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Time-varying international stock market interaction and the identification of volatility signals

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  • Strohsal, Till
  • Weber, Enzo

Abstract

This paper investigates the dependency of international stock market interaction on financial volatility. We show in a stylized economic model that volatility-dependent cross-market spillovers can be interpreted in two different ways, as indicating information flow or uncertainty. If higher volatility in one market leads to higher (lower) reactions in another market, volatility reflects information (uncertainty). We apply a simultaneous time-varying coefficient model, where structural ARCH-type variances serve two purposes: governing the time variation of spillovers and ensuring statistical identification. We analyze data of US and further stock markets. Indeed, we find strong nonlinear, volatility-dependent spillovers.

Suggested Citation

  • Strohsal, Till & Weber, Enzo, 2015. "Time-varying international stock market interaction and the identification of volatility signals," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 28-36.
    • Handle: RePEc:eee:jbfina:v:56:y:2015:i:c:p:28-36
    DOI: 10.1016/j.jbankfin.2015.01.020
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    2. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2017. "Asymmetry in spillover effects: Evidence for international stock index futures markets," International Review of Financial Analysis, Elsevier, vol. 53(C), pages 94-111.
    3. Tangyong Liu & Xu Gong & Boqiang Lin, 2021. "Analyzing the frequency dynamics of volatility spillovers across precious and industrial metal markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(9), pages 1375-1396, September.
    4. Boeckelmann Lukas & Stalla-Bourdillon Arthur, 2021. "Structural Estimation of Time-Varying Spillovers: An Application to International Credit Risk Transmission," Working papers 798, Banque de France.
    5. Gong, Xu & Liu, Yun & Wang, Xiong, 2021. "Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method," International Review of Financial Analysis, Elsevier, vol. 76(C).
    6. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stober, 2016. "Regime switching vine copula models for global equity and volatility indices," Papers 1604.05598, arXiv.org.
    7. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stöber, 2017. "Regime Switching Vine Copula Models for Global Equity and Volatility Indices," Econometrics, MDPI, vol. 5(1), pages 1-38, January.

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    More about this item

    Keywords

    Information; Uncertainty; Spillover; Simultaneous equations; Identification;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • 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

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