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Has the interaction between skewness and kurtosis of asset returns information content for risk forecasting?

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  • Jiménez, Inés
  • Mora-Valencia, Andrés
  • Perote, Javier

Abstract

This paper introduces the effect of the crossed products of Hermite polynomials on Gram-Charlier densities. This allows capturing the impact of the interaction between skewness and kurtosis and evaluating this new parameter as an additional source of information for risk management. We show that our modified Gram-Charlier density presents an improved accuracy, especially at distribution tails. Risk quantification is assessed for S&P500 losses with backtesting procedures for Value-at-Risk and Median Shortfall.

Suggested Citation

  • Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2022. "Has the interaction between skewness and kurtosis of asset returns information content for risk forecasting?," Finance Research Letters, Elsevier, vol. 49(C).
    • Handle: RePEc:eee:finlet:v:49:y:2022:i:c:s1544612322003294
    DOI: 10.1016/j.frl.2022.103105
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    References listed on IDEAS

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    1. Emmanuel Jurczenko & Bertrand Maillet & Bogdan Negrea, 2004. "A note on skewness and kurtosis adjusted option pricing models under the Martingale restriction," Quantitative Finance, Taylor & Francis Journals, vol. 4(5), pages 479-488.
    2. Trino-Manuel Ñíguez & Javier Perote, 2012. "Forecasting Heavy-Tailed Densities with Positive Edgeworth and Gram-Charlier Expansions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(4), pages 600-627, August.
    3. León, à ngel & Mencía, Javier & Sentana, Enrique, 2009. "Parametric Properties of Semi-Nonparametric Distributions, with Applications to Option Valuation," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 176-192.
    4. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2020. "Risk quantification for commodity ETFs: Backtesting value-at-risk and expected shortfall," International Review of Financial Analysis, Elsevier, vol. 70(C).
    5. Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2022. "Semi-nonparametric risk assessment with cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 59(C).
    6. Bertrand Maillet & Bogdan Négréa, 2004. "A Note on Skewness and Kurtosis Adjusted Option Pricing Models under the Martingale Restriction," Post-Print hal-00308980, HAL.
    7. Ignacio Mauleón, 2010. "Assessing the value of Hermite densities for predictive distributions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(8), pages 689-714, December.
    8. Steven Kou & Xianhua Peng, 2014. "Expected shortfall or median shortfall," Journal of Financial Engineering (JFE), World Scientific Publishing Co. Pte. Ltd., vol. 1(01), pages 1-6.
    9. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    10. Ignacio Mauleon & Javier Perote, 2000. "Testing densities with financial data: an empirical comparison of the Edgeworth-Sargan density to the Student's t," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 225-239.
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    Cited by:

    1. Bouri, Elie & Jalkh, Naji, 2023. "Spillovers of joint volatility-skewness-kurtosis of major cryptocurrencies and their determinants," International Review of Financial Analysis, Elsevier, vol. 90(C).

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    More about this item

    Keywords

    Gram-charlier expansions; Skewness; Kurtosis; Value-at-risk; Median shortfall; Backtesting;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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