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Directional predictability and time-varying spillovers between stock markets and economic cycles

Author

Listed:
  • Stelios Bekiros

    (Economics Department [European University Institute] - EUI - European University Institute - Institut Universitaire Européen)

  • Syed Jawad Hussain Shahzad

    (Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School)

  • Jose Arreola-Hernandez

    (Rennes SB - Rennes School of Business)

  • Mobeen Ur Rehman

    (Shaheed Zulfiqar Ali Bhutto Institute of Science & Technology, Karachi)

Abstract

We examine the nonlinear dependence structure and causal nexus between business cycles, stock market returns and asset return volatility for the US economy. We implement two novel methodologies, namely quantile-on-quantile analysis and cross-quantilogram to account for tail dependence and spillovers across quantile ranges. We find evidence of statistically significant spillover effects from extreme equity market returns and their corresponding volatility to specific stages of business cycles. The sensitivity of returns and volatility to business cycle shocks is only evident for extreme quantiles. These findings indicate the importance of modeling the nonlinearity and tail behaviour when analyzing the relationships between equity markets and business cycles. Financial and monetary policy regulators may use the dynamics of spillover predictability and influence between the equity market returns, their volatility and business cycles to exert some degree of control upon business cycle formation and development.

Suggested Citation

  • Stelios Bekiros & Syed Jawad Hussain Shahzad & Jose Arreola-Hernandez & Mobeen Ur Rehman, 2018. "Directional predictability and time-varying spillovers between stock markets and economic cycles," Post-Print hal-01996787, HAL.
  • Handle: RePEc:hal:journl:hal-01996787
    DOI: 10.1016/j.econmod.2017.10.003
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    Cited by:

    1. Mo, Bin & Chen, Cuiqiong & Nie, He & Jiang, Yonghong, 2019. "Visiting effects of crude oil price on economic growth in BRICS countries: Fresh evidence from wavelet-based quantile-on-quantile tests," Energy, Elsevier, vol. 178(C), pages 234-251.
    2. Asgari, Heshmatolah & Moridian, Ali, 2023. "Investigating the Role of Human Capital and Shadow Economy in the Impact of Natural Resource Rent on Income Inequality with Regime Change (in Persian)," The Journal of Planning and Budgeting (٠صلنامه برنامه ریزی و بودجه), Institute for Management and Planning studies, vol. 28(4), pages 75-110, December.
    3. Syed Jawad Hussain Shahzad & Dene Hurley & Román Ferrer, 2021. "U.S. stock prices and macroeconomic fundamentals: Fresh evidence using the quantile ARDL approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3569-3587, July.
    4. Marlon Fritz & Thomas Gries & Lukas Wiechers, 2024. "An early indicator for anomalous stock market performance," Quantitative Finance, Taylor & Francis Journals, vol. 24(1), pages 105-118, January.
    5. Troster, Victor & Bouri, Elie & Roubaud, David, 2019. "A quantile regression analysis of flights-to-safety with implied volatilities," Resources Policy, Elsevier, vol. 62(C), pages 482-495.
    6. Corbet, Shaen & Goodell, John W. & Günay, Samet, 2020. "Co-movements and spillovers of oil and renewable firms under extreme conditions: New evidence from negative WTI prices during COVID-19," Energy Economics, Elsevier, vol. 92(C).
    7. Kumar, Satish & Khalfaoui, Rabeh & Tiwari, Aviral Kumar, 2021. "Does geopolitical risk improve the directional predictability from oil to stock returns? Evidence from oil-exporting and oil-importing countries," Resources Policy, Elsevier, vol. 74(C).
    8. Mobeen Ur Rehman & Sajid Ali & Syed Jawad Hussain Shahzad, 2020. "Asymmetric Nonlinear Impact of Oil Prices and Inflation on Residential Property Prices: a Case of US, UK and Canada," The Journal of Real Estate Finance and Economics, Springer, vol. 61(1), pages 39-54, June.
    9. Si, Deng-Kui & Liu, Xi-Hua & Kong, Xianli, 2019. "The comovement and causality between stock market cycle and business cycle in China: Evidence from a wavelet analysis," Economic Modelling, Elsevier, vol. 83(C), pages 17-30.
    10. Narayan, Paresh Kumar & Liu, Ruipeng, 2018. "A new GARCH model with higher moments for stock return predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 56(C), pages 93-103.
    11. Jiang, Shangwei & Jin, Xiu, 2021. "Effects of investor sentiment on stock return volatility: A spatio-temporal dynamic panel model," Economic Modelling, Elsevier, vol. 97(C), pages 298-306.

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    Keywords

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    JEL classification:

    • B26 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Financial Economics
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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