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Cross-Market Spillovers with 'Volatility Surprise'

Author

Listed:
  • Sofiane Aboura

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

  • Julien Chevallier

    (UP8 - Université Paris 8 Vincennes-Saint-Denis)

Abstract

This article adopts the asymmetric DCC with one exogenous variable (ADCCX) model developed by Vargas (2008), by updating the concept of ‘volatility surprise' to capture cross-market relationships. Current methods for measuring spillovers do not focus on volatility interactions, and neglect cross-effects between the conditional variances. This paper aims to fill this gap. The dataset includes four aggregate indices representing equities, bonds, foreign exchange rates and commodities from 1983 to 2013. The results provide strong evidence of spillover effects coming from the ‘volatility surprise' component across markets. Against the background of the recent financial crisis, the aim is to contribute to the literature on the interdependencies of financial markets, both in conditional means and (co)variances. In addition, asset management implications are derived.

Suggested Citation

  • Sofiane Aboura & Julien Chevallier, 2014. "Cross-Market Spillovers with 'Volatility Surprise'," Post-Print hal-01529770, HAL.
    • Handle: RePEc:hal:journl:hal-01529770
    DOI: 10.1016/j.rfe.2014.08.002
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    2. Jozef Baruník & Evžen KoÄ enda, 2019. "Total, Asymmetric and Frequency Connectedness between Oil and Forex Markets," The Energy Journal, , vol. 40(2_suppl), pages 157-174, December.
    3. Zhang, Weiping & Zhuang, Xintian, 2019. "The stability of Chinese stock network and its mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 748-761.
    4. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2017. "Asymmetric volatility connectedness on the forex market," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 39-56.
    5. Shah, Adil Ahmad & Dar, Arif Billah, 2022. "Asymmetric, time and frequency-based spillover transmission in financial and commodity markets," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    6. Ngene, Geoffrey M., 2021. "What drives dynamic connectedness of the U.S equity sectors during different business cycles?," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    7. Kanamura, Takashi, 2016. "Role of carbon swap trading and energy prices in price correlations and volatilities between carbon markets," Energy Economics, Elsevier, vol. 54(C), pages 204-212.
    8. Gagan Sharma & Parthajit Kayal & Piyush Pandey, 2019. "Information Linkages Among BRICS Countries: Empirical Evidence from Implied Volatility Indices," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(3), pages 263-289, December.
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    10. Zhang, Yue-Jun & Peng, Yu-Lu & Ma, Chao-Qun & Shen, Bo, 2017. "Can environmental innovation facilitate carbon emissions reduction? Evidence from China," Energy Policy, Elsevier, vol. 100(C), pages 18-28.
    11. Baklaci, Hasan Fehmi & Aydoğan, Berna & Yelkenci, Tezer, 2020. "Impact of stock market trading on currency market volatility spillovers," Research in International Business and Finance, Elsevier, vol. 52(C).

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    More about this item

    Keywords

    Cross-market relationships; Volatility surprise; Volatility spillover; ADCCX; Asset management; Crisis; Exchange Rate; Financial Market; Foreign Exchange;
    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
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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