Abstract
In this paper, we consider the problem of herding behaviour in a Stock Exchange. Herding occurs when amateur investors follow the advice of financial gurus since they do not have the time, expertise or finances to do the research that is typically performed by these gurus. Although herding is well understood, many of the previous analyses have been through the use of statistical techniques. In this paper we have a second look using Machine Learning and demonstrate its effectiveness. We use a dataset obtained from the Singapore Stock exchange. Stocks were grouped into different portfolios based on the number of shares traded per day. Results from the algorithm show that herding is evident in each portfolio. We also find that herding is more pronounced among stocks that have higher volumes of shares traded.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Ahmed, N.K., Atiya, A.F., Gayar, N.E., El-Shishiny, H.: An empirical comparison of machine learning models for time series forecasting. Econ. Rev. 29(5–6), 594–621 (2010)
Bottou, L.: Large-scale machine learning with stochastic gradient descent. In: Lechevallier, Y., Saporta, G. (eds.) COMPSTAT 2010, pp. 177–186. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-7908-2604-3_16
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)
Chiang, T.C., Zheng, D.: An empirical analysis of herd behavior in global stock markets. J. Bank. Financ. 34(8), 1911–1921 (2010)
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)
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)
Jung, J.K., Patnam, M., Ter-Martirosyan, A.: An Algorithmic Crystal Ball: Forecasts-based on Machine Learning. International Monetary Fund (2018)
Laih, Y.W., Liau, Y.S.: Herding behavior during the subprime mortgage crisis: evidence from six Asia-Pacific stock markets. Int. J. Econ. Financ. 5(7), 71–84 (2013)
Lao, P., Singh, H.: Herding behaviour in the Chinese and Indian stock markets. J. Asian Econ. 22(6), 495–506 (2011)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Rique, G., Hosein, P., Arjoon, V. (2019). Analysis of Herd Behavior in Stock Prices Using Machine Learning. In: El Yacoubi, S., Bagnoli, F., Pacini, G. (eds) Internet Science. INSCI 2019. Lecture Notes in Computer Science(), vol 11938. Springer, Cham. https://doi.org/10.1007/978-3-030-34770-3_27
Download citation
DOI: https://doi.org/10.1007/978-3-030-34770-3_27
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-34769-7
Online ISBN: 978-3-030-34770-3
eBook Packages: Computer ScienceComputer Science (R0)