Inter-Factor Determinants of Return Reversal Effect with Dynamic Bayesian Network Analysis: Empirical Evidence from Pakistan

• 발행기관: 한국유통과학회
• 저자명: Abdul HAQUE Marriam RAO Muhammad Ali Jibran QAMAR
• 간행물 정보: 『The Journal of Asian Finance, Economics and Business(JAFEB)』Vol. 9 No.3, 203~215쪽, 전체 13쪽
• 주제분류: 경제경영 > 경제학
• 파일형태: PDF
• 발행일자: 2022.03.30

영문 초록

Bayesian Networks are multivariate probabilistic factor graphs that are used to assess underlying factor relationships. From January 2005 to December 2018, the study examines how Dynamic Bayesian Networks can be utilized to estimate portfolio risk and return as well as determine inter-factor relationships among reversal profit-generating components in Pakistan’s emerging market (PSX). The goal of this article is to uncover the factors that cause reversal profits in the Pakistani stock market. In visual form, Bayesian networks can generate causal and inferential probabilistic relationships. Investors might update their stock return values in the network simultaneously with fresh market information, resulting in a dynamic shift in portfolio risk distribution across the networks. The findings show that investments in low net profit margin, low investment, and high volatility-based designed portfolios yield the biggest dynamical reversal profits. The main triggering aspects related to generation reversal profits in the Pakistan market, in the long run, are net profit margin, market risk premium, investment, size, and volatility factor. Investors should invest in and build portfolios with small companies that have a low price-to-earnings ratio, small earnings per share, and minimal volatility, according to the most likely explanation.

목차

1. Introduction

2. Literature Review

3. Methodology

4. Results and Discussion

5. Conclusion

References

키워드

Return Reversal Bayesian Networks Portfolio Risk Contrarian Strategy