INTRODUCTION

Many empirical studies have been done to show the predictability of stock returns and plenty of evidence supports that security returns are predictable.

Purpose of this paper and summary of paper

DIVIDEND, DIVIDEND YIELD AND STOCK RETURNS

A company makes use of the profit or surplus it earns in two major ways: Firstly, It can reinvest the profits in the business which is normally termed as retained earnings where company has the advantage of investing its surplus in the positive Net Present Value (NPV) projects. Secondly, it can either distribute the excess profits to the shareholders in the form of dividends or make use of that profit in doing the stock repurchases. Most of the companies in the present scenario are retaining a fraction of their total earnings and are distributing the remainder to the shareholders in the form of dividend. Some terms which are used throughout the paper are discussed.

DIVIDEND

Dividend is a taxable payment which is declared by the management board of a corporation for the class of its shareholders. It is paid to the shareholders out of the corporate profits usually quarterly earnings or retained earnings either in the form of cash, stock or property. A company usually announces quarterly and annually dividends based on a fixed schedule but sometimes announces the dividend at any time in the year and may refer it to special dividend. The allocation of a dividend is done as a fixed amount per shares called dividend per share, which results in shareholder receiving a dividend in regard to his/her shareholding pattern.

DIVIDEND YIELD

Dividend yield is a rate of return an investor or a shareholder is getting from each buck invested in equity. Dividend yield ratio is a measure of calculating how much a corporation is spending on dividends each year comparative to its share price. It is calculated by dividing the company’s annual dividend payments by its market capitalisation or by dividing dividend per share by the price per share.

SECURITY

REVIEW OF LITERATURE

A detailed literature review is carried out to focus on the existing research on the subject of predictability of stock returns. Articles published in the professional journals, books, reports and other sourced information from the internet, particularly from the main professional bodies in UK, US and other emerging economies are highlighted.

There is extensive literature available on this topic as various empirical studies have been done to show the predictability of stock returns. The time series behaviour of dividend yield has been observed by many researchers over the last twenty five years and extensive support for using the dividend yield as a prime ratio for measuring expected security returns is provided. Michael S. Rozeff (1984) shows evidence that equity risk premium is forecasted by dividend yield. Among various methods of calculating the equity risk premium, the method of realised market rates of return, Gordon- Shapiro constant growth model and spreads between different bonds classes are the popular ones. He used the constant growth model also known as Gordon growth model and gave it a new twist suggesting that the dividend yield on stock as an approximation of equity risk premium would be very much helpful to look at. Generally the model suggests that the expected rate of return on stock market is equal to a variable of dividend yield on the market plus the predicted growth rate of dividends. He wrote the model as:

RSTK = DYLD (1+GROW) + GROW (2)

Where,

RSTK = Expected rate of return (capital gains plus dividend yield) of the stock market

DYLD = Current dividend yield on the market

GROW = Nominal expected growth rate of the market dividends

Equation for measuring the equity risk premium (RPE) is observed by subtracting out the nominal riskless rate, RBILL (expected rate of return on treasury bills)

RPE = DYLD (1+GROW) + GROW – RBILL (3)

Some very useful characteristics were observed in this view as attention is being driven mainly on two major aspects of expected market return, the yield and growth, but the drawback in the model was that the predicted growth rate of dividend was unobservable due to which the risk premium could not be measured by using the model without estimating the predicted long-run growth rate of dividends. Although the model gives the suggestion that the variation in the expected stock returns should be captured by the dividend yields.

Fama and French (1988) examined the ability of dividend yields to predict stock returns. The dividend / price ratios i.e. dividend yield is used to project the returns on the equal weighted and value weighted portfolios consisting stocks of New York Stock Exchange (NYSE) and having the holding period i.e. return horizons from one month to four years. Their result supports existing evidence that the predictable component of return is a small fraction of short horizon return variances. By using overlapping multiple-year horizon returns, very strong evidence is provided by them in support of the dividend yield effect. They offered evidence that predictability power increases with the return horizon. Less than 5% of monthly or quarterly return variances are explained by performing regression of returns on yields. The discount-rate effect has remained the focus point for the explanation in their studies which suggest that the counter adjustments of security prices are set off by the shock to the discount rates and returns expected. Fama and French (1988) found out that there is an increase in the explanatory power of dividend yield in the time horizon of the returns. They also noticed a massive high of 64% in the R2 over the horizon of 4 years.

Studies over the span of past twenty years have shown that some econometric difficulty exists in the test involving long holding period (horizons) return and hence resulted in the biasness towards the rejection of null hypothesis. Stambaugh (1986) pointed out another problem that the explanatory variable or the independent variable “Dividend yield” contains a level of price that already appear in regressand and therefore it may not be properly a externally originating variable. The error-in-variable problem pointed out by Fama and French (1988) is due to the fact that the information about the prediction of future returns and dividend growth is already present in the yield. It might actually result in the bias down towards the regression coefficient in the regression of dividend yield.

Some issues arising out of these researches were addressed by Hodrick (1992), where he explored the statistical properties of three methodologies in monte calro experiments and used them to carry out conclusion and measurement in long run forecasting experiment along with an application to dividend yields as predictor variable for stock returns. He uses Ordinary Least Square (OLS) regression which is used by Fama and French (1988b) as his prime methodology along with Vector autoregression (VAR) as second methodology which is used in Campbell and Shiller (1988), Kandel and Stambaugh (1988) and Campbell (1991).

By establishing a link between long and short run predictability of return, he demonstrated that consistency exist only between a reasonable large amount of long horizon predictability and small amount of short horizon predictability. For the sample of 1952-1987, the strong support has been provided by the VAR test for the explanatory power of one month ahead returns. The significant constant changes in expected stock returns are forecasted by the changes dividend