Long Memory in Asymmetric Volatility of Asean Exchange-Traded Funds

Maya Malinda
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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.
东盟交易所交易基金非对称波动的长记忆效应
本研究以东盟etf收盘价格回报为研究对象。本文采用分数阶自回归综合移动平均(ARFIMA)、分数阶自回归综合移动平均(ARFIMA)与分数阶综合广义自回归条件异方差(ARFIMA- figarch)、分数积分非对称功率自回归条件异方差(ARFIMA- fiaparch)和双曲广义自回归条件异方差(ARFIMA- hygarch)模型的ARFIMA。结果表明,采用收盘价收益率数据样本,东盟ETF在波动率和负非对称波动率方面具有较长的记忆。ARFIMA-FIAPARCH模型对东盟ETF波动率和非对称波动率的长记忆性研究效果较好。这些发现可以由学者、金融风险管理者、投资者和监管机构进行评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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