Finance

This research paper mainly analyzes the impact of Digital Marketing in the Middle East and it also assesses its impacts on the marketing industry. The study evaluates the challenges facing the companies that implement digital marketing, analyzes the effectiveness if digital tools and compare the effectiveness of the print media and digital media. In addition the study further determines the country in the Middle East that has more potential in using digital marketing. The introduction of digital marketing is slowly replacing traditional or direct marketing.

The main focus of this research proposal is to analyze and identify the rise of Digital Marketing in the Middle East. The research question that has been used as the primary guideline for the study is to discover the growth of Digital Marketing in the Middle East nations.

The main research objectives of this study are to identify the challenges facing companies that implement digital marketing to promote their products, to identify whether the digital marketing tools are effective or not in the Middle East, to identify whether print media is more effective or digital media, to identify the Middle East country that has more potential in employing digital marketing tools and why and to identify the impact of the economic instability of (2009) affected the marketing strategies of the companies or not.

Methodology
In reality, two specific research methods are used the quantitative and the qualitative methods of research. These may be combined to give the mixed-method approach. Quantitative research reveals information that is personal because the participants input serves as the main source of information to the researcher (Creswell, 2001). In the present study quantitative data has been used to run the regression function. Qualitative research generates data that is based on the participants own categories of meaning, it is useful for learning a limited number of cases in depth, and tends to collect data in naturalistic background (Creswell, 2001).

Quantitative research method adopted for the current study.  The data which have been collected are the data of the portfolios formed, the securities and the  which is a measure of risk. In this method the data which have been collected would be analyzed. For this, regression analysis will be carried out in this study. The Ms-Excel software will be used for carrying out the regression analysis.

Basically, in this study, we will be talking about Capital Asset Pricing Model (CAPM). The Sharpe-Lintner version of the CAPM states that variability in market betas accounts for a significant portion of stock returns. The following equations can summarize CAPM in a nutshell.

QUOTE   1
QUOTE   2
Once all  QUOTE  s are obtained, the CAPM can be tested using the following generalized formula
QUOTE   3
QUOTE   is the standard deviation of residual returns  QUOTE   for each security.
The major story behind the Fama and Macbeth (1973) paper is testing the effectiveness of CAPM using 5 hypothesis, they are
C1  Linearity of the Security Market Line  QUOTE
C2 - No Systematic Effect of Non - Beta explains all return variability  QUOTE
C3 - Positive Expected Return - Risk Trade  off  QUOTE
SL - Sharpe - Lintner CAPM  QUOTE
ME - Market Efficiency  QUOTE  )
The hypothesis of this study is. H0 i  i2  Si 0
Against alternative hypothesis H1 i  i2  Si  0
We would be checking whether the explanatory variables, i, i2 and Si have any kind of influence on the explanatory variable, Rit.

Findings, Analysis and Interpretation
The investors take higher risk in order to get higher return from the market. The difference between the market return and the rate of interest is known as the market risk premium which is termed as (rm- rf). In a competitive framework, the expected risk premium varies directly with the  which is a measure of risk. Hence all the investments should be undertaken on the security market line (SML). The entire investment portfolio must be plotted along the slope of the SML. The x- axis represents  and y- axis represents the expected return.

The relationship can be written as
r- rf   (rm- rf)
Where, rf  is the risk free rate rm is the expected return on market r- rf   is the expected risk premium on stocks (rm- rf) is the expected risk premium on market (Brealey and Myers, 1993)

Expected Return on Investment

rm
                                                                                        Security Market Line (SML)
rf


                                                                                          Beta ()                                                                                          
Figure 1 Diagrammatic Representation of the Security Market line

In this study, it would be analyzed that whether the investments on the digital marketing is feasible in a country like Middle East.

In this study,  will be the explanatory variable and return and the securities would be the explained or the dependent variable.

We will be considering the P-value in the regression analysis in order to check whether we can accept the null hypothesis or not. We can also make use of the F statistic and t statistic. But, in this study, we will only take into account the P-value of the analysis. P-value is observed significance level at which a null hypothesis can be rejected.

In case of portfolio 1, the P-value for beta is given by 0.113379124831408. This calculated value is greater than 0.05 at 95 confidence level. It implies that we are accepting the true null hypothesis. In portfolio 1, the beta does not have influence on the return of the stocks.  It means the risk measure has no influence on the stocks. The P-value for securities is 0.211836009968191 which is also greater than 0.05 at 95 confidence level. It implies that we are accepting the true null hypothesis. Securities have no significant effect on the return of the stocks.

Similarly, in case of portfolio 2, it has been found that the P-value for beta is given by 0.301282996184625. This calculated value is greater than 0.05 at 95 confidence level. It implies that we are accepting the true null hypothesis. In portfolio 2 also, the beta has no influence on the return of the stocks.  It means the risk measure has no influence on the stocks. The P-value for securities is 0.000685838018288465 which is less than 0.05 at 95 confidence level. It implies that we are rejecting the true null hypothesis. Here, securities have significant effect on the return of the stocks.

Likewise, in case of portfolio 3, it has been found that the P-value for beta is given by 0.527901. This calculated value is greater than 0.05 at 95 confidence level. It implies that we are accepting the true null hypothesis. In portfolio 3, the beta has no influence on the return of the stocks.  The P value for securities obtained from the regression analysis in portfolio 3 is 0.266503. This is also greater than 0.05. Here also, we are accepting the null hypothesis. The securities have no significant influence on the return of the stocks.

The P-value for beta obtained from the regression analysis in portfolio 4 is found to be 0.88735.  This is obviously greater than 0.05 at 95 confidence level. It can be said that we are accepting the true null hypothesis (Type I error). The P value for securities obtained from the regression analysis in portfolio 4 is 0.202. This is also greater than 0.05.

0.817 is the P-value for beta which is generated by performing the regression analysis of portfolio 5. This is greater than 0.05 at 95 confidence level. The P value for securities obtained from the regression analysis in portfolio 4 is 0.136. This is also greater than 0.05.

Thus, it has been seen that all of these five stocks may or may not have influence of beta (), (which is a measure of risk) and securities. If the value of  increases, then (r- rf) which is the expected risk premium on stocks also rises.

Now, we will be analyzing portfolio number 200201 to 200512.
In the 1st portfolio, the P value for beta square is -2.9 which is less than 0.05. Here, we are rejecting the null hypothesis. The beta square has significant effect on the return of the stocks. However, as the value of beta square is negative, they have a negative relationship. As the value of beta square increases, the return of the stocks decreases.