Volatility Transmission from Equity, Bulk Shipping, and Commodity Markets to Oil ETF and Energy Fund—A GARCH-MIDAS Model

Arthur J. Lin and Hai-Yen Chang
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Arthur J. Lin: Graduate Institute of International Business, National Taipei University, New Taipei City 237, Taiwan
Hai-Yen Chang: Department of Banking and Finance, Chinese Culture University, Taipei City 111, Taiwan

Mathematics, 2020, vol. 8, issue 9, 1-21

Abstract: Oil continues to be a major source of world energy, but oil prices and funds have experienced high volatility over the last decade. This study applies the generalized autoregressive conditional heteroskedasticity-mixed-data sampling (GARCH-MIDAS) model on data spanning 1 July 2014 to 30 April 2020 to examine volatility transmission from the equity, bulk shipping, commodity, currency, and crude oil markets to the United States Oil Fund (USO) and BlackRock World Energy Fund A2 (BGF). By dividing the sample into two subsamples, we find a significant volatility transmission from the equity market to the oil ETF and energy fund both before and after the 2018 U.S.–China trade war. The volatility transmission from the bulk shipping, commodity, and crude oil markets turns significant for the oil ETF and energy fund after the 2018 U.S.–China trade war, extending into the COVID-19 pandemic in early 2020. The results suggest that investors can use the equity market to predict the movement of oil and energy funds during both tranquil and turmoil periods. Moreover, investors can use bulk shipping, commodity, and crude oil markets in addition to the equity market to forecast oil and energy funds’ volatility during the turmoil periods. This paper benefits investors against the high volatility of the energy funds.

Keywords: oil industry; oil ETF; energy mutual fund; volatility transmission; contagion; GARCH-MIDAS model; U.S.–China trade war; commodities (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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