This research investigates the existence of persistent temporal dependence in the returns and volatility of seven Asian emerging market (EM) exchange-traded funds (ETFs) from 2008 to 2013 using fractionally-integrated models. This paper finds that SPDR S&P China ETF (ticker: GXC) and Wisdom Tree Indian Rupee Fund (ICN) ETFs have intermediate memory, which characterizes the strong tendency of these ETFs to mean revert. This study also finds long memory properties in the volatility structures of most Asian EM ETF, which is a possible sign of market inefficiency, and can be exploited by financial traders in the long-term through a “hold” strategy to earn excess returns. Moreover, the log-likelihood values point to the ARFIMA-HYGARCH models as the best fitting models compared to the ARFIMA and ARFIMA-FIGARCH models.
Asian emerging markets, exchange-traded funds, long-memory models
