本文探討槓桿型/反向型ETF之追蹤誤差是否會因為追縱標的屬於不同產業而有差異。為此先將46檔具有顯著追蹤誤差之槓桿型/反向型ETF樣本分為七類不同的產業，並設定產業作虛擬變數放入多元迴歸模型中，結果為當追蹤指數屬於建築業、零售業及服務業之槓桿型/反向型ETF傾向得到較大的追蹤誤差，而追蹤指數屬於礦產業、製造業、水電業及金融業者，其追蹤誤差較小。追蹤誤差大之產業，其指數波動度也較大，推測指數波動度可能是造成特定產業追蹤績效不佳的原因。另外在本研究中也發現，追蹤礦產業、建築業及製造業指數之槓桿型/反向型ETF，其槓桿型績效優於反向型績效；而追蹤水電業、零售業、金融業及服務業指數之槓桿型/反向型ETF則是反向型績效優於槓桿型績效。其原因推測與ETF存在年限、ETF發行公司和指數成分股個數有關。

This paper discusses whether the tracking error of leveraged/inverse ETF varies by industry of underlying indexes. We take 46 leveraged/inverse ETFs with significant tracking error into the samples, divide them into 7 different industries and set those industries as dummy variables in multiple regression models. The outcome shows that the tracking error tends to be larger if the underlying index of leveraged/inverse ETF belongs to construction, retails or service industries; otherwise, the tracking error tends to be smaller if it tracks the index from mining, manufacturing, utility or finance industries. The larger tracking errors may result from more volatile indexes of those industries. Besides, we also find that leveraged ETFs outperform the inverse ones if the index belongs to mining, construction or manufacturing industry; on the other hand, inverse ETFs outperform leveraged ones when the index comes from utility, retails, finance or service industry. The possible reasons may be the different characteristics of ETFs, such as the length of ETF’s existence, ETF’s issuer and the number of constituents in underlying index.

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