近年來，反向型ETF與波動型ETF成為相當熱門的避險與投機商品，然而以往的文獻卻很少將這兩種商品的避險績效互相比較。因此，本研究嘗試建構這兩種不同的避險組合，並利用動態Copula-GJR-GARCH模型，估計每個樣本點上的報酬變異與關聯結構參數，藉此求得更加精準的最適避險比率。本研究也以避險效率與避險效用來評估避險績效，旨在提供避險者可以從更客觀的角度分析前沿避險模型與傳統OLS模型的差異。最後經本研究實證結果顯示，所有動態Copula模型在避險效用上均勝於傳統OLS模型，而且波動型ETF不僅避險效用優於反向型ETF，也具有避險成本較低的優勢。

In recent years, inverse ETFs and volatility ETFs have become very popular instruments for the purpose of hedging and speculation. However, seldom did previous studies compare the hedging performance of those two instruments. Therefore, we attempt to construct two hedging portfolios with those two instruments, and employ the dynamic Copula-GJR-GARCH model to estimate the variation of returns and parameters of copula at each sample point, thereby obtaining the optimal hedging ratio more precisely. In order to analyze the difference between the frontier hedging model and the conventional OLS model from a relatively objective perspective, we evaluate the hedging performance of each portfolio by both the corresponding hedge effectiveness and the corresponding hedging utility. The empirical results show that all models embedded with a dynamic Copula function perform better than the conventional OLS model in terms of hedging utility, and the volatility ETF not only has greater hedging utility than the inverse ETF, but also has an advantage of lower hedging
cost.

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