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Uncovering the Skewness News Impact Curve

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  • Stanislav Anatolyev
  • Anton Petukhov

Abstract

We investigate, within flexible semiparametric and parametric frameworks, the shape of the news impact curve (NIC) for the conditional skewness of stock returns, that is, how past returns affect present skewness. We find that returns may impact skewness in ways that sharply differ from those proposed in earlier literature. The skewness NIC may exhibit sign asymmetry, other types of nonlinearity, and even non-monotonicity. In particular, the newly discovered "rotated S"-shape of the skewness NIC for the S&P500 index is intriguing. We explore, among other things, properties of skewness NIC estimates and conditional density forecasts, the term structure of the skewness NIC, and previously documented approaches to its modeling.

Suggested Citation

  • Stanislav Anatolyev & Anton Petukhov, 2016. "Uncovering the Skewness News Impact Curve," Journal of Financial Econometrics, Oxford University Press, vol. 14(4), pages 746-771.
    • Handle: RePEc:oup:jfinec:v:14:y:2016:i:4:p:746-771.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbw005
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    References listed on IDEAS

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    1. Ranjini Jha & Madhu Kalimipalli, 2010. "The economic significance of conditional skewness in index option markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(4), pages 378-406, April.
    2. Paul Schneider & Christian Wagner & Josef Zechner, 2020. "Low‐Risk Anomalies?," Journal of Finance, American Finance Association, vol. 75(5), pages 2673-2718, October.
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    Cited by:

    1. Stanislav Anatolyev, 2021. "Directional news impact curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 94-107, January.
    2. Trung H. Le & Apostolos Kourtis & Raphael Markellos, 2023. "Modeling skewness in portfolio choice," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(6), pages 734-770, June.
    3. Ñíguez, Trino-Manuel & Perote, Javier, 2017. "Moments expansion densities for quantifying financial risk," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 53-69.
    4. Trung H. Le, 2024. "Forecasting VaR and ES in emerging markets: The role of time‐varying higher moments," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 402-414, March.
    5. León, Ángel & Ñíguez, Trino-Manuel, 2020. "Modeling asset returns under time-varying semi-nonparametric distributions," Journal of Banking & Finance, Elsevier, vol. 118(C).
    6. Le, Trung H., 2020. "Forecasting value at risk and expected shortfall with mixed data sampling," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1362-1379.
    7. León, Ángel & Ñíguez, Trino-Manuel, 2021. "The transformed Gram Charlier distribution: Parametric properties and financial risk applications," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 323-349.

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