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Table of Contents

THE INFORMATION CONTENT OF DIVIDEND ANNOUNCEMENTS IN OMAN – Part 5

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CHAPTER 3: DATA AND METHODOLOGY

This chapter offers a discussion of the approach, statistical sampling, and descriptions of the variables used to test the theory and the hypotheses development relevant to the impact of the information content of dividends on market reactions in Oman and on the Muscat Securities Market (MSM).

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Mixed-methods Study Approach and Rationale

To accomplish the objective of this study to discern the market prices/behaviour as it is impacted by announcement content of dividends in Oman, a mixed-methods approach was used: (1) an event study was conducted to identify and calculate 90 dividend announcements and abnormal returns on investment (ROI) during the event period from July 2013 to July 2014; and 2) a regression analysis was done to calculate market behaviour around the ex-dividend events across 100 listed institutions on the Oman MSM covering the same period.

Event Study

The event study method will be comprised of three stages: 1) stage when stock returns prior to the event period (aka, the estimation period), whereby data are observed and gathered to form the database for the regression analysis model and the estimation of the expected stock returns; 2) stage when an estimation is made on the departure of real stock returns from the expected stock returns during the event period to generate the abnormal returns; and 3) stage for finding the daily return of the share and market index and testing if abnormal returns differ (from zero). The original data comprises closing price of shares and the closing value of the market index.

According to Khotari and Warner, in both corporate and capital market research contexts, the event study is a valuable instrument of measurement:

In a corporate context, the usefulness of event studies arises from the fact that the magnitude of abnormal performance at the time of an event provides a measure of the (unanticipated) impact of this type of event on the wealth of the firms’ claimholders… Event studies also serve an important purpose in capital market research as a way of testing market efficiency. Systematically nonzero abnormal security returns that persist after a particular type of corporate event are inconsistent with market efficiency (2006, p. 4).

That is, the event study approach here can have useful implications that inform dividend policy and at the same time can serve to answer the inquiry into market efficiency—or, to reinforce or negate market efficiency theory.

Regression analysis

An ordinary least squares (OLS) regression analysis shall determine the correlation between dividend announcements and market behaviour—with dividend announcement content being the hypothesized determinant of market price. This will be achieved through regression of the data which per-share dividends (in US Dollars) against abnormal returns in the event windows. Whenever needed, acquired data shall be (legitimately) modified to fit the stated convention.

According to Khalaf (2012), although an abundance of studies have been focused on dividends, not only are dividends a vital part of investment processes but understanding of dividends in such contexts is limited. In these respects, of the primary reasons for using regression analysis, one major rationale is that explained by the Esri staff (n.d.): the first reason is…

To model some phenomena in order to better understand it and possibly use that understanding to affect policy or to make decisions about appropriate actions to take….

The efforts at understanding are facilitated; moreover, the utility of regression analysis for this study is in its leading to conclusions about particular economic theory and the specific dividend signalling theory and dividend effect and the efficient market hypotheses and whether or not they are the best fit for analysing information content of dividends.

To this end, regression analysis will be calculated based upon event study data, as follows:

It was intended that the event study and regression model would

  1. - find stock returns prior to the event period (aka, the estimation period);
  2. -estimate the expected stock returns;
  3. -estimate departure of real stock returns from the expected stock returns during the event period to generate the abnormal returns; and
  4. -find the daily return of the share and market index/testing if abnormal returns differ (from zero).

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To accomplish the above, the researcher selected 100 different companies listed on the Muscat Stock Exchange (MSE). All of these companies are representatives of different sectors—such as the banking and financial sector, the electronic sector, the industrial sector, and the services and insurance sector, among others. The researcher then applied five different hypotheses that needed to be cover in this particular analysis; every hypothesis was tested through regression analysis and with simple tools, as well:

Hypothesis 1:

H0: changes in dividends are positively related to changes in future performances (ROA)

H1: changes in dividends are negatively related to changes in future performances

Hypothesis # 2

H0: changes in total assets are positively related to changes in ROA

H1: changes in total assets are negatively related to changes in ROA

Hypothesis #3

H0: changes in total sales are positively related to changes in ROA

H1: changes in total sales are negatively related to changes in ROA

Hypothesis #4

H0: changes in the leverage ratio are positively related to changes in ROA

H1: changes in the leverage ratio are negatively related to changes in ROA

Hypothesis #5

H0: Age of firm is positively related to changes in ROA

H1: Age of firm is negatively related to changes in ROA

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