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Modeling the risk premium in the Russian stock market considering the asymmetry effect

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  • Juri Trifonov

    (HSE University, Moscow, Russian Federation)

Abstract

The study examines the risk premium modeling for three major Russian stock market indices. The key feature is accounting for the asymmetry effect in the risk premium via the asymmetric GARCH-M model. The empirical analysis provided evidence favoring a significant leverage effect in the risk premium in the Russian market. However, the effect sign is contrary to the hypothesis and the empirical evidence in the American market. These findings are probably explained by the violation of the efficient market hypothesis and the presence of a high proportion of irrational investors in the Russian stock market.

Suggested Citation

  • Juri Trifonov, 2023. "Modeling the risk premium in the Russian stock market considering the asymmetry effect," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 71, pages 5-19.
    • Handle: RePEc:ris:apltrx:0475
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    References listed on IDEAS

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    1. Tim Bollerslev, 2022. "Realized Semi(co)variation: Signs That All Volatilities are Not Created Equal [Vulnerable Growth]," Journal of Financial Econometrics, Oxford University Press, vol. 20(2), pages 219-252.
    2. Dmitriy Borzykh & Artem Yazykov, 2019. "The new KS method for a structural break detection in GARCH(1,1) models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 54, pages 90-104.
    3. Hong, Seok Young & Linton, Oliver, 2020. "Nonparametric estimation of infinite order regression and its application to the risk-return tradeoff," Journal of Econometrics, Elsevier, vol. 219(2), pages 389-424.
    4. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    5. Kilian, Lutz & Baumeister, Christiane, 2014. "A General Approach to Recovering Market Expectations from Futures Prices With an Application to Crude Oil," CEPR Discussion Papers 10162, C.E.P.R. Discussion Papers.
    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    8. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    9. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    10. Tim Bollerslev & Julia Litvinova & George Tauchen, 2006. "Leverage and Volatility Feedback Effects in High-Frequency Data," Journal of Financial Econometrics, Oxford University Press, vol. 4(3), pages 353-384.
    11. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    12. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    13. Alberto G. Rossi & Allan Timmermann, 2015. "Modeling Covariance Risk in Merton's ICAPM," The Review of Financial Studies, Society for Financial Studies, vol. 28(5), pages 1428-1461.
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    Keywords

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    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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