Elucidating the Impact of behavioral biases in Pakistan Stock Market: Moderating Impact of Financial Literacy

Authors

  • Muhammad Haroon Rasheed University of Sargodha, Sargodha, Pakistan http://orcid.org/0000-0001-7951-6867
  • Amir Rafique COMSATS University, Islamabad, Pakistan
  • Usama Kalim Southwest University in Chongqing, Chongqing, China
  • Faid Gul National University of Modern Languages, Islamabad, Pakistan

DOI:

https://doi.org/10.29145/jqm.52.06

Keywords:

behavioral finance, financial literacy, decision making

Abstract

The current study focuses on some of the most commonly relied upon biases in decision making. The study aimed at understanding the influence of herding, overconfidence, anchoring, and loss aversion on the decision-making style of investor besides it also investigates the role of financial literacy, since the traditional paradigm of finance is of the view that the knowledge of finance is directly associated with the degree of irrational outcomes. To explore this linkage data from investors trading at Lahore, Karachi, and Islamabad is gathered. Structural equation modeling is used for establishing the proposed associations. The results revealed that behavioral biases significantly impact the decision-making of investors.  The results of moderation analysis presented that financial literacy plays a major role in de-biasing decision making. These findings can be extremely useful for investors, policymakers, and investment professionals. Not only to make optimal decision-making but also by providing a deeper understanding of the daily life stock market behavior.

Downloads

Download data is not yet available.

Downloads

Published

2021-08-31

How to Cite

Rasheed, M. H., Rafique, A., Kalim, U., & Gul, F. (2021). Elucidating the Impact of behavioral biases in Pakistan Stock Market: Moderating Impact of Financial Literacy. Journal of Quantitative Methods, 5(2), 128–146. https://doi.org/10.29145/jqm.52.06

Issue

Section

Articles

Similar Articles

1 2 > >> 

You may also start an advanced similarity search for this article.