Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Quantifying the Information Flow between Ghana Stock Market Index and Its Constituents Using Transfer Entropy

Domain:

socioeconomic

Record type:

paper
Creator:
PriAno
Publisher:
WILEY
Host:
We quantify the strength and the directionality of information transfer between the Ghana stock market index and its component stocks as well as observe the same among the individual stocks on the market using transfer entropy. The information flow between the market index and its components and among individual stocks is measured by the effective transfer entropy of the daily logarithm returns generated from the daily market index and stock prices of 32 stocks ranging from 2 nd January 2009 to 16 th February 2018. We find a bidirectional and unidirectional flow of information between the GSE index and its component stocks, and the stocks dominate the information exchange. Among the individual stocks, SCB is the most active stock in the information exchange as it is the stock that receives the highest amount of information, but the most informative source is EGL (an insurance company) that has the highest net information outflow while the most information sink is PBC that has the highest net information inflow. We further categorize the stocks into 9 stock market sectors and find the insurance sector to be the largest source of information which confirms our earlier findings. Surprisingly, the oil and gas sector is the information sink. Our results confirm the fact that other sectors including oil and gas mitigate their risk exposures through insurance companies and are always expectant of information originating from the insurance sector in relation to regulatory compliance issues. It is our firm conviction that this study would allow stakeholders of the market to make informed buy, sell, or hold decisions.

Visit

doi.org

Licenses

http://creativecommons.org/licenses/by/4.0/

Similar

Modeling Stock Market Volatility Using GARCH Approach on the Ghana Stock ExchangeDynamic Link Between Stock Market Size and Stock Market Investment Returns In NigeriaThe stock market reaction to stock dividends in Nigeria and their information contentPredicting Australian stock market index using neural networks exploiting dynamical swings and intermarket influencesA New EEMD‐Effective Transfer Entropy‐Based Methodology for Exchange Rate Market Information Transmission in Southern Africa Development CommunityPredicting Stock Market Price Movement Using Sentiment Analysis: Evidence From Ghana

Modeling Stock Market Volatility Using GARCH Approach on the Ghana Stock Exchange

The study examined and modeled stock market volatility of financial return series for three listed e

Dynamic Link Between Stock Market Size and Stock Market Investment Returns In Nigeria

Purpose—This study examines the dynamic link between stock market size and investment returns in Nig

The stock market reaction to stock dividends in Nigeria and their information content

Purpose The purpose of this paper is to examine whether stock dividend announcements create value f

Predicting Australian stock market index using neural networks exploiting dynamical swings and intermarket influences

This paper presents a computational approach for predicting the Australian stock market index - AORD

A New EEMD‐Effective Transfer Entropy‐Based Methodology for Exchange Rate Market Information Transmission in Southern Africa Development Community

The desire to form monetary unions among regional blocs in Africa has necessitated the need to asses

Predicting Stock Market Price Movement Using Sentiment Analysis: Evidence From Ghana

Abstract Predicting the stock market remains a challenging task due to the numer