<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:dc="http://purl.org/dc/elements/1.1/" version="2.0">
  <channel>
    <title>OAR@UM Collection:</title>
    <link>https://www.um.edu.mt/library/oar/handle/123456789/112843</link>
    <description />
    <pubDate>Sat, 04 Apr 2026 19:07:02 GMT</pubDate>
    <dc:date>2026-04-04T19:07:02Z</dc:date>
    <item>
      <title>A comparative analysis of financial sectors in Europe</title>
      <link>https://www.um.edu.mt/library/oar/handle/123456789/128090</link>
      <description>Title: A comparative analysis of financial sectors in Europe
Abstract: Financial sectors in Europe have been the backbone of several economies throughout the years, while collectively, they have put Europe at the forefront for global competition with other financial hubs. It was therefore seen as ideal, especially at times of great macroeconomic volatility, that a comparative analysis is done as to assess on which financial sectors Europe is mostly dependent on, and which domestic economies mostly rely on the financial sectors. The study has gone through all European countries from a quantitative approach, and has assessed different elements of the markets, such as the Gross Domestic Products (GDP), Gross Value Added (GVA), the Gross Operating Surplus (GOS), and so on. Furthermore, the figures obtained were deflated as to provide a more realistic overview of the European financial sectors, given inflationary pressures in recent years. The GOS, GVA, and Compensation for employees were then analysed through graphs for every EU country, to be able to compare each financial sector with the other. It was also noted that there is a strong element of dependency between the Gross Domestic Product of a country and the Gross Value Added created by the financial sector of the country, despite this not being applicable for all countries. This is because, for most countries, it was noted that as the GVA of the financial sector grows, the GDP of the country grows as well. The other way round was also assessed, where it was noted that, for most countries, as the GDP of a country increases, the GVA of financial institutions grows as well. For the countries that such a relationship was not relevant, plausible explanations were researched and laid out, as to try to derive an answer on why this is not applicable. This was also true for the employment rate within the financial sector, where it was noted that, for most countries, higher GDP will result into greater employment rates within the financial sector as to cater for this growth. From a qualitative approach, 5 countries were chosen which were deemed as some of the most prominent financial sectors in Europe and some of the largest within their domestic economy, or because a particular trend was noticed for their financial sector, whereby a case study for each has been done. These countries, which are Malta, Luxembourg, Cyprus, Ireland, and Portugal, were analysed as to obtain an overview of the country’s financial market, the present state of the financial market within the country, and the future of that financial market. It was noted, in general, that several governments all around Europe are putting in efforts as to better their position and become more prominent within such sector. This was mainly noted through the qualitative approach, which saw detailed plans being put in place by the governments of the chosen countries, in order for the financial markets of these countries to continue to evolve. All of this show that financial markets in Europe remain catalyst for the domestic and European economies, requiring proper supervision and input by Governments to protect and stabilise this significant sector of the economy.
Description: B.Com. (Hons)(Melit.)</description>
      <pubDate>Sun, 01 Jan 2023 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://www.um.edu.mt/library/oar/handle/123456789/128090</guid>
      <dc:date>2023-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>The rationale behind stock splits : its effects and market reaction</title>
      <link>https://www.um.edu.mt/library/oar/handle/123456789/113692</link>
      <description>Title: The rationale behind stock splits : its effects and market reaction
Abstract: This study aims to investigate the impact of stock splits on the performance of selected &#xD;
companies from different sectors listed on NYSE and NASDAQ from June 2020 to the end of &#xD;
December 2022. The study employs the market model-event study methodology with an event &#xD;
window of 66 days (50 days prior to announcement split and 15 days post-announcement split) &#xD;
and split announcement date (𝐴𝑛 date, 𝑡0) as the event date, to examine the market reaction. &#xD;
The findings indicate that the market is found to react positively with significantly positive &#xD;
average abnormal results on 𝑡0 and very near to the 𝐴𝑛 date especially evident during 𝑡−1 to 𝑡+1. &#xD;
Several hypotheses were considered in this study. The findings suggested that signalling &#xD;
hypothesis was the main motive behind the actions.
Description: B.Com.(Hons)(Melit.)</description>
      <pubDate>Sun, 01 Jan 2023 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://www.um.edu.mt/library/oar/handle/123456789/113692</guid>
      <dc:date>2023-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>A comparative analysis on the performance of publicly traded companies in Europe</title>
      <link>https://www.um.edu.mt/library/oar/handle/123456789/113688</link>
      <description>Title: A comparative analysis on the performance of publicly traded companies in Europe
Abstract: The two main objectives of this dissertation were to find correlations and &#xD;
quantitative linear relationships between a number of dependent variables with &#xD;
multiple independent variables for several publicly traded companies in Europe. &#xD;
This dissertation takes on a quantitative approach because it has selected two &#xD;
statistical models that are used to reach the objectives. The first model that was &#xD;
selected was Multiple Correlation Coefficient which tests the level of correlation &#xD;
between the X variables with the Y variables. The second model that is used for &#xD;
this study was Multiple Linear Regression. This statistical model tests multiple X &#xD;
variables with a single Y variable and generates an equation that represents the &#xD;
linear relationship between the significant variables.&#xD;
The dependent variables that were tested were Return on Assets, Current Ratio &#xD;
and Debt/Equity Ratio. All of these ratios were calculated from the interim/annual &#xD;
financial statements published by the companies. When it came to the &#xD;
independent variables, the ones selected were Investments in Assets, Price &#xD;
Changes and Volume Changes. The first of which was also found in the financial &#xD;
statements whilst for the other two the data was generated from the stock &#xD;
markets. When it came to the selection of data the companies were all public &#xD;
traded in Europe that came from different sectors and countries. Some of the &#xD;
sectors selected were software, telecommunications, pharmaceuticals, car &#xD;
manufactures and much more. Some of the countries that were tested included &#xD;
Malta, France, Italy, United Kingdom and more.&#xD;
The results from this study varied showing some which were very significant that &#xD;
showed linear relationship and correlations between the selected independent &#xD;
and dependent variables. There were some specific tests where this model was &#xD;
not successful, this can be due to limitations that this dissertation faced. There &#xD;
were some shortcomings when carrying out this study and for that reason there &#xD;
are a number of recommendations proposed which can help improve future &#xD;
studies in the area of performance evaluation using financial ratio analysis.
Description: B.Com.(Melit.)</description>
      <pubDate>Sun, 01 Jan 2023 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://www.um.edu.mt/library/oar/handle/123456789/113688</guid>
      <dc:date>2023-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Profitability determinants : empirical evidence from the banking sector</title>
      <link>https://www.um.edu.mt/library/oar/handle/123456789/113684</link>
      <description>Title: Profitability determinants : empirical evidence from the banking sector
Abstract: This research study empirically examines a set of carefully chosen profitability &#xD;
determinants for a sample of 50 banks operating in different countries across the &#xD;
EU, America, Asia, Africa and Australia from 2007 to 2021. Two types of data &#xD;
methods were employed; a multiple linear regression model was used to identify &#xD;
the impact of the variables on each bank separately, and then a panel data &#xD;
regression model (two-level random intercept model) was used to provide a &#xD;
conclusion on the determinants and their relationship with bank’s profitability.&#xD;
The outcomes of the multiple linear regression demonstrate a consistent negative &#xD;
relation between bank size and bank profitability in all three instances of &#xD;
profitability assessments. ROAA and NIM have a positive relationship with capital &#xD;
adequacy. However, there is a negative relationship between capital adequacy &#xD;
and ROAE. Management efficiency has a negative relationship with both ROAA &#xD;
and ROAE. Management efficiency, on the other hand, has a positive relationship &#xD;
with NIM, contrary to predictions. Finally, ROAA and NIM have a positive &#xD;
association with liquidity risk, whilst ROAE has a negative relationship with &#xD;
liquidity risk.&#xD;
The panel data regression results, show that there is no correlation between bank &#xD;
size and ROAE, but there is a negative relationship between bank size and ROAA&#xD;
and/or NIM. Capital adequacy has a positive association with ROAA and NIM but &#xD;
has no influence on ROAE. Furthermore, there are no associations between &#xD;
management efficiency and ROAA, ROAE, and/or NIM. Finally, there is no link &#xD;
between liquidity risk and NIM, but there is a negative link between liquidity risk &#xD;
and ROAA and ROAE.
Description: B.Com.(Hons)(Melit.)</description>
      <pubDate>Sun, 01 Jan 2023 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://www.um.edu.mt/library/oar/handle/123456789/113684</guid>
      <dc:date>2023-01-01T00:00:00Z</dc:date>
    </item>
  </channel>
</rss>

