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Modelling asymmetric market volatility with univariate GARCH models: Evidence from Nasdaq-100

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  • Aliyev, Fuzuli
  • Ajayi, Richard
  • Gasim, Nijat

Abstract

This paper models and estimates the volatility of nonfinancial, innovative and hi-tech focused stock index, the Nasdaq-100, using univariate asymmetric GARCH models. We employ EGARCH and GJR-GARCH using daily data over the period January 4, 2000 through March 19, 2019. We find that the volatility shocks on the index returns are quite persistent. Furthermore, our findings show that the index has leverage effect, and the impact of shocks is asymmetric, whereby the impacts of negative shocks on volatility are higher than those of positive shocks of the same magnitude. The financial implication of the findings for investors is that Nasdaq-100 index returns’ volatility exhibits clustering, and this permits investors to establish future positions in expectation of this characteristic.

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  • Aliyev, Fuzuli & Ajayi, Richard & Gasim, Nijat, 2020. "Modelling asymmetric market volatility with univariate GARCH models: Evidence from Nasdaq-100," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    • Handle: RePEc:eee:joecas:v:22:y:2020:i:c:s1703494920300141
    DOI: 10.1016/j.jeca.2020.e00167
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    7. B M, Lithin & chakraborty, Suman & iyer, Vishwanathan & M N, Nikhil & ledwani, Sanket, 2022. "Modeling asymmetric sovereign bond yield volatility with univariate GARCH models: Evidence from India," MPRA Paper 117067, University Library of Munich, Germany, revised 05 Jan 2023.
    8. Azimova, Tarana, 2022. "Modelling volatility transmission in regional Asian stock markets," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
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