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Volatility Spillover between Oil and Stock Market Returns

Author

Listed:
  • B. Anand

    (Department of Economics, Central University of Rajasthan)

  • Sunil Paul

    (Madras School of Economics, Chennai)

  • M. Ramachandran

    (Department of Economics, Pondicherry University)

Abstract

In the recent past, international crude oil markets have witnessed significant fluctuations and such fluctuations tend to have ramifications on the economy as a whole. In this regard, this paper makes an attempt to model such volatility spillover from oil price returns to the returns of the Indian stock market. The study also makes a comparative analysis of the volatility transmission mechanism between the periods prior to and after the eruption of the global financial crisis. The empirical analysis employs BEKK parameterization of bivariate GARCH model and various tools of continuous wavelet transform to understand the dynamics of volatility spillover between these two markets. The empirical evidence suggests that the fluctuations in the crude oil price returns exert significant impact on the volatility of stock market returns. More importantly, such volatility spillovers are found to be much stronger during the post financial crisis period and the results obtained from the wavelet analysis indicate the dominance of high frequency components in the oil-stock market relationship.

Suggested Citation

  • B. Anand & Sunil Paul & M. Ramachandran, 2014. "Volatility Spillover between Oil and Stock Market Returns," Indian Economic Review, Department of Economics, Delhi School of Economics, vol. 49(1), pages 37-56.
  • Handle: RePEc:dse:indecr:0083
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    Cited by:

    1. Zhang, Yingying & Xu, Shaojun, 2023. "Spillover connectedness between oil and China's industry stock markets: A perspective of carbon emissions," Finance Research Letters, Elsevier, vol. 54(C).
    2. Guan, Bo & Mazouz, Khelifa & Xu, Yongdeng, 2024. "Asymmetric volatility spillover between crude oil and other asset markets," Energy Economics, Elsevier, vol. 130(C).
    3. Ozdemir, Huseyin & Ozdemir, Zeynel Abidin, 2021. "A Survey of Hedge and Safe Havens Assets against G-7 Stock Markets before and during the COVID-19 Pandemic," IZA Discussion Papers 14888, Institute of Labor Economics (IZA).
    4. Escribano, Ana & Koczar, Monika W. & Jareño, Francisco & Esparcia, Carlos, 2023. "Shock transmission between crude oil prices and stock markets," Resources Policy, Elsevier, vol. 83(C).
    5. Wang, Hu & Li, Shouwei, 2021. "Asymmetric volatility spillovers between crude oil and China's financial markets," Energy, Elsevier, vol. 233(C).
    6. B., Anand & Paul, Sunil, 2021. "Oil shocks and stock market: Revisiting the dynamics," Energy Economics, Elsevier, vol. 96(C).
    7. Jinghua Wang & Geoffrey Ngene, 2018. "Symmetric and asymmetric nonlinear causalities between oil prices and the U.S. economic sectors," Review of Quantitative Finance and Accounting, Springer, vol. 51(1), pages 199-218, July.
    8. Theplib, Krit & Sethapramote, Yuthana & Jiranyakul, Komain, 2020. "Shock and Volatility Spillovers between Crude Oil Price and Stock Returns: Evidence for Thailand," MPRA Paper 98094, University Library of Munich, Germany.
    9. Sahoo, Satyaban, 2024. "Harmony in diversity: Exploring connectedness and portfolio strategies among crude oil, gold, traditional and sustainable index," Resources Policy, Elsevier, vol. 97(C).
    10. Mahmoud Ayoub & Mahmoud Qadan, 2024. "Financial ambiguity and oil prices," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-23, December.
    11. Loc Dong Truong & H. Swint Friday & Nhien Tuyet Doan, 2024. "The Asymmetric Effects of Oil Price Volatility on Stock Returns: Evidence from Ho Chi Minh Stock Exchange," JRFM, MDPI, vol. 17(7), pages 1-14, June.
    12. Burhan F. Yavas & Lidija Dedi & Tihana Škrinjarić, 2022. "Did equity returns and volatilities change after the 2016 Trump election victory?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1291-1308, January.

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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