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Modeling and Testing Volatility Spillovers in Oil and Financial Markets for the USA, the UK, and China

Author

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  • Chia-Lin Chang

    (Department of Applied Economics, Department of Finance, National Chung Hsing University, Taichung 402, Taiwan
    Department of Finance, Asia University, Taichung 41354, Taiwan)

  • Michael McAleer

    (Department of Finance, Asia University, Taichung 41354, Taiwan
    Discipline of Business Analytics, University of Sydney Business School, Sydney 2006, Australia
    Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, 3000 Rotterdam, The Netherlands
    Department of Economic Analysis and ICAE, Complutense University of Madrid, 28040 Madrid, Spain)

  • Jiarong Tian

    (Department of Quantitative Finance, National Tsing Hua University, Hsinchu 30013, Taiwan)

Abstract

The main purpose of the paper is to analyze the conditional correlations, conditional covariances, and co-volatility spillovers between international crude oil and associated financial markets. The prices of oil and its interactions with financial markets make it possible to determine the associated prices of financial derivatives, such as carbon emission prices. The approach taken in the paper is different from others in the literature; the purpose is to examine the usefulness of modeling and testing volatility spillovers in the oil and financial markets. The paper investigates co-volatility spillovers (namely, the delayed effect of a returns shock in one physical or financial asset on the subsequent volatility or co-volatility in another physical or financial asset) between the oil and financial markets. The oil industry has four major regions, namely North Sea, the USA, Middle East, and South-East Asia. Associated with these regions are two major financial centers, namely the UK and the USA. For these reasons, the data to be used are the returns on alternative crude oil markets, returns on crude oil derivatives, specifically futures, and stock index returns in the UK and the USA. Given the importance of the Chinese financial and economic systems, the paper also analyzes Chinese financial markets, where the data are more recent. The USA and China are the world’s two largest economies and the UK is the world’s sixth largest economy (and second in the existing EU) behind the USA, China, Japan, Germany, and India. Moreover, the USA and the UK are associated with WTI and Brent oil, respectively. One of the purposes of the paper is to examine how China might be different from the USA and the UK, which seems to be borne out in the empirical analysis. Based on the conditional covariances to test the co-volatility spillovers, dynamic hedging strategies will be suggested to analyze market fluctuations in crude oil prices and associated financial markets.

Suggested Citation

  • Chia-Lin Chang & Michael McAleer & Jiarong Tian, 2019. "Modeling and Testing Volatility Spillovers in Oil and Financial Markets for the USA, the UK, and China," Energies, MDPI, vol. 12(8), pages 1-24, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:8:p:1475-:d:224091
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    References listed on IDEAS

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    3. Syed Kumail Abbas Rizvi & Bushra Naqvi & Nawazish Mirza, 2022. "Is green investment different from grey? Return and volatility spillovers between green and grey energy ETFs," Annals of Operations Research, Springer, vol. 313(1), pages 495-524, June.
    4. Zhang, Chuanguo & Mou, Xinjie & Ye, Shuping, 2022. "How do dynamic jumps in global crude oil prices impact China's industrial sector?," Energy, Elsevier, vol. 249(C).
    5. Jiliang Sheng & Juchao Li & Jun Yang, 2022. "Tail Dependency and Risk Spillover between Oil Market and Chinese Sectoral Stock Markets—An Assessment of the 2013 Refined Oil Pricing Reform," Energies, MDPI, vol. 15(16), pages 1-19, August.
    6. Chang, Chia-Lin & McAleer, Michael & Wang, Yu-Ann, 2020. "Herding behaviour in energy stock markets during the Global Financial Crisis, SARS, and ongoing COVID-19," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).

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    More about this item

    Keywords

    co-volatility spillovers; crude oil; financial markets; spot; futures; diagonal BEKK; optimal dynamic hedging;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products

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