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How asymmetric is U.S. stock market volatility?

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  • Ederington, Louis H.
  • Guan, Wei
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Abstract

This paper explores differences in the impact of equally large positive and negative surprise return shocks in the aggregate U.S. stock market on: (1) the volatility predictions of asymmetric time-series models, (2) implied volatility, and (3) realized volatility. Following large negative surprise return shocks, both asymmetric time-series models (such as the EGARCH and GJR models) and implied volatility predict an increase in volatility and, consistent with this, ex post realized volatility normally rises as predicted. Following large positive return shocks, asymmetric time-series models predict an increase in volatility (albeit a much smaller increase than following a negative shock of the same magnitude), but both implied and realized volatilities generally fall sharply. While asymmetric time-series models predict a decline in volatility following near-zero returns, both implied and realized volatility are normally little changed from levels observed prior to the stable market. The reasons for the differences are explored.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Financial Markets.

Volume (Year): 13 (2010)
Issue (Month): 2 (May)
Pages: 225-248

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Handle: RePEc:eee:finmar:v:13:y:2010:i:2:p:225-248

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Web page: http://www.elsevier.com/locate/finmar

Related research

Keywords: Asymmetric volatility Implied volatility GARCH EGARCH;

References

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Citations

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Cited by:
  1. Jozef Barunik & Evzen Kocenda & Lukas Vacha, 2013. "Asymmetric volatility spillovers: Revisiting the Diebold-Yilmaz (2009) spillover index with realized semivariance," Papers 1308.1221, arXiv.org.
  2. Ederington, Louis H. & Guan, Wei, 2013. "The cross-sectional relation between conditional heteroskedasticity, the implied volatility smile, and the variance risk premium," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3388-3400.

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