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Dynamic Correlations and Volatility Spillovers between Crude Oil and Stock Index Returns: The Implications for Optimal Portfolio Construction

Author

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  • Yen-Hsien Lee

    (Department of Finance, Chung Yuan Christian University, Taiwan.)

  • Ya-Ling Huang

    (Golden-Ager Industry Management, Chaoyang University of Technology, Taiwan)

  • Chun-Yu Wu

    (Department of Finance, Chung Yuan Christian University, Taiwan.)

Abstract

This paper researches the portfolio construction between stock price of group of seven (G7) and West Texas Intermediate crude oil from January 2, 1998 to March 1, 2012. We investigate the volatility spillover between stock price and oil price with the dynamic conditional correlation (DCC), constant conditional correlation (CCC) and BEKK models, and also analyze their optimal hedge ratio and portfolio weights. The empirical result is that the hedge effectiveness of DCC model is better than the CCC model and BEKK models. The hedge effectiveness (HE) in Canada is the highest but Japan is the lowest. Moreover, the results show that Japan has the biggest optimal portfolio weight and the lowest hedge ratio. We do this research with expectation of providing investors information to increase the basis of investing

Suggested Citation

  • Yen-Hsien Lee & Ya-Ling Huang & Chun-Yu Wu, 2014. "Dynamic Correlations and Volatility Spillovers between Crude Oil and Stock Index Returns: The Implications for Optimal Portfolio Construction," International Journal of Energy Economics and Policy, Econjournals, vol. 4(3), pages 327-336.
    • Handle: RePEc:eco:journ2:2014-03-2
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    Cited by:

    1. Liu, Xueyong & An, Haizhong & Huang, Shupei & Wen, Shaobo, 2017. "The evolution of spillover effects between oil and stock markets across multi-scales using a wavelet-based GARCH–BEKK model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 374-383.
    2. Cem Berk, 2016. "Indexing Oil from a Financial Point of View: A Comparison between Brent and West Texas Intermediate," International Journal of Energy Economics and Policy, Econjournals, vol. 6(2), pages 152-158.
    3. Tiwari, Aviral Kumar & Trabelsi, Nader & Alqahtani, Faisal & Raheem, Ibrahim D., 2020. "Systemic risk spillovers between crude oil and stock index returns of G7 economies: Conditional value-at-risk and marginal expected shortfall approaches," Energy Economics, Elsevier, vol. 86(C).
    4. Burak Korkusuz & David G. McMillan & Dimos Kambouroudis, 2023. "Complex network analysis of volatility spillovers between global financial indicators and G20 stock markets," Empirical Economics, Springer, vol. 64(4), pages 1517-1537, April.
    5. Pu, Yingjian & Yang, Baochen, 2022. "The commodity futures' historical basis in trading strategy and portfolio investment," Energy Economics, Elsevier, vol. 105(C).
    6. Sarwar, Suleman & Shahbaz, Muhammad & Anwar, Awais & Tiwari, Aviral Kumar, 2019. "The importance of oil assets for portfolio optimization: The analysis of firm level stocks," Energy Economics, Elsevier, vol. 78(C), pages 217-234.
    7. Lei, Lei & Aziz, Ghazala & Sarwar, Suleman & Waheed, Rida & Tiwari, Aviral Kumar, 2023. "Spillover and portfolio analysis for oil and stock market: A new insight across financial crisis, COVID-19 and Russian-Ukraine war," Resources Policy, Elsevier, vol. 85(PA).
    8. Tanattrin Bunnag, 2015. "Hedging Petroleum Futures with Multivariate GARCH Models," International Journal of Energy Economics and Policy, Econjournals, vol. 5(1), pages 105-120.
    9. Mohamed Osman, 2015. "Dynamic Asymmetries in the Electric Consumption of the GCC Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 5(2), pages 461-467.
    10. Liu, Xueyong & An, Haizhong & Li, Huajiao & Chen, Zhihua & Feng, Sida & Wen, Shaobo, 2017. "Features of spillover networks in international financial markets: Evidence from the G20 countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 265-278.
    11. Aziz, Ghazala & Sarwar, Suleman & Yuan, Qiong & Waheed, Rida & Morales, Lucía, 2024. "Reinvestigating the role of oil and gold for portfolio optimization in view of COVID-19 and structural breaks: Empirical evidence of BEKK, DCC and wavelet quantile based estimations," Resources Policy, Elsevier, vol. 92(C).
    12. Selma Izadi & M. Kabir Hassan, 2018. "Portfolio and hedging effectiveness of financial assets of the G7 countries," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 8(2), pages 183-213, August.

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    More about this item

    Keywords

    Crudeoil; DCC model; Hedge effectiveness; Optimal portfolio;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G1 - Financial Economics - - General Financial Markets
    • N7 - Economic History - - Economic History: Transport, International and Domestic Trade, Energy, and Other Services

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