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Determinants of equity return correlations: a case study of the Amman Stock Exchange

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Listed:
  • Mohammad Alomari

    (German Jordanian University)

  • David. M. Power

    (University of Dundee)

  • Nongnuch Tantisantiwong

    (University of Southampton)

Abstract

This paper seeks to explain time-varying correlations among equity returns. The literature has shown that fundamental and economic factors can explain stock returns or the volatility of markets. Here, panel data analysis is employed to examine whether these factors can also explain the comovement of stock returns. Time-varying correlations among sectoral indexes are estimated using a restricted multivariate threshold GARCH model with dynamic conditional correlation controlling for the asymmetric effects of news and the influence of financial crises. The empirical results from this panel data analysis show that equity return correlations can be explained not only by macroeconomic variables but also by fundamentals within an industry.

Suggested Citation

  • Mohammad Alomari & David. M. Power & Nongnuch Tantisantiwong, 2018. "Determinants of equity return correlations: a case study of the Amman Stock Exchange," Review of Quantitative Finance and Accounting, Springer, vol. 50(1), pages 33-66, January.
    • Handle: RePEc:kap:rqfnac:v:50:y:2018:i:1:d:10.1007_s11156-017-0622-4
    DOI: 10.1007/s11156-017-0622-4
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    More about this item

    Keywords

    Equity returns correlations; Risk factors; Multivariate threshold GARCH; Dynamic conditional correlation; Panel data analysis;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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