The topic that I have selected for my project is the "Stock Price Variability" as exhibited by stocks from the three main sector wise players in the Pakistani stock market namely: "Banking", Cement" and "Oil".
Literature Review:
Share prices are the most important indicator readily available to the investors for their decision to invest or not in a particular share. Theories suggest that share price changes is associated with changes in fundamental variables which are relevant for share valuation like payout ratio, dividend yield, capital structure, earnings size of the firm and its growth, [Wilcox (1984), Rappoport (1986), Downs (1991)]. Linter (1956) linked dividend changes to earnings while Shapiro valuation model (1962) showed dividend streams discounted by the difference in discount rate and growth in dividend should be equal to share price. This predicts direct relation between pay out ratio and the price -earning multiple. Conversely it means that there is an inverse relation between pay out ratio and share price changes. Several event-based studies established direct relation between share price changes and either earnings or dividend changes (Ball and Brown 1968: Baskin 1989). Sharpe (1964) and Hamada (1972) suggested direct relation between share price changes and capital structure. Beaver, Kettler and Sholes (1970) showed that firms appear to pay less of their earnings if firms have higher earning volatility. This suggests payout ratio as relevant factor for share price changes. Investigations of share price changes appear to yield evidence that changes in fundamental variable(s) should jointly bring about changes in share prices both in developed and emerging markets. However, the actual fundamental factors found to be relevant may vary from market to market. For example, changes in asset growth of firms are significant in the case of Japanese shares while earnings appear to be universally a relevant factor (Ariff et al., 1994). However, it is widely agreed that a set of fundamental variables as suggested by individual theories is no doubt relevant as possible factors affecting share price changes in the short and the long-run (Ariff and Khan, 2000).
The link between fundamental factors and share prices changes has been extensively investigated over short horizons but only few studies attempted to model it over lengthy periods of time. Studies over short windows commonly apply cross-sectional tests using event-based research methodology. The cases of studies examining this relation cross-sectional or inter-temporally are few, and these have one common feature i.e., the fundamental factors used in a specific study are either one or two although there is a long list of fundamental factors. Furthermore, while price revisions at the time of announcements of price relevant disclosures are valid as announcement effects shown over short horizons, it is equally important to test the effect over a lengthier period of time using data over several years as measure of the variables (Ariff and Khan, 2000). Black and Sholes (1973) support the idea, that the value of security will be higher; the higher is the volatility of security's return. The relation between dividend and earning follows that the greater the volatility of earnings of a firm the less is the likelihood of dividend yield being changed by the firm's management. Hence earnings volatility is directly related to share price volatility.
Another relevant factor in affecting the share prices is the capital structure of the firm. The level of debt financing by the firm has impact on the value of firm's assets. Hamada (1972) and Sharpe (1964) specify their theories regarding the capital structure. A high-risk firm (a firm with debt) must generate high return consistent with the investor's expected return. It follows that with higher debt firm should have greater rate of change in its share price. Hence capital structure (DA as debt to asset ratio) changes must be directly related to the share price volatility. Modigliani and Miller (1958) emphasized that in competitive capital markets the value of a firm is independent of its financial structure. But if markets are imperfect Authors are MPhil research fellow at Applied Economics Research Centre, University of Karachi and Professor and Chairman, Department of Economics and Finance, Institute of Business Administration, (transaction cost, taxes, informational asymmetry, agency cost etc.) then capital structure matters and influences the share prices.
Size of a firm does have effect on the valuation of the firm assets. Smaller stocks have higher average returns. Introduction of size, as a multiplicative term to dividend, provides a significant improvement in the explanation of share prices (Karathanassis and Philiappas, 1988). The size of the firm if captured through total capital employed, is expected to influence the share prices positively as large firms are better diversified than small ones and thus are less risky (Benishy, 1961). Atiase (1985) showed that as the size of the firm increases, their share price volatility declines.
(Ariff et al, 1994) established the joint linear effect of these six variables for the three markets using data relating to samples of firms over 16 or more years in Japan, Malaysia and Singapore. In general, the six variables are significantly related to share price volatility in the three markets although some were not significant in particular markets. In the case of more analytically intensive Japanese market, changes in the fundamental factors accounted for two-fifth of the variation in share price volatility The same was not the case in the less analytically intensive developing markets of Malaysia and Singapore. Obviously, larger portions of price variation appear not to be explained by the variation in the six firm-specific fundamental variables in the less developing markets. Perhaps, prices in the latter two markets, it may be suggested, are more responsive to macroeconomic factors, which were not included in the cross-sectional tests. Alternatively, investors in such markets are not pricing the shares on the basis of fundamental factors, perhaps preferring to price on speculative information. The US Investors are known to price the securities much more on the basis of analysis made widely available by the financial analyst community and the mass media. In another study (Ariff, 2000) on a sample of hundred homogenous industrial firms, four out of these six factors were found significant and explained two-third of share price volatility over a window of twenty years for US market.
Karachi stock exchange is an important emerging capital market of the region among the developing countries. KSE is termed as high-risk high return market where investors seek high-risk premium (Nishat, 1999). Few studies have attempted to analyze the long run behavior of the market (Nishat, 1991) and no work has been done to explore the fundamental variables affecting the share prices. Factors affecting share prices has been identified for the short run (Nishat, 1995; Nishat and Saghir, 1991). It is also important to study these factors in the Pakistani context after the introduction of reforms, which emphasized more towards openness to foreign investor and competition. Under reforms emphasis has been on information disclosure by companies, documentation, increasing role of brokerage houses and investment companies which provide more feedback to investor.
Introduction to Sectors
Cement:
This has been a much neglected sector until a few years. This has been due to the fact that the government has neglected the construction industry altogether. Apart from that it is one of the highest capital investment industries in Pakistan. That is the reason why the major companies are all withheld by the big conglomerates of Pakistan. Cement sector over the years has evolved into a very major player in the Pakistani stock market. As was made clear in the Afghan war, earthquake 2005, construction of bhasha and kala bagh dams to name a few. The stock market saw heavy trading after all these incidents as the market speculation regarding the demand of cement shot up significantly. Over the past three four years the volume of trading for the cement stocks has been tremendously high contributing heavily to the everyday trading. The outlook for cement sector seems positive as the demand of cement is expected to grow at sustainable pace.
Commercial Banks:
In Pakistan's booming stock market, the listed commercial banks have performed extremely well and that is why banking stocks are amongst the investors' top picks. Listed commercial banking sector posted a superb 149 per cent return (as measured by adjusted market capitalization excluding ABL and UBL) during the year 2005 with two leading banks MCB and NBP posted a handsome gain of 258 per cent and 200 per cent respectively. With the listing of two new commercial banks, namely Allied Bank (ABL) and United Bank (UBL), in 2005, the total number of listed commercial bank has now reached 20. These 20 banks have 75 per cent and 82 per cent share in the total advances and deposits, respectively, of Pakistan's total commercial banking industry. Moreover, the share of commercial banks in KSE's market capitalization is also rising and currently stands at around 19 per cent compared to 9 per cent, 2 years back.
Due to the above mentioned statistics we can easily conclude that the importance of commercial banks in the stock market is growing by leaps and bounds with every passing year. The major players that control the overall output of the stock market come from this very sector.
Fuel & Energy:
At the moment, indigenous hydrocarbon production is highly skewed towards gas which accounts for 90 percent of the combined oil and gas production in the country. While the domestic gas production is sufficient to meet the local consumption, the local oil production is hardly 22 percent of the total consumption of the country. To fill the demand supply gap, Pakistan imported $4.2bn worth of crude and refined oil during FY05.
The Karachi Stock Exchange (KSE) record-breaking spree has been largely inspired by oil and gas shares' purchases by foreign and local funds raising the trading volumes and market capitalization figures to new heights.
Commenting on the mind-boggling rises, stocks dealers, say that there is still a room for growth in the energy's bellwether stocks, which have helped in crossing the all-important crucial benchmark of 10000 points in 2005.
All this is attributed to lucrative prices of oil and gas shares, acceleration in the privatization process, higher payouts and encouraging economic indicators.
Apart from all these factors the influence of this sector can be judged by the fact that the stock market crash in 2005 was lead by the artificial increase in prices of OGDC's stocks based on its privatization, new discoveries and favorable earnings. Other players that contributed included PPL as well thus making the importance and effect of this sector loud and clear. PSO was also a start performer. HUBCO could not have been ignored as well.
Main Objective
The underlying objective of my research is to test the significance of the coefficients of determinants of the sector wise stock price variability in Pakistan i.e. to identify the factors affecting stock prices. I looked at four different variables which I gradually reduced after running regressions which basically determined the significance of these variables with respect to changes in the stock prices. Out of all these variables I chose the most significant variables for my final model.
Model:
My initial equation was as follows:
Stock Price Variability = α + β1averagestockprice + β2activity/turnoverofstock + β3pricetoearningratio + β4earningpershare
Independent variables: average stock price, earning per share, activity/turnover of the stock and price to earning ratio.
Dependent variable: stock price variability
Explanation of Variables:
Stock Price:
The expected price of a stock has a positive affect on the price of the stock. It is an important factor in determining the overall variability in a particular stock.
Earnings per Share:
Any news about the increase or decrease has a positive or a negative effect on the stock price respectively. Investors tend to take this factor into account while deciding their investments thus drawing the stock price up and down.
Activity/Turnover of Stock:
Studies do indicate that stocks which have a higher turnover tend to exhibit greater price variability as compared to those that have a lower turnover, thus, making this an important factor to check the volatility in stock prices.
Price to Earning Ratio:
It is of fundamental importance to the investors as a great deal rests on this. Market makers also take this to be a source to invest or divest their investment in a particular stock.
Hypothesis:
My hypothesis for all the variables was stated as:
H0: ßi = 0 (relationship is not significant)
H1: ßi ≠0 (relationship is significant)
Methodology:
Source: All the data was taken from the business recorder website.
Time Frame: The time frame used was from the year 1998 till 2005. This was mainly due to the constraint of obtaining the data. The website mentioned above had only eight years of data available on it.
Calculation: Data was tested through running multiple regressions to determine the relationship of all the variables with the stock price variability in KSE. Further on, for the purpose of econometric analysis the problem of multicollinearity was detected and removed successfully.
Data Analysis:
To make the data seem more viable for the study and comparison with my other colleagues the three sectors (cement, banking and oil and gas) under study were not segregated from each other. The data was taken as a whole eliminating the difference in the sectors. The first and the foremost steps were to check the data for significance of different variables. Econometric study involved checking the data for multicollinearity as there was some evidence of it.
The price volatility in each of the 15 stocks was taken to be the dependent variable. Its calculation was done on the basis of the difference between the highest and the lowest price of the stock. It was done in order to give us a range in which the price has fluctuated for the eighth years under study.
The following independent variables were taken in order to test the inferential and econometric models.
Earning per share was taken directly from the data source for the eight year period.
The price to earning ratio of the stocks was measured by dividing the annual average prices by their respective earning per share.
Activity or turnover of the stock was taken directly from the data source. It exhibits the total shares traded annually.
Average prices were taken directly from the data source measured by the difference of the highest and the lowest prices for a given year divided by two.
The results are as follows:
The first step was to check the significance of the model by running regressions on it. This led to the reduction of those variables which were not significant and the model was reduced.
The R2 for the then reduced model comes out to be 0.976 showing that it is a highly significant model. The variables taken explain the variability in the stock prices to a large extent.
However one problem that the data set exhibited was multicollinearity. So it was checked for that purpose by constructing a correlation matrix. The variables with correlation ranging between 0.8 - 1.0 were dropped and the regression was performed on the remaining variables. The remedial action took to the making of three models out of which the most appropriate was used. The model showed an R2 of 0.696 which was due to the earning per share for the year 2005. The F statistic was also very high at 29 thus verifying the high significance of the model.
The results indicate that the average price is the least likely variable to cause any significant change in the stock prices. If it was not for this very variable the results might have been different and the model might have been able to explain more based on the other three variables. The results exhibited by this support the empirical evidence of prices not normally pushing up stock prices.
The strongest relationship was exhibited by the earning per share. It stems from the fact that any indication of an increase in a companies earning will make the prices go up.
Same can be said about the turnover of the stock. The larger the volumes traded the more will be the room for variability in a stock's price at any given point in time.
The price to earning ratio also holds some significance as they are calculated directly by the earning per share. Thus they also reflect the changes that are caused by the earning per share.
Comparison with my Colleagues:
The mere basis of this project is the comparison between my project and that of my two colleagues. The results were as follows:
Ms.Sahar Ms. Maria Ms. Hajra
R2= 0.968 R2= 0.999 R2= 0.976
After the Removal of Multicollinearity
Ms.Sahar Ms. Maria Ms. Hajra
R2= 1 R2= 0.0957 R2= 0.696
The above results explain the relationships between the independent and the dependant variables taken by all three of us. But the fact still remains that my model is the least significant as compared to the other two. The reason being that the cement sector taken in my study has been in losses for half the years taken. The model presented by Ms. Sahar takes into account the stock market crash that took place in 2005. The last year values are representing a turning point in the values of the said stocks. Similarly results exhibited by Ms. Maria's model are emanating from the high turnover stock. I have mentioned very clearly in my results that activity of a stock plays a large part in the variability. Thus her results support this theory very well also making the model the best out of the three. Similarly Ms. Sahar's model also surpasses the high significance barriers owing to the selection of those stocks that lead to the stock market doom last year.
However my results cannot be ignored as the results show that although I took to study only three sectors out of the total sectors at the Karachi stock exchange they are explaining more than half of the variability in the stock prices. There performance over the past eighth years has lead to massive gains and losses for the KSE as explained by my introduction to the sectors.
Conclusion:
All said and done a lot still remains to be found out about the true reasons for the variability in stock prices. Apart from the variables taken in this study there are certain factors whose significance cannot be tested numerically but there influence has and will always be there to change the stock prices causing volatility. Examples pertinent to the Pakistani stock market that have over the years caused unexplained variations in the prices of stocks are badla financing, control by brokers, speculation , false company information, price manipulation, border tensions with India etc. to name a few.
