Journal of Finance and Accounting

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Switching Regime in Investors’ Risk Perception

Received: 13 April 2014    Accepted: 25 April 2014    Published: 30 April 2014
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Abstract

Financial assets’ risk is considered as heteroskedastic, and is generally modelled with GARCH models. However, this risk is perceived in the same manner, only external events change, such as returns and historical risk. The way these events are treated by investors, is assumed static. Some scholars explain that risk perception is subject to structural breaks, which are not taken under consideration in GARCH models. For this reason, this paper aims to develop the switching regime GARCH model SWGARCH. Results clearly show that the SWGARCH can capture the risk dynamics of the studied indexes better than classical models.

DOI 10.11648/j.jfa.20140203.13
Published in Journal of Finance and Accounting (Volume 2, Issue 3, May 2014)
Page(s) 48-52
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Switching Regime, GARCH, Risk Perception, Index

References
[1] A. Abdymomunov, "Regime-switching measure of systemic financial stress," Annals of Finance, vol. 9, no. 3, pp. 455-470, 2013.
[2] R. F. Engle, "Autoregressive Conditional Heteroskedasticity with estimates of the variance of United Kingdom Inflation," Econometrica, vol. 50, no. 4, pp. 987-1007, 1982.
[3] T. Bollerslev, "Generalized Autoregressive Conditional Heteroskedasticity," Journal of Econometrics, vol. 31, pp. 307-327, 1986.
[4] A. O. I. Hoffmann, T. Post and J. M. E. Pennings, "Individual investor perceptions and behavior during the financial crisis," Journal of Banking & Finance, vol. 37, no. 1, pp. 60-74, 2013.
[5] J. Marcucci, "Forecasting Stock market Volatility With Regime-Switching GARCH Models," Studies in Nonlinear Dynamics & Econometrics, vol. 9, no. 4, 2005.
[6] T. G. Anderson and T. Bollerslev, "Answering the skeptics: yes, standard volatility models do provide accurate forecasts," International Economic Review, vol. 39, no. 4, pp. 885-905, 1998.
[7] H. Ichiue and K. Koyama, "Regime switches in exchange rate volatility and uncovered interest parity," Journal of International Money and Finance, vol. 30, no. 7, pp. 1436-1450, 2011.
[8] X. Liu, D. Margaritris and P. Wang, "Stock market volatility and equity returns: Evidence from a two-state Markov-switching model with regressors," Journal of Empirical Finance, vol. 19, no. 4, pp. 483-496, 2012.
[9] L. Bauwens, A. Preminger and J. Rombouts, "Theory and inference for a Markov switching GARCH model," Econometrics Journal, vol. 13, no. 2, pp. 218-244, 2010.
[10] J. Geweke and G. Amisano, "Hierarchical Markov Normal Mixture Models With Applications To Financial Asset Returns," Journal of Applied Econometrics, vol. 26, no. 1, pp. 1-29, 2011.
[11] R. F. Engle and T. Bollerslev, "Modelling the persistence of conditional variance," Econometric Reviews, vol. 5, pp. 1-50, 1986.
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Author Information
  • BESTMOD – ISG, Bouchoucha Bardo, Tunis 2000, Tunisia

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  • APA Style

    Houda Litimi, Ahmed BenSaïda. (2014). Switching Regime in Investors’ Risk Perception. Journal of Finance and Accounting, 2(3), 48-52. https://doi.org/10.11648/j.jfa.20140203.13

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    Houda Litimi; Ahmed BenSaïda. Switching Regime in Investors’ Risk Perception. J. Finance Account. 2014, 2(3), 48-52. doi: 10.11648/j.jfa.20140203.13

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    AMA Style

    Houda Litimi, Ahmed BenSaïda. Switching Regime in Investors’ Risk Perception. J Finance Account. 2014;2(3):48-52. doi: 10.11648/j.jfa.20140203.13

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  • @article{10.11648/j.jfa.20140203.13,
      author = {Houda Litimi and Ahmed BenSaïda},
      title = {Switching Regime in Investors’ Risk Perception},
      journal = {Journal of Finance and Accounting},
      volume = {2},
      number = {3},
      pages = {48-52},
      doi = {10.11648/j.jfa.20140203.13},
      url = {https://doi.org/10.11648/j.jfa.20140203.13},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.jfa.20140203.13},
      abstract = {Financial assets’ risk is considered as heteroskedastic, and is generally modelled with GARCH models. However, this risk is perceived in the same manner, only external events change, such as returns and historical risk. The way these events are treated by investors, is assumed static. Some scholars explain that risk perception is subject to structural breaks, which are not taken under consideration in GARCH models. For this reason, this paper aims to develop the switching regime GARCH model SWGARCH. Results clearly show that the SWGARCH can capture the risk dynamics of the studied indexes better than classical models.},
     year = {2014}
    }
    

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  • TY  - JOUR
    T1  - Switching Regime in Investors’ Risk Perception
    AU  - Houda Litimi
    AU  - Ahmed BenSaïda
    Y1  - 2014/04/30
    PY  - 2014
    N1  - https://doi.org/10.11648/j.jfa.20140203.13
    DO  - 10.11648/j.jfa.20140203.13
    T2  - Journal of Finance and Accounting
    JF  - Journal of Finance and Accounting
    JO  - Journal of Finance and Accounting
    SP  - 48
    EP  - 52
    PB  - Science Publishing Group
    SN  - 2330-7323
    UR  - https://doi.org/10.11648/j.jfa.20140203.13
    AB  - Financial assets’ risk is considered as heteroskedastic, and is generally modelled with GARCH models. However, this risk is perceived in the same manner, only external events change, such as returns and historical risk. The way these events are treated by investors, is assumed static. Some scholars explain that risk perception is subject to structural breaks, which are not taken under consideration in GARCH models. For this reason, this paper aims to develop the switching regime GARCH model SWGARCH. Results clearly show that the SWGARCH can capture the risk dynamics of the studied indexes better than classical models.
    VL  - 2
    IS  - 3
    ER  - 

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