Both unrenewable and renewable energy ETFs have a long memory in volatility and negative asymmetric volatility. ARFIMA-FIEGARCH model perform better to investigate long memory in volatility and asymmetric volatility for both energy ETFs among others.

Item Type:	Article
Uncontrolled Keywords:	Long memory in volatility, asymmetric volatility, renewable energy ETFs.
Subjects:	H Social Sciences > HG Finance
Divisions:	Fakultas Ekonomi > S-1 Manajemen
Depositing User:	admin LPPM
Date Deposited:	21 Feb 2018 08:41
Last Modified:	21 Feb 2018 08:41
URI:	http://repository.lppm.maranatha.edu/id/eprint/421

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