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Volatility Modelling of Volatility Indices: The Case of Emerging Markets

In: Advances in Quantitative Economic Research

Author

Listed:
  • Nadia Villiers

    (University of Johannesburg)

  • Pierre J. Venter

    (University of Johannesburg)

Abstract

The purpose of this paper was to examine the stylised facts of volatility and volatility modelling of volatility index returns in the context of emerging markets. The stylised facts of volatility include volatility clustering, mean reversion, a negative relationship with stock market returns and positive relationship with trading volume. By using autoregressive models, linear regression and unit root tests, empirical results indicate that the volatility indices reproduce all the stylised facts of volatility for the following emerging economies: Brazil, India, China, Korea and South Africa. In addition, the volatility modelling of volatility index returns is also considered. In the empirical analysis, the symmetric GARCH, asymmetric GJR-GARCH and EGARCH models were estimated using the volatility indices of emerging economies; the best fitting model was determined using the AIC and SIC. The asymmetric terms of the GJR-GARCH and EGARCH models are statistically significant. The information criterion suggests that the EGARCH model is the best fitting model for all the volatility indices, except Korea. For Korea, the GJR-GARCH model is the best fitting model.

Suggested Citation

  • Nadia Villiers & Pierre J. Venter, 2022. "Volatility Modelling of Volatility Indices: The Case of Emerging Markets," Springer Proceedings in Business and Economics, in: Nicholas Tsounis & Aspasia Vlachvei (ed.), Advances in Quantitative Economic Research, chapter 0, pages 31-46, Springer.
    • Handle: RePEc:spr:prbchp:978-3-030-98179-2_3
    DOI: 10.1007/978-3-030-98179-2_3
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