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Table 1 shows a broad description of the summary statistics of the variables used in the study.

It shows the statistical means, standard deviation, median, and standard error. According to Allen and Rachim (1996), if it is assumed that stock prices follow a normal distribution pattern and ignoring the effect of firm’s going ex-dividend, the standard deviation of stock market returns equivalent to the measured volatility of this study. This can be done using the formula derived by Parkinson (1980) in line with Baskin (1989), here, the mean of price volatility 0.2940, is multiplied by the constant 0.6008 which gives a result of 17.66%. This is inline with the results of Allen and Rachim (1996) on Australian firms with US firms of 36.9%.

Table 2 shows the correlation amongst the variables utilized for the study. From the table, it can be seen that the correlation between price volatility and dividend yield is negative (-0.2583) as expected, this is in line with that of Baskin(1989) which was -0.643, but it is in contrast with that of Allen and Rachim (1996) which was positive (0.006). Also the correlation between price volatility and dividend payout is negative (-0.4446) as expected and it is in line with the correlation in both Baskin’s (1989) which was -0.542 and Allen and Rachim (1996)which was -0.210. The correlation table also shows a high correlation between dividend yield and payout with values 0.6684 (approximately 70%), this raises questions as there is the possibility of multicollinearity which could be a potential problem. Multicollinearity problem exist when the correlation between two independent variables is equal to or greater than 70% (Drury, 2008). There is therefore the need for the inclusion of the control variables in the regression equation to see if there would be changes.

 We will go in the field with our made questionnaire and request the people to fill the data. Special focus would be given to the people who belongs to the finance department of a company and should belongs to upper management because they are the only one who can give a clear picture of the requirements of financial regulatory.

Limitation of the data

Time constrain is the biggest limitation according to my analysis because it relates to the personal belonging of a person. We think that 10% of the people fulfill their questionnaire without giving proper attention and study due to the time constrain factor. It is a small chance of error and would not impact the end result indeed.

CHAPTER-4

ANALYSIS AND DISCUSSION

Quantitative Analytical Framework

Before leap over the quantitative analysis section, there is a need to show the tools and techniques used to quantifying the analysis.

The relationship between ordinary stock price volatility and dividend policy has been analyzed utilizing multiple least square regressions.

Benchmarking to Lintner (1956)

There are two key results in Lintner (1956). First, corporate dividend decisions were made very conservatively. Second, the starting point for most payout decisions was the payout ratio (i.e., dividends as a proportion of earnings). Combining these two key features, Lintner’s empirical model of dividend policy is simple: dividends per share equal a coefficient times the difference between the target dividend payout and lagged dividends per share. The coefficient is less than one because it reflects a “partial adjustment” (dividend conservatism implies that dividends per share do not move.