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Analysis of Herding Behavior Using Bayesian Quantile Regression

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Beyond Traditional Probabilistic Methods in Economics (ECONVN 2019)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 809))

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Abstract

The purpose of this paper is to analyse the herding behavior of eight stock sectors of the Stock Exchange of Thailand consisting of Banking (BANK), Commerce (COM), Communications (COMUN), Energy and Utilities (ENERG), Food and Beverage (FOOD), Personal Products and Pharmaceuticals (PERS), Petrochemicals and Chemicals (PETRO), and Property Development (PROP), for the period from January of 2014 to May of 2018. Conventionally, the model used for finding the herding behavior is linear regression, which is based on the mean of the distribution. However, the result obtained from the linear mean regression model may not be consistent with the heterogeneity of investor behavior. Thus, in this study, we employ Bayesian quantile regression to empirically estimate the daily stock returns. The innovation of this paper is to examine the data conditional on different quantiles and test the behavioral relation between stock returns and market movements with different quantile distributions. The results show that five out of the eight sectors have herding behavior at quantile 0.25 and the remaining three sectors have no herding behavior.

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References

  1. Ababio, K.A., Mwamba, J.M.: Test of herding behaviour in the Johannesburg stock exchange: application of quantile regression model. J. Econ. Financ. Sci. 10(3), 457–474 (2017)

    Google Scholar 

  2. Al-Shboul, M.Q.: Asymmetric effects and the herd behavior in the Australian equity market. Int. J. Bus. Manag. 7(7), 121 (2012)

    Article  Google Scholar 

  3. Barnes, M.L., Hughes, A.T.W.: A quantile regression analysis of the cross section of stock market returns (2002)

    Google Scholar 

  4. Bikhchandani, S., Sharma, S.: Herd behavior in financial markets. IMF Staff Papers 47(3), 279–310 (2000)

    Google Scholar 

  5. Buchinsky, M.: Recent advances in quantile regression models: a practical guideline for empirical research. J. Hum. Resour. 33, 88–126 (1998)

    Article  Google Scholar 

  6. Chang, E.C., Cheng, J.W., Khorana, A.: An examination of herd behavior in equity markets: an international perspective. J. Bank. Financ. 24(10), 1651–1679 (2000)

    Article  Google Scholar 

  7. Chiang, T.C., Zheng, D.: An empirical analysis of herd behavior in global stock markets. J. Bank. Financ. 34(8), 1911–1921 (2010)

    Article  Google Scholar 

  8. Christie, W.G., Huang, R.D.: Following the pied piper: do individual returns herd around the market? Financ. Anal. J. 51(4), 31–37 (1995)

    Article  Google Scholar 

  9. Demirer, R., Kutan, A.M.: Does herding behavior exist in Chinese stock markets? J. Int. Financ. Mark. Inst. Money 16(2), 123–142 (2006)

    Article  Google Scholar 

  10. Demirer, R., Kutan, A.M., Chen, C.D.: Do investors herd in emerging stock markets? Evidence from the Taiwanese market. J. Econ. Behav. Organ. 76(2), 283–295 (2010)

    Article  Google Scholar 

  11. Economou, F., Kostakis, A., Philippas, N.: Cross-country effects in herding behaviour: evidence from four south European markets. J. Int. Financ. Mark. Inst. Money 21(3), 443–460 (2011)

    Article  Google Scholar 

  12. Gerlach, R.H., Chen, C.W., Chan, N.Y.: Bayesian time-varying quantile forecasting for value-at-risk in financial markets. J. Bus. Econ. Stat. 29(4), 481–492 (2011)

    Article  MathSciNet  Google Scholar 

  13. Gleason, K.C., Mathur, I., Peterson, M.A.: Analysis of intraday herding behavior among the sector ETFs. J. Empir. Financ. 11(5), 681–694 (2004)

    Article  Google Scholar 

  14. Hwang, S., Salmon, M.: Market stress and herding. J. Empir. Financ. 11(4), 585–616 (2004)

    Article  Google Scholar 

  15. Koenker, R.W., d’Orey, V.: Algorithm AS 229: computing regression quantiles. J. R. Stat. Soc. Ser. C (Appl. Stat.) 36(3), 383–393 (1987)

    Google Scholar 

  16. Koop, G., Potter, S.M.: Bayesian analysis of endogenous delay threshold models. J. Bus. Econ. Stat. 21(1), 93–103 (2003)

    Article  MathSciNet  Google Scholar 

  17. Lao, P., Singh, H.: Herding behaviour in the Chinese and Indian stock markets. J. Asian Econ. 22(6), 495–506 (2011)

    Article  Google Scholar 

  18. Pastpipatkul, P., Yamaka, W., Wiboonpongse, A., Sriboonchitta, S.: Spillovers of quantitative easing on financial markets of Thailand, Indonesia, and the Philippines. In: International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, pp. 374–388. Springer, Cham, October 2015

    Google Scholar 

  19. Reich, B.J., Fuentes, M., Dunson, D.B.: Bayesian spatial quantile regression. J. Am. Stat. Assoc. 106(493), 6–20 (2011)

    Article  MathSciNet  Google Scholar 

  20. Saastamoinen, J.: Quantile regression analysis of dispersion of stock returns-evidence of herding. Keskustelualoitteita 57, 1–19 (2008)

    Google Scholar 

  21. Shiller, R.J.: Behavioral economics and institutional innovation (2005)

    Article  Google Scholar 

  22. Wermers, R.: Mutual fund herding and the impact on stock prices. J. Financ. 54(2), 581–622 (1999)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Center of Excellence in Econometrics, Chiang Mai University, Chiang Mai, Thailand

    Rungrapee Phadkantha

  2. International College of Digital Innovation, Chiang Mai University, Chiang Mai, Thailand

    Rungrapee Phadkantha

  3. Center of Excellence in Econometrics, Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Woraphon Yamaka & Songsak Sriboonchitta

Authors
  1. Rungrapee Phadkantha
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  2. Woraphon Yamaka
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  3. Songsak Sriboonchitta
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Corresponding author

Correspondence to Rungrapee Phadkantha .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Vladik Kreinovich

  2. Banking University HCMC, Ho Chi Minh City, Vietnam

    Nguyen Ngoc Thach

  3. Banking University HCMC, Ho Chi Minh City, Vietnam

    Nguyen Duc Trung

  4. TTC Group, Ho Chi Minh City, Vietnam

    Dang Van Thanh

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Phadkantha, R., Yamaka, W., Sriboonchitta, S. (2019). Analysis of Herding Behavior Using Bayesian Quantile Regression. In: Kreinovich, V., Thach, N., Trung, N., Van Thanh, D. (eds) Beyond Traditional Probabilistic Methods in Economics. ECONVN 2019. Studies in Computational Intelligence, vol 809. Springer, Cham. https://doi.org/10.1007/978-3-030-04200-4_56

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