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Asymmetric covariance in spot‐futures markets

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  • Vicente Meneu
  • Hipòlit Torró

Abstract

This article studies how the spot‐futures conditional covariance matrix responds to positive and negative innovations. The main results of the article are achieved by obtaining the Volatility Impulse Response Function (VIRF) for asymmetric multivariate GARCH structures, extending Lin (1997) findings for symmetric GARCH models. This theoretical result is general and can be applied to analyze covariance dynamics in any financial system. After testing how multivariate GARCH models clean up volatility asymmetries, the Asymmetric VIRF is computed for the Spanish stock index IBEX‐35 and its futures contract. The empirical results indicate that the spot‐futures variance system is more sensitive to negative than positive shocks, and that spot volatility shocks have much more impact on futures volatility than vice versa. Additionally, evidence is obtained showing that optimal hedge ratios are insensitive to the well‐known asymmetric volatility behavior in stock markets. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:1019–1046, 2003

Suggested Citation

  • Vicente Meneu & Hipòlit Torró, 2003. "Asymmetric covariance in spot‐futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(11), pages 1019-1046, November.
    • Handle: RePEc:wly:jfutmk:v:23:y:2003:i:11:p:1019-1046
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    Cited by:

    1. Qu, Hui & Wang, Tianyang & Zhang, Yi & Sun, Pengfei, 2019. "Dynamic hedging using the realized minimum-variance hedge ratio approach – Examination of the CSI 300 index futures," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    2. Dark, Jonathan, 2015. "Futures hedging with Markov switching vector error correction FIEGARCH and FIAPARCH," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 269-285.
    3. Tao, Juan & Green, Christopher J., 2012. "Asymmetries, causality and correlation between FTSE100 spot and futures: A DCC-TGARCH-M analysis," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 26-37.
    4. Helena Chulia & Francisco Climent & Pilar Soriano & Hipolit Torro, 2009. "Volatility transmission patterns and terrorist attacks," Quantitative Finance, Taylor & Francis Journals, vol. 9(5), pages 607-619.
    5. Nikos Nomikos & Enrique Salvador, 2014. "The role of volatility regimes on volatility transmission patterns," Quantitative Finance, Taylor & Francis Journals, vol. 14(1), pages 1-13, January.
    6. Angelos Kanas, 2009. "Regime switching in stock index and futures markets: a note on the NIKKEI evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 14(4), pages 394-399.
    7. Alemany, Aida & Ballester, Laura & González-Urteaga, Ana, 2015. "Volatility spillovers in the European bank CDS market," Finance Research Letters, Elsevier, vol. 13(C), pages 137-147.
    8. Aragó, Vicent & Salvador, Enrique, 2011. "Sudden changes in variance and time varying hedge ratios," European Journal of Operational Research, Elsevier, vol. 215(2), pages 393-403, December.
    9. Angelos Kanas, 2008. "Modeling regime transition in stock index futures markets and forecasting implications," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 649-669.
    10. Jose Luis Miralles Marcelo & Jose Luis Miralles Quiros & Maria del Mar Miralles Quiros, 2007. "Sudden shifts in variance in the Spanish market: persistence and spillover effects," Applied Financial Economics, Taylor & Francis Journals, vol. 18(2), pages 115-124.

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