Testing the degree of efficiency of Ireland Capital market with Efficient Market Hypothesis (EMH): A comparative analysis of Ireland Capital market efficiency with its neighbouring capital markets of the UK, Belgium and the Netherlands

Kaushik, Medha (2020) Testing the degree of efficiency of Ireland Capital market with Efficient Market Hypothesis (EMH): A comparative analysis of Ireland Capital market efficiency with its neighbouring capital markets of the UK, Belgium and the Netherlands. Masters thesis, Dublin, National College of Ireland.

Preview	PDF (Master of Science) Download (895kB) | Preview
Preview	PDF (Configuration manual) Download (233kB) | Preview

Abstract

This paper analyses Ireland's capital market efficiency and performs a comparative analysis with its neighbouring countries of the United Kingdom, Belgium and the Netherlands using daily returns from their respective stock market indices from 1 January 2014 to 31 December 2019, a period rarely studied. The techniques used to conduct the analysis are random walk tests, namely unit root test, serial correlation test, runs test and Shannon Entropy Test. The four developed European markets were tested for their weak form of efficient market hypothesis and the information Efficiency (Shannon Entropy) was employed to ascertain the degree of information efficiency in the markets. The empirical evidence indicates that the Ireland Stock market and its Neighboring countries (UK, Belgium, and Netherland) confirm Weak form of Efficient market hypothesis. The results from Shannon Entropy – informational efficiency point out Belgium and Netherlands to be higher in information efficiency than Ireland with UK scoring the least on the information efficiency of all the tested markets. The results concluded that in these markets a passive approach to portfolio management is a better investment strategy than an active portfolio management strategy. Furthermore, it is suggested to test the individual stocks in the index for efficiency and more complex models and test be used to ascertain efficiency in these indexes with a higher degree of certainty.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software H Social Sciences > HG Finance > Investment
Divisions:	School of Computing > Master of Science in FinTech
Depositing User:	Dan English
Date Deposited:	29 Jan 2021 16:42
Last Modified:	29 Jan 2021 16:42
URI:	https://norma.ncirl.ie/id/eprint/4569

Actions (login required)

View Item