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The information contents of vix index and range-based volatility on volatility forecasting performance of s&p 500

Author

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  • Jui-Cheng Hung

    (Lunghwa University of Science and Technology)

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, 2009. "The information contents of vix index and range-based volatility on volatility forecasting performance of s&p 500," Economics Bulletin, AccessEcon, vol. 29(3), pages 1-24.
    • Handle: RePEc:ebl:ecbull:eb-09-00547
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    File URL: http://www.accessecon.com/pubs/EB/2009/Volume29/EB-09-V29-I3-A24.pdf
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    Cited by:

    1. Maithili S. Naik & Y.V. Reddy, 2021. "India VIX and Forecasting Ability of Symmetric and Asymmetric GARCH Models," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 11(3), pages 252-262, March.
    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.

    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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