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Volatility equicorrelation: A cross-market perspective

Author

Listed:
  • Julien Chevallier

    (UCP - Université de Cergy Pontoise - Université Paris-Seine)

  • Sofiane Aboura

    (DRM - Dauphine Recherches en Management - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper contains the first empirical application of the Dynamic Equicorrelation (DECO) model to a cross-market dataset composed of equities, bonds, foreign exchange rates and commodities during 1983-2013. The originality of our approach consists in examining the volatility equicorrelations, by updating the concept of ‘volatility surprise'. We document that the average volatility equicorrelation across markets is around 15%, while being time-varying with regime shifts before/after September 2005 and with a low mean-reversion level.

Suggested Citation

  • Julien Chevallier & Sofiane Aboura, 2014. "Volatility equicorrelation: A cross-market perspective," Post-Print hal-01531237, HAL.
    • Handle: RePEc:hal:journl:hal-01531237
    DOI: 10.1016/j.econlet.2013.12.008
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    2. Lv, Fei & Yang, Chen & Fang, Libing, 2020. "Do the crude oil futures of the Shanghai International Energy Exchange improve asset allocation of Chinese petrochemical-related stocks?," International Review of Financial Analysis, Elsevier, vol. 71(C).
    3. R. REYTIER & A. Blanes & Q. Gaucher & S. Thiam & P. Debled, 2015. "Behavior of Covariance Matrices with Equi-Correlation Approach," Proceedings of International Academic Conferences 2805027, International Institute of Social and Economic Sciences.
    4. Yilmaz, Mustafa K. & Sensoy, Ahmet & Ozturk, Kevser & Hacihasanoglu, Erk, 2015. "Cross-sectoral interactions in Islamic equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 32(C), pages 1-20.
    5. Bouri, Elie & Lucey, Brian & Roubaud, David, 2020. "The volatility surprise of leading cryptocurrencies: Transitory and permanent linkages," Finance Research Letters, Elsevier, vol. 33(C).
    6. Mensi, Walid & Hammoudeh, Shawkat & Rehman, Mobeen Ur & Al-Maadid, Alanoud Ali S. & Hoon Kang, Sang, 2020. "Dynamic risk spillovers and portfolio risk management between precious metals and global foreign exchange markets," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    7. Ngo Thai Hung, 2021. "Directional Spillover Effects Between BRICS Stock Markets and Economic Policy Uncertainty," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(3), pages 429-448, September.
    8. Elsayed, Ahmed H. & Hammoudeh, Shawkat & Sousa, Ricardo M., 2021. "Inflation synchronization among the G7and China: The important role of oil inflation," Energy Economics, Elsevier, vol. 100(C).
    9. Ching-Chun Wei, 2016. "Empirical Analysis of ¡°Volatility Surprise¡± between Dollar Exchange Rate and CRB Commodity Future Markets," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(9), pages 117-126, September.
    10. Cui, Jinxin & Goh, Mark & Zou, Huiwen, 2021. "Coherence, extreme risk spillovers, and dynamic linkages between oil and China’s commodity futures markets," Energy, Elsevier, vol. 225(C).
    11. Maitra, Debasish & Chandra, Saurabh & Dash, Saumya Ranjan, 2020. "Liner shipping industry and oil price volatility: Dynamic connectedness and portfolio diversification," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    12. Kang, Sang Hoon & Uddin, Gazi Salah & Troster, Victor & Yoon, Seong-Min, 2019. "Directional spillover effects between ASEAN and world stock markets," Journal of Multinational Financial Management, Elsevier, vol. 52.
    13. Kang, Sang Hoon & McIver, Ron & Yoon, Seong-Min, 2017. "Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets," Energy Economics, Elsevier, vol. 62(C), pages 19-32.

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