Abstract
This paper examines the market efficiency of Energy Exchange-Traded Funds (ETFs) of both renewable and unrenewable energy ETFs. We adopt GARCH modelling approach to investigate the long-range dependence in ETFs volatility. Specifically, we estimate a FIGARCH model proposed by Baillie et al. (1996) using daily returns. We find evidence of long memory dependence in all ETFs, implying that, all the indexes under investigation are weak-form inefficient. The results also indicate that the volatility has a predictable structure in all the ETFs of both renewable and unrenewable energy ETFs, indicating the potential of diversification for the international investors.
Highlights
Most existing literature focus on investigating long-term memory in stock markets returns, fixed income markets returns, or commodity markets returns
While comparing different generalized ARCH (GARCH) family models based on diagnostic tests, we found FIGARCH model performs better than the other two models, which is again consistence with the most recent prior research on the topic
We attempt to re-examine the market efficiency of Energy Exchange-Traded Funds
Summary
Most existing literature focus on investigating long-term memory in stock markets returns, fixed income markets returns, or commodity markets returns. Mixed results were found on the presence of apparent temporal dependencies in financial market volatility. Several studies conclude that capital markets are characterized by long memory processes [1]-[6]. Many studies do not find any significant and robust evidence of positive long-term persistence in the financial markets [7]-[12]. Other stream of literature finds temporary or little evidence of long-term memory in different stock markets [7]-[21]. Studies that investigate the temporal dependencies in financial market volatility, employ various methodologies such as, classical rescaled-range
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