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The Information Contents of VIX Index and Range-based Volatility on Volatility Forecasting Performance of S&P 500

Author

Listed:
  • Jui-Cheng Hung

    (Lunghwa University of Science and Technology)

  • Ren-Xi Ni

    (Takming University of Science and Technology)

  • Matthew C. Chang

    (Hsuan Chuang University)

Abstract

In this paper, we investigate the information contents of S&P 500 VIX index and range-based volatilities by comparing their benefits on the GJR-based volatility forecasting performance. To reveal the statistical significance and ensure obtaining robust results, we employ Hansen's SPA test (2005) to examine the forecasting performances of GJR and GJR-X models for the S&P500 stock index. The results indicate that combining VIX and range-based volatilities into GARCH-type model can both enhance the one-step-ahead volatility forecasts while evaluating with different kinds of loss functions. Moreover, regardless of under-prediction, GJR-VIX model appears to be the most preferred, which implies that VIX index has better information content for improving volatility forecasting performance.

Suggested Citation

  • Jui-Cheng Hung & Ren-Xi Ni & Matthew C. Chang, 2009. "The Information Contents of VIX Index and Range-based Volatility on Volatility Forecasting Performance of S&P 500," Economics Bulletin, AccessEcon, vol. 29(4), pages 2592-2604.
    • Handle: RePEc:ebl:ecbull:eb-09-00548
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    References listed on IDEAS

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    2. Cathy Chen & Shu-Yu Chen & Sangyeol Lee, 2013. "Bayesian Unit Root Test in Double Threshold Heteroskedastic Models," Computational Economics, Springer;Society for Computational Economics, vol. 42(4), pages 471-490, December.

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    More about this item

    Keywords

    Range-based volatilities; GJR-based volatility forecasting; VIX index; SPA test;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G1 - Financial Economics - - General Financial Markets

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