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A cross-volatility index for hedging the country risk

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)

Abstract

This paper proposes a new empirical methodology for computing a cross-volatility index, coined CVIX, that characterizes the country risk understood here as the financial market risk measurement. The approach, based on the Factor DCC-model, requires to encapsulate all the sources of risk stemming from the financial markets for any given country. We provide an application to the U.S. economy by constructing an aggregate volatility index composed of implied volatility indexes characterizing the equity market, the FX market, fixed income market and the commodity market. The analysis reveals that 75% of the aggregate risk comes from the commodity market, and that the volatility index average value evolves around 22%. The CVIX provides a better hedging performance than the VVIX used as a benchmark.

Suggested Citation

  • Sofiane Aboura & Julien Chevallier, 2015. "A cross-volatility index for hedging the country risk," Post-Print hal-01529742, HAL.
    • Handle: RePEc:hal:journl:hal-01529742
    DOI: 10.1016/j.intfin.2015.05.008
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    Cited by:

    1. 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.
    2. Cañón Salazar Carlos Iván & Gallón Santiago & Olivar Santiago, 2016. "Functional Systemic Risk, Complementarities and Early Warnings," Working Papers 2016-12, Banco de México.
    3. Guido Bonatti & Andrea Ciacci & Enrico Ivaldi, 2021. "Different Measures of Country Risk: An Application to European Countries," JRFM, MDPI, vol. 14(1), pages 1-16, January.
    4. Kilic, Erdem, 2017. "Contagion effects of U.S. Dollar and Chinese Yuan in forward and spot foreign exchange markets," Economic Modelling, Elsevier, vol. 62(C), pages 51-67.

    More about this item

    Keywords

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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
    • G01 - Financial Economics - - General - - - Financial Crises
    • F15 - International Economics - - Trade - - - Economic Integration

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