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The effect of global and regional stock market shocks on safe haven assets

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  • Balcilar, Mehmet
  • Demirer, Riza
  • Gupta, Rangan
  • Wohar, Mark E.

Abstract

This paper examines the fundamental linkages between stock markets and safe haven assets by developing a two-factor, regime-based volatility spillover model with global and regional stock market shocks as risk factors. The risk exposures of safe havens with respect to global and regional stock market shocks are found to display significant time variation and regime-specific features, with the exception of VIX for which consistent negative risk exposures are observed with respect to both global and regional stock market shocks. While traditional safe havens like precious metals exhibit positive risk exposures to both regional and global stock market shocks during high volatility periods, Swiss Franc, Japanese Yen and U.S. Treasuries are found to display either insignificant or negative risk exposures during market stress periods to equity market shocks, implying these assets would serve as more effective hedges (or safe havens) for equity investors. Our findings highlight the importance of dynamic models in assessing the linkages between safe haven assets and stock returns as static models would introduce large biases in diversification measures and optimal hedge ratios.

Suggested Citation

  • Balcilar, Mehmet & Demirer, Riza & Gupta, Rangan & Wohar, Mark E., 2020. "The effect of global and regional stock market shocks on safe haven assets," Structural Change and Economic Dynamics, Elsevier, vol. 54(C), pages 297-308.
  • Handle: RePEc:eee:streco:v:54:y:2020:i:c:p:297-308
    DOI: 10.1016/j.strueco.2020.04.004
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    Cited by:

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    2. Zhenghui Li & Zhiming Ao & Bin Mo, 2021. "Revisiting the Valuable Roles of Global Financial Assets for International Stock Markets: Quantile Coherence and Causality-in-Quantiles Approaches," Mathematics, MDPI, vol. 9(15), pages 1-18, July.
    3. David Gabauer & Rangan Gupta & Sayar Karmakar & Joshua Nielsen, 2022. "Stock Market Bubbles and the Forecastability of Gold Returns (and Volatility)," Working Papers 202228, University of Pretoria, Department of Economics.
    4. Beirne, John & Sugandi, Eric, 2023. "Risk-off shocks and spillovers in safe havens," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    5. Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Time and frequency connectedness and network across the precious metal and stock markets: Evidence from top precious metal importers and exporters," Resources Policy, Elsevier, vol. 72(C).
    6. Yousaf, Imran & Suleman, Muhammad Tahir & Demirer, Riza, 2022. "Green investments: A luxury good or a financial necessity?," Energy Economics, Elsevier, vol. 105(C).
    7. Rangan Gupta & Christian Pierdzioch, 2023. "Do U.S. economic conditions at the state level predict the realized volatility of oil-price returns? A quantile machine-learning approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-22, December.
    8. Bonato, Matteo & Gupta, Rangan & Lau, Chi Keung Marco & Wang, Shixuan, 2020. "Moments-based spillovers across gold and oil markets," Energy Economics, Elsevier, vol. 89(C).
    9. Marco Tronzano, 2023. "Safe-Haven Currencies as Defensive Assets in Global Stocks Portfolios: A Reassessment of the Empirical Evidence (1999–2022)," JRFM, MDPI, vol. 16(5), pages 1-23, May.
    10. Imran Yousaf & Vasilios Plakandaras & Elie Bouri & Rangan Gupta, 2022. "Hedge and Safe Haven Properties of Gold, US Treasury, Bitcoin, and Dollar/CHF against the FAANA Companies and S&P 500," Working Papers 202227, University of Pretoria, Department of Economics.
    11. Hadhri, Sinda, 2023. "News-based economic policy uncertainty and financial contagion: An international evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 63-76.
    12. Çepni, Oğuzhan & Gupta, Rangan & Pienaar, Daniel & Pierdzioch, Christian, 2022. "Forecasting the realized variance of oil-price returns using machine learning: Is there a role for U.S. state-level uncertainty?," Energy Economics, Elsevier, vol. 114(C).

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    More about this item

    Keywords

    Safe haven assets; Multivariate regime-switching; Equity market shocks;
    All these keywords.

    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
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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