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Interaction between Oil Price and Investor Sentiment: Nonlinear Causality, Time- Varying Influence, and Asymmetric Effect

Author

Listed:
  • Zhifang He
  • Fangzhao Zhou
  • Xiaohua Xia
  • Fenghua Wen
  • Yiyuan Huang

Abstract

This paper investigates the interaction between crude oil prices and individual investor sentiment with the Hiemstra and Jones (HJ) test, the Diks and Panchenko (DP) test, the time-varying parameter structural vector autoregression (TVP-SVAR) model, and the nonlinear autoregressive distributed lags (NARDL) model. Results reveal a bidirectional nonlinear Granger causality, rather than a linear Granger causality, between crude oil prices and individual investor sentiment. Meanwhile, the interactions between the two variables are time-varying, and oil prices negatively affect individual investor sentiment in general. However, the effect of individual sentiment on oil prices is more complicated. It has more significant impacts on oil prices after 2000, and shows a positive influence before the global financial crisis, a minor influence during the crisis, and even a negative influence after the crisis. In addition, the oil price has significant long-run and short-run asymmetric effects on individual investor sentiment, whereas individual investor sentiment has no asymmetric effect on oil prices.

Suggested Citation

  • Zhifang He & Fangzhao Zhou & Xiaohua Xia & Fenghua Wen & Yiyuan Huang, 2019. "Interaction between Oil Price and Investor Sentiment: Nonlinear Causality, Time- Varying Influence, and Asymmetric Effect," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(12), pages 2756-2773, September.
    • Handle: RePEc:mes:emfitr:v:55:y:2019:i:12:p:2756-2773
    DOI: 10.1080/1540496X.2019.1635450
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    Citations

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    Cited by:

    1. Jain, Prachi & Maitra, Debasish & Kang, Sang Hoon, 2023. "Oil price and the automobile industry: Dynamic connectedness and portfolio implications with downside risk," Energy Economics, Elsevier, vol. 119(C).
    2. Szymon Lis, 2022. "Investor Sentiment in Asset Pricing Models: A Review," Working Papers 2022-14, Faculty of Economic Sciences, University of Warsaw.
    3. He, Zhifang & Sun, Hao, 2024. "The time-varying and asymmetric impacts of oil price shocks on geopolitical risk," International Review of Economics & Finance, Elsevier, vol. 91(C), pages 942-957.
    4. Wen, Fenghua & Cao, Jiahui & Liu, Zhen & Wang, Xiong, 2021. "Dynamic volatility spillovers and investment strategies between the Chinese stock market and commodity markets," International Review of Financial Analysis, Elsevier, vol. 76(C).
    5. Tian, Meiyu & Li, Wanyang & Wen, Fenghua, 2021. "The dynamic impact of oil price shocks on the stock market and the USD/RMB exchange rate: Evidence from implied volatility indices," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    6. Chuangxia Huang & Xian Zhao & Renli Su & Xiaoguang Yang & Xin Yang, 2022. "Dynamic network topology and market performance: A case of the Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1962-1978, April.
    7. Phan, Dinh Hoang Bach & Tran, Vuong Thao & Nguyen, Dat Thanh & Le, Anh, 2020. "The importance of managerial ability on crude oil price uncertainty-firm performance relationship," Energy Economics, Elsevier, vol. 88(C).
    8. Chen, Qitong & Zhu, Huiming & Yu, Dongwei & Hau, Liya, 2022. "How does investor attention matter for crude oil prices and returns? Evidence from time-frequency quantile causality analysis," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    9. Wang, Kangsheng & Wen, Fenghua & Gong, Xu, 2024. "Oil prices and systemic financial risk: A complex network analysis," Energy, Elsevier, vol. 293(C).
    10. Zhao, Lili & Wen, Fenghua & Wang, Xiong, 2020. "Interaction among China carbon emission trading markets: Nonlinear Granger causality and time-varying effect," Energy Economics, Elsevier, vol. 91(C).
    11. Priya, Pragati & Pal, Debdatta, 2024. "Does crude oil price volatility respond asymmetrically to financial shocks?," Resources Policy, Elsevier, vol. 92(C).
    12. Lucey, Brian & Ren, Boru, 2021. "Does news tone help forecast oil?," Economic Modelling, Elsevier, vol. 104(C).
    13. Ouyang, Zi-sheng & Liu, Meng-tian & Huang, Su-su & Yao, Ting, 2022. "Does the source of oil price shocks matter for the systemic risk?," Energy Economics, Elsevier, vol. 109(C).
    14. He, Zhifang, 2023. "Geopolitical risks and investor sentiment: Causality and TVP-VAR analysis," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    15. Narayan, Paresh Kumar & Narayan, Seema, 2021. "Do opinion polls on government preference influence stock returns?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    16. Fasanya, Ismail & Adekoya, Oluwasegun & Oyewole, Oluwatomisin & Adegboyega, Soliu, 2022. "Investor sentiment and energy futures predictability: Evidence from Feasible Quasi Generalized Least Squares," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    17. Zheng, Yan & Zhou, Min & Wen, Fenghua, 2021. "Asymmetric effects of oil shocks on carbon allowance price: Evidence from China," Energy Economics, Elsevier, vol. 97(C).

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