Abstract—This research applied closing price return for ASEAN ETFs. Comparing the long memory in volatility and asymmetric volatility of ASEAN ETFs, this research used four models, fractional autoregressive integrated moving average (ARFIMA), a hybrid of ARFIMA and fractionally integrated generalized autoregressive conditional heteroscedasticity (ARFIMA-FIGARCH), ARFIMA with fractionally integrated asymmetric power autoregressive conditional heteroscedasticity (ARFIMA-FIAPARCH) and ARFIMA with hyperbolic generalized autoregressive conditional heteroscedasticity (ARFIMA-HYGARCH) models. The results show that by using closing price return data samples ASEAN ETF have a long memory in volatility and negative asymmetric volatility. ARFIMA-FIAPARCH model perform better to investigate long memory in volatility and asymmetric volatility for ASEAN ETF. This findings can be evaluated by academicians, financial risk managers, investors, and regulators.
Index Terms—Long memory in volatility, asymmetric volatility, ASEAN ETF.
Maya Malinda is with the Universitas Kristen Maranatha (Maranatha Christian University), Indonesia (e-mail: hmy.malinda@yahoo.com).
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Cite: Maya Malinda, "Long Memory in Asymmetric Volatility of Asean Exchange-Traded Funds," International Journal of Trade, Economics and Finance vol.8, no.2, pp. 78-82, 2017.