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Stochastic Volatility in Mean: Empirical Evidence from Stock Latin American Markets

Author

Listed:
  • Carlos A. Abanto-Valle

    (Federal University of Rio de Janeiro)

  • Gabriel Rodríguez

    (Departamento de Economía de la Pontificia Universidad Católica del Perú / Fiscal Council of Peru)

  • Hernán B. Garrafa-Aragón

    (Universidad Nacional de Ingeniería)

Abstract

Using a Stochastic Volatility in Mean (SVM) model, we perform an empirical study of five Latin American indexes in order to see the impact of the volatility in the mean of the returns. We use MCMC Hamiltonian dynamics. The results indicate that volatility has a negative impact on returns suggesting that the volatility feedback effect is stronger than the effect related to the expected volatility. This result is clear and opposite to the finding of Koopman and Uspensky (2002). The other countries present negative values but the upper tail of the intervals are near to the zero value.

Suggested Citation

  • Carlos A. Abanto-Valle & Gabriel Rodríguez & Hernán B. Garrafa-Aragón, 2020. "Stochastic Volatility in Mean: Empirical Evidence from Stock Latin American Markets," Documentos de Trabajo / Working Papers 2020-481, Departamento de Economía - Pontificia Universidad Católica del Perú.
    • Handle: RePEc:pcp:pucwps:wp00481
    DOI: 10.18800/2079-8474.0481
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    References listed on IDEAS

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    1. Adolfo Figueroa, 2019. "The Quality of Society," Springer Books, Springer, number 978-3-030-11656-9, June.
    2. Lengua Lafosse, Patricia & Rodríguez, Gabriel, 2018. "An empirical application of a stochastic volatility model with GH skew Student's t-distribution to the volatility of Latin-American stock returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 155-173.
    3. Abanto-Valle, C.A. & Bandyopadhyay, D. & Lachos, V.H. & Enriquez, I., 2010. "Robust Bayesian analysis of heavy-tailed stochastic volatility models using scale mixtures of normal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 2883-2898, December.
    4. Adolfo Figueroa, 2017. "Economics of the Anthropocene Age," Libros no PUCP / Books other publishers, Otras editoriales / Other publishers, edition 1, number otr-2017-07, December.
    5. Adolfo Figueroa, 2019. "The Quality of Society Essays on the Unified Theory of Capitalism," Libros no PUCP / Books other publishers, Otras editoriales / Other publishers, edition 0, number otr-2019_01, December.
    6. Melino, Angelo & Turnbull, Stuart M., 1990. "Pricing foreign currency options with stochastic volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 239-265.
    7. Joshua C. C. Chan, 2017. "The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 17-28, January.
    8. Roman Liesenfeld & Robert C. Jung, 2000. "Stochastic volatility models: conditional normality versus heavy-tailed distributions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(2), pages 137-160.
    9. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November.
    10. Siem Jan Koopman & Eugenie Hol Uspensky, 2002. "The stochastic volatility in mean model: empirical evidence from international stock markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(6), pages 667-689.
    11. Langrock, Roland & MacDonald, Iain L. & Zucchini, Walter, 2012. "Some nonstandard stochastic volatility models and their estimation using structured hidden Markov models," Journal of Empirical Finance, Elsevier, vol. 19(1), pages 147-161.
    12. Jacquier, Eric & Polson, Nicholas G. & Rossi, P.E.Peter E., 2004. "Bayesian analysis of stochastic volatility models with fat-tails and correlated errors," Journal of Econometrics, Elsevier, vol. 122(1), pages 185-212, September.
    13. M. Angeles Carnero, 2004. "Persistence and Kurtosis in GARCH and Stochastic Volatility Models," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 319-342.
    14. Perron, Pierre & Qu, Zhongjun, 2010. "Long-Memory and Level Shifts in the Volatility of Stock Market Return Indices," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 275-290.
    15. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    16. Jhonatan Clausen & Angelo Cozzubo & Carolina Trivelli & Carlos Urrutia & Johanna Yancari, 2018. "Desigualdad y pobreza en un contexto de crecimiento económico," Libros no PUCP / Books other publishers, Otras editoriales / Other publishers, edition 1, number otr-2018-01, December.
    17. Bekaert, Geert & Wu, Guojun, 2000. "Asymmetric Volatility and Risk in Equity Markets," Review of Financial Studies, Society for Financial Studies, vol. 13(1), pages 1-42.
    18. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    19. Adolfo Figueroa, 2016. "Rules for Scientific Research in Economics," Springer Books, Springer, number 978-3-319-30542-4, June.
    20. Roland Langrock, 2011. "Some applications of nonlinear and non-Gaussian state--space modelling by means of hidden Markov models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(12), pages 2955-2970, March.
    21. Mark Girolami & Ben Calderhead, 2011. "Riemann manifold Langevin and Hamiltonian Monte Carlo methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(2), pages 123-214, March.
    22. Didit Nugroho & Takayuki Morimoto, 2015. "Estimation of realized stochastic volatility models using Hamiltonian Monte Carlo-Based methods," Computational Statistics, Springer, vol. 30(2), pages 491-516, June.
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