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Analysis of Herd Behavior in Stock Prices Using Machine Learning

  • Gerard RiqueEmail author
  • Patrick Hosein
  • Vaalmikki Arjoon
Conference paper
  • 79 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11938)

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

Herd behavior Machine learning Regression 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.The University of the West IndiesSt. AugustineTrinidad and Tobago

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