Determinants of stock prices in dhaka stock exchange (dse),


Published on

International Academic Journals

  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Determinants of stock prices in dhaka stock exchange (dse),

  1. 1. European Journal of Developing Country Studies, Vol.13 2012 ISSN(paper)2668-3385 ISSN(online)2668-3687 Determinants of Stock Prices in Dhaka Stock Exchange (DSE), Bangladesh. Elizabeth C. Kalunda and Siti Haryati National University of SingaporeAbstractThe sole focus of this very research was to delineate the major determinants of stock price incase of the largest stock market in Bangladesh named as Dhaka Stock Exchange (DSE). Theresearchers have used panel data pertaining to five sectors of DSE - Food and Allied, Fueland Power, Engineering, Pharmaceuticals and Chemicals, and Healthcare sectors for theperiod 2006-2010 and used fully modified ordinary least squares method. As per the researchresult variables like - dividend, price- earnings ratio and leverage were significantdeterminant of share prices for all the aforementioned sectors. Moreover, profitability didinfluence share prices only in the case of the Food and Allied, Engineering, and Healthcaresectors respectively.Key words: Dividend, P/E ratio, leverage, profitability, fully modified ordinary least squaremethod, panel data, cointegration, Unit root test.INTRODUCTIONHumans by nature are always on the lookout for returns and prefer more to less than takinghigh risk opportunities. Equity investment can be such an investment which will yieldconsiderable amount of return without taking any outrageous or wild guess. Apart from thatfirms in need of capital for their establishment are also capitalizing this situation by issuingequity securities. All these create an environment that leads to the smooth functioning of theof the capital markets. However, the returns from equity investment are subject to varydepending upon various factors such as the performance of the particular stock, the marketimperfections, interactions between macro and micro level variables etc. With properknowledge and understanding of the impact and or value of that information always opens thedoor for outperforming the market and helps in making a hand full.In the securities market, whether the primary or the secondary market, the price of equity issignificantly influenced by a number of factors which include book value of the firm,dividend per share, earnings per share, price-earnings ratio and dividend cover (Gompers,Ishii & Metrick, 2003). The most basic factors that influence price of equity share are demandand supply factors. If most people start buying then prices move up and if people start sellingprices go down. Government policies, firm’s and industry’s performance and potentials haveeffects on demand behavior of investors, both in the primary and secondary markets. Thefactors affecting the price of an equity share can be viewed from the macro and microeconomic perspectives. Macro economic factors include politics, general economic conditions- i.e. how the economy is performing, government regulations, etc. Then there may be otherfactors like demand and supply conditions which can be influenced by the performance of thecompany and, of course, the performance of the company vis-a-vis the industry and the otherplayers in the industry. 13
  2. 2. European Journal of Developing Country Studies, Vol.13 2012 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.orgInformation of a particular stock would help investors make wise investment decisions andenable firms to enhance their market value. Therefore the impact of information on theshareholders value creation is tremendous. The factors that influence share prices could eitherbe internal factors, such as earnings, dividend, book value, etc. or external factors such asinterest rate, government regulations, foreign exchange rate, etc. Several empirical researcheshave been carried out to identify the factors that influence stock price. The pioneering workon share price determinants by Collins (1957) for United States identified dividend, net profit,operating earnings and book value as the underlying factors influencing share prices.Followed by Collins (1957), there have been other attempts to identify the determinants ofshare prices for different markets. Campbell and Shiller (1988, 1989) and Campbell (1991)attempt to break up stock price movements (returns) into the contributions of changes inexpectations about future dividends and future returns. And keeping all those view on mindthis research effort will try to shed some light on the exploration of the determinants of thestock prices in Bangladesh.LITERATURE REVIEWSeveral scholars not only from the field of finance have tried to locate the underlying reasonsfor which stock prices move. Karathanassis and Philippas (1988) pointed out dividend,retained earnings and size as the most influential factors while studying the Greek market. InKuwait earnings per share and financial leverage prove to have significant impact on themarket price of stock as per Midani (1991). In line with this view AL-Omar and AL-Mutairi(2008) showed book value per share also exerts some influence on the share price on the samemarket. Dividend yield, leverage, payout ratio and size of the firm are the factors to beassessed while making investment decisions by the investors in Pakistan [Irfan and Nishat(2002)]. On the other hand Nepalese stock showed significant reaction only due to dividend[Pradhan (2003)]. According to Sunde and Sanderson (2009) in Zimbabwe analyst reports,availability of substitutes, earnings, Government policy, investor sentiments, Lawsuits,macroeconomic fundamentals, management, market liquidity and stability, mergers andtakeovers, technical influences determines the price that investors are willing to pay for anyparticular share. In Bangladesh Khan (2009) and Uddin (2009) ion their respective studieshave identified factor such as dividend, earning per share and net asset value per share as themost influential element to cause any change share value.Zhang (2004) designed a multi-index model to determine the effect of industry, country andinternational factors on asset pricing. Byers and Groth (2000) defined the asset pricingprocess as a function utility (economic factors) and non-economic (psychic) factors. Clerc andPfister (2001) posit that monetary policy is capable of influencing asset prices in the long run.Any change in interest rates especially unanticipated change affects growth expectations andthe rates for discounting investment future cash flows. Ross’ (1976) APT model which couldbe taken as a protest of one factor model of CAPM which assumes that asset price depends 14
  3. 3. European Journal of Developing Country Studies, Vol.13 2012 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.orgonly on market factor believe that the asset price is influenced by both the market and non-market factors such as foreign exchange, inflation and unemployment rates. One of thedefects of APT in spite of its advancement of asset pricing model is that the factors to beincluded in asset pricing are unspecified. Hartone (2004) argues that a significantly positiveimpact is made on equity prices if positive earnings information occurs after negativedividend information. Also, a significantly negative impact occurs in equity pricing if positivedividend information is followed by negative earning information. Al – Tamimi (2007)identified company fundamental factors (performance of the company, a change in board ofdirectors, appointment of new management, and the creation of new assets, dividends,earnings), and external factors ( government rules and regulations, inflation, and othereconomic conditions, investor behavior, market conditions, money supply, competition,uncontrolled natural or environmental circumstances) as influencers of asset prices.Therefore it is easily grasped that various factors have emerged as determinants of shareprices for different markets namely dividend, retained earnings, size, earnings per share,dividend yield, leverage, payout ratio, book value per share, foreign exchange rate, grossdomestic product, lending interest rate, analyst reports, availability of substitutes, Governmentpolicy, investor sentiments, lawsuits, macroeconomic fundamentals, management, marketliquidity and stability, mergers and takeovers, and technical influences. For the discovery ofvarious factors that can have some impact on the market has attracted the interest of manyscholars in this part of the world but not many from Bangladesh. From Bangladesh context,only a limited a number of studies have attempted to identify the share price determinants.The empirical evidences, however, differ from study to study depending upon the choice ofthe firms, sample period and econometric methodology chosen for empirical investigation.Most of the studies undertaken have used either time-series or cross-section data. There havealso been attempts to identify the share price determinants using panel data. However, suchstudies have applied the conventional regression analysis and examined whether the data fitsinto fixed effect or random effect model. These exercises ignore the time series properties ofthe data and hence, it is likely that the results generated might be suffering from spuriousrelationship. The present study differs from the earlier empirical works in the sense that itemploys the panel unit root tests to understand the time series properties of the data andapplies the panel cointegration test to examine the long run equilibrium relationship betweenshare price and the chosen explanatory variables. Subsequently, fully modified ordinary leastsquares (FMOLS) method is employed to estimate the impact of the chosen variables on shareprices, if cointegration is established among the variables. We also attempt to identify theshare price determinants across different sectors, as they are likely to vary from one sector tothe other. The rest of the paper is organized as follows: section 3 deals with the researchmethodology followed by discussion of empirical results presented in section 4 and section 5presents the concluding remarks. 15
  4. 4. European Journal of Developing Country Studies, Vol.13 2012 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.orgECONOMETRIC METHODOLOGYPanel Cointegration TestIn this study, we use the econometric methodology proposed by Pedroni (1999) which ismeant for testing cointegration among a set of variables. This test is an extension of the Engleand Granger (1987) two step residual based procedure for testing the null hypothesis of nocointegration in the case of heterogeneous panels. The major advantage of this test is that itallows for individual member specific fixed effects, deterministic trends and slopecoefficients. The methodology involved in testing for cointegration among a set of variables isdiscussed below with respect to the model used in this study. To identify the factors thatinfluence share prices, panel regression of share prices (SP) on dividend (DPS), profitability(ROA), price earning ratio (PE) and leverage (DE) as in equation (1) is estimated. , , , , , , … … … … … … … … … .. 1where, 1,2,3, … … … … , ; N= is the number of cross-sectional units; 1,2,3, … … … … , ; T=is the time period; ’s are the slope coefficients; is the memberspecific intercept. The variables in equation (1) are integrated of the same order and said to becointegrated if , , is a stationary process; hence, testing for cointegration between SP, DPS,ROA, PE and DE involves testing for stationarity of , . The stationarity of the residualsfrom equation (1) can be tested by estimating the following auxiliary regression: , , ! " , …………………………. 2The null hypothesis 1 implies that , has unit root. In order to test the null hypothesis,Pedroni (1999) proposes two different sets of statistics, namely, the ‘within-dimension’statistics and the ‘between-dimension’ statistics. Within-dimension statistics are also knownas panel cointegration statistics and between-dimension statistics as group mean panelcointegration statistics. There are seven test statistics of which, Panel Variance, Panel Rho,Panel PP and Panel ADF statistic are within dimension statistics, while Group Rho, Group PPand Group ADF statistics are between dimension statistics. Although the null hypothesis isthe same, the alternative hypothesis is different for the two sets of statistics. The nullhypothesis relating to within dimension statistics is defined as 1 for all i against thealternative of # 1 for all i. The alternative hypothesis implies that there iscointegration among the variables of all the members of the panel. The null hypothesispertaining to between dimension statistics is defined as 1 for all i against the alternativeof # 1 for all i. In this case, unlike within dimension statistics, a common value foris not assumed. Thus, the alternative hypothesis implies that cointegration exists for at leastone individual member of the panel. The between dimension statistics, therefore, allows tomodel an additional source of potential heterogeneity across individual members of the panel.Fully Modified Ordinary Least Squares Method (FMOLS)The application of OLS method to obtain the cointegrating vector from a panel leads to biasedestimates due to endogeneity problem. However, the fully modified ordinary least squares(FMOLS) method of Pedroni (2000) accounts for heterogeneity across individual members ofthe panel, corrects for serially correlated errors and resolves the endogeneity problem; hence,the estimates are unbiased. The FMOLS produces two types of estimators, viz., pooled panel 16
  5. 5. European Journal of Developing Country Studies, Vol.13 2012 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.orgestimator and group mean panel estimator. The former is based on ‘within dimension’ of thepanel whereas the latter is based on ‘between dimension’ of the panel. In the case of pooledpanel estimator, the null hypothesis is defined as $% : % for all i against the alternative of$: ( % for all i, where % is the hypothesized common value for under the nulland is some alternative value for which is also common to all members of the panel. Inthe caseof group mean panel estimator, the null hypothesis is defined as $% : % for all i againstthe alternative of $ : ( % for all i, where are not necessarily constrained to behomogeneous across different members of the panel. Thus the group mean panel FMOLSestimator provides greater flexibility by allowing heterogeneity of the cointegratingparameters.RESULTS AND DISCUSSIONSThe study uses panel data consisting of annual time series data over the period 2006-2010 andcross section data pertaining to three sectors. The initial sample consisted of the variousDhaka Stock Exchange (DSE) sectoral indices. The final data sample has been constructedsuch that there are a minimum of 9 firms in each sector with continuous data on the selectedvariables over the sample period. The details of the final sample1 are given in Table 1.Secondary data on all the selected variables is obtained from Dhaka Stock Exchange, Dhaka-1000, Bangladesh. Table 1: Details of final sample Serial Number Name of Sectors Number of Firms 1 Food and Allied 10 2 Fuel and Power 9 3 Engineering 14 4 Pharmaceuticals and Chemicals 12 5 Healthcare 9As a measure of share price (dependent variable), average of yearly high and low share pricesis used. It is deflated by the wholesale price index. Earlier studies have identified variousfactors as share price determinants. In this study, four factors viz., dividend, profitability,price-earning ratio and leverage, are considered as possible determinants of share prices.Dividend, the return that shareholders receive on their shareholdings, is a source of regularincome to them. Dividend seeking investors wish to earn current income in the form ofdividend rather than capital appreciation, and prefer firms that pay higher dividends. Thispreference creates greater demand for higher dividend paying stocks, which triggers themarket price of such stocks. This way, dividend is expected to be positively related to shareprices. As a surrogate for dividend, dividend per share i.e. the total dividend amount paid toequity shareholders upon the number of equity shares outstanding is used. Dividend per shareis deflated by the wholesale price index. Profit after tax and preference dividend is theearnings available to the equity shareholders. Firms utilize these earnings to distributedividends to shareholders. Thus, higher the profits, higher are the dividend payments, whichin turn enhances the market price of the stocks. A positive relationship is thereby expectedbetween share prices and profitability. As a measure of profitability, the ratio of profit after 17
  6. 6. European Journal of Developing Country Studies, Vol.13 2012 ISSN(paper)2668-3385 ISSN(online)2668-3687 tax to total assets i.e. return on assets (ROA) is used. Price-earning (PE) ratio indicates the price that investors are willing to pay for the net profit per share earned by the firm. It is computed as the market price per equity share upon earnings per share of the firm. Since price-earning ratio reflects the market expectations about the firm’s future performance, a high PE ratio denotes the investors’ expectations that the firm will have higher earnings in the future. Investors would therefore be willing to pay more for the shares of firms with higher PE ratio. A positive relationship is therefore expected between share prices and price-earning ratio. Leverage measured as debt-equity ratio, indicates the proportion of a firm’s assets that is financed by debt as against equity. Raising capital via debt involves periodic interest payments on part of firms; increased use of debt by a firm would therefore result in higher interest payments and this lowers the earnings available to equity shareholders. Investors therefore generally prefer firms with lower debt. This way a negative relation between share prices and leverage is expected. Prior to testing for cointegration, the data needs to be tested for stationarity. We employ two panel unit root tests, viz., Fisher type Augmented Dickey-Fuller (Fisher-ADF) and Phillips- Perron (Fisher-PP) tests to test the unit root properties of the data. These tests accommodate individual member specific unit root process. The results of the panel unit root tests for the chosen variables, both in level and first difference are reported in table 2. Table 2: Panel Unit Root Test Results (Null Hypothesis : Series has Unit Root) Fisher ADF Test Fisher PP Test Test Sectors Level First Level First Difference Difference Share priceFood and Allied 11.81(0.34) 39.87(0.00) 10.12(0.58) 47.23(0.00)Fuel and Power 14.20(0.24) 81.24(0.00) 17.92(0.35) 58.12(0.00)Engineering 19.81(0.81) 102(0.00) 31.20(0.91) 162.12(0.00)Pharmaceuticals and Chemicals 14.29(0.78) 87.95(0.00) 17.98(0.61) 90.87(0.00)Healthcare 21.30(0.56) 69.75(0.00) 24.17(0.19) 89.76(0.00) Dividend per shareFood and Allied 15.51(0.34) 59.78(0.00) 10.12(0.28) 61.25(0.00)Food and Allied 34.30(0.20) 73.44(0.00) 29.90(0.13) 68.15(0.00)Fuel and Power 29.85(0.71) 102(0.00) 41.25(0.50) 112.52(0.00)Engineering 95.24(0.68) 27.55(0.00) 27.58(0.11) 92.89(0.00)Pharmaceuticals and Chemicals 31.31(076) 50.23(0.00) 39.19(0.10) 70.76(0.00)Healthcare 19.61(0.75) 42.87(0.00) 21.52(0.28) 13.53(0.00) Return on AssetsFood and Allied 12.21(0.44) 45.70(0.00) 50.22(0.80) 17.53(0.00)Food and Allied 52.10(0.34) 75.54(0.00) 77.72(0.20) 78.22(0.00)Fuel and Power 28.21(0.71) 92(0.00) 51.70(0.91) 62.20(0.00)Engineering 19.21(0.56) 25.35(0.00) 27.78(0.93) 95.57(0.00)Pharmaceuticals and Chemicals 32.50(0.75) 39.95(0.00) 44.78(0.56) 84.26(0.00)Healthcare 21.78(0.54) 69.45(0.00) 21.78(0.65) 32.20(0.00) Price-Earning ratioFood and Allied 71.51(0.34) 50.87(0.00) 25.20(0.58) 37.23(0.00)Food and Allied 18.50(0.24) 78.25(0.00) 24.05(0.78) 48.32(0.00) 18
  7. 7. European Journal of Developing Country Studies, Vol.13 2012 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.orgFuel and Power 31.81(0.81) 92(0.00) 51.30(0.91) 192.18(0.00)Engineering 17.30(0.30) 90.05(0.00) 15.78(0.69) 55.77(0.00)Pharmaceuticals and Chemicals 20.50(0.45) 73.75(0.00) 29.77(0.15) 99.86(0.00)Healthcare 17.51(0.04) 36.80(0.00) 16.22(0.40) 40.20(0.00) Debt-Equity ratioFood and Allied 25.95(0.89) 56.77(0.00) 40.62(0.68) 93.33(0.00)Fuel and Power 17.20(0.24) 70.20(0.00) 10.90(0.30) 50.22(0.00)Engineering 45.31(0.71) 152(0.00) 72.20(0.81) 132.10(0.00)Pharmaceuticals and Chemicals 24.30(0.72) 85.95(0.00) 18.88(0.61) 90.80(0.00)Healthcare 22.40(0.96) 29.75(0.00) 14.15(0.35) 99.06(0.00) Note: Values in (#) are P-values. As shown in table 2, the Fisher ADF test result for share price in level fails to reject the null hypothesis that share price in level is nonstationary. Similarly the result of Fisher PP test indicates that share price in level is nonstationary. Hence, we test for stationarity of share price in first difference. Both the Fisher ADF test and Fisher PP test results indicate that share price in first difference is stationary. This implies that, for all the sectors under consideration, the variable share price follows an I (1) process. Next, we examine whether the variable dividend per share is stationary. The results of both Fisher ADF and Fisher PP tests indicate that dividend per share in level is nonstationary. When tested for stationarity in first difference, the results of Fisher ADF and Fisher PP tests reject the null hypothesis that dividend per share in first difference is nonstationary. Therefore, for all the sectors, dividend per share becomes stationary upon first differencing and it follows an I (1) process. For the variable return on assets, both the Fisher ADF and Fisher PP test reveal that return on asset in level is nonstationary. In first difference form, return on assets is found to be stationary as indicated by the test results. Thus, the data pertaining to the variable return on assets, for all the sectors, follow an I (1) process. Similarly for the variables price earning ratio and debt equity ratio, the results of both Fisher ADF and Fisher PP tests fail to reject the null hypothesis that the variable in level is nonstationary. Upon first differencing, both these variables turn out to be stationary. The results thus indicate that the variables price earning ratio and debt equity ratio for all the sectors under consideration follow an I (1) process. Overall, for the chosen sectors, the variables share price, dividend per share, return on assets, price earning ratio and debt equity ratio are nonstationary in level and stationary in first difference. Since all these variables follow I (1) process, we next proceed to test whether there exists cointegration between these variables. To test for cointegration, we employ panel cointegration test proposed by Pedroni (1999), the results of which are reported in table 3. Table 3: Panel cointegration test results (Null Hypothesis : no cointegration) Name of Sectors Group ADF test statistics Food and Allied -4.89(0.00) Fuel and Power -9.12(0.01) Engineering -3-08(0.00) Pharmaceuticals and Chemicals -7.89(0.00) Healthcare -6.23(0.02) Note: Values in (#) are P-values. From table 3 it is evident that, for all the sectors under consideration, the Group ADF test statistics rejects the null hypothesis that there is no cointegration between the variables. This 19
  8. 8. European Journal of Developing Country Studies, Vol.13 2012 ISSN(paper)2668-3385 ISSN(online)2668-3687 implies that the variables share price, dividend per share, return on assets, price earning ratio and debt equity ratio are cointegrated and that there exists a long run equilibrium relationship between them. Having identified that the variables are cointegrated, we proceed to estimate the model specified in equation (1) in order to identify the share price determinants. For this purpose, we employ the group mean panel FMOLS method proposed by Pedroni (2000), and the results are reported in table 4. Table 4: Group mean panel FMOLS resultsSectors Slope CoefficientsFood and Allied 11.23(17.11)*** 2.48(3.72)*** 3.66(10.23)*** -2.54(-3.08)***Fuel and Power 46.86(9.23)*** 8.17(-6.12) 8.45(7.12)*** -1.87(-2.18)*Engineering 59.75(22.10)*** -3.59(4.26)* 6.12(3.16)*** -0.58(-7.71)***Pharmaceuticals and Chemicals 19.87(3.49)*** 2.58(-0.04) 2.98(8.72)* -1.58(-0.75)***Healthcare 24.36(5.18)*** 6.59(0.34)*** 5.38(9.72)* -0.89(-4.23)*** Note: Values in (#) are t-values. *** and * denote significance at 1% and 10% level respectively; , , and are the slope coefficients for DPS, ROA, PE and DE respectively. From the results of table 4 it is evident that the variable dividend per share is a significant determinant of share prices for all the sectors under consideration. As expected, dividend per share is positively related to share price. This means that share price would rise with an increase in dividend per share. This finding indicates that investors attach more value to those firms that pay dividends and therefore, a consistent and liberal dividend policy would enable firms enhance their market value. Similar evidence of dividend being a significant determinant of share prices is reported in Zahir and Khanna (1982), Karathanassis & Philippas (1988) and Zahir (1992). Next, we examine the influence of return on assets on share prices. As is evident from table 4, return on assets is found to significantly influence share prices in the case of Food and Allied, Engineering, and Healthcare sectors respectively. As expected, return on assets bear a positive relation with share prices. For the remaining two sectors, Fuel and Power, and Pharmaceuticals and Chemicals, return on assets does not influence share prices. This finding implies that investors do not attach much importance to profitability of a firm. Instead, what matters to the investors more is the portion of earnings that is paid to them in the form of dividend. Zahir (1992) and Somoye et al (2009) have also found evidence of profitability being a significant determinant of share prices. The variable price earning ratio is found to be a significant factor influencing share prices for all the five sectors under consideration. It is found to be positively related to share prices. This indicates that the shares with higher PE ratio will be better valued in the market as it reflects the investors’ expectations that the firm will have good prospects in the future. The finding of price earning ratio as a significant determinant of share prices is in line with Mehta and Turan (2005).The results further indicate that debt-equity ratio is a significant determinant of share prices for all the five sectors and that it exerts a negative relation with share price. This implies that as the debt content in the capital structure of a firm decreases, its share price rise and vice versa. This finding indicates 20
  9. 9. European Journal of Developing Country Studies, Vol.13 2012 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.orgthat investors prefer firms with lower debt content, since increased use of debt by a firmlowers the earnings available for equity shareholders and investors become apprehensiveabout their returns. In a nutshell, the FMOLS test results reported in table 4 reveal that thevariables dividend, price-earning ratio and leverage are significant determinants of shareprices for all the sectors under consideration. Further, profitability is found to be a significantfactor influencing share price only in the case of Food and Allied, Engineering, andHealthcare sectors respectively.CONCLUSIONThe present study attempted to identify the factors that influence share prices for the selectedsectors of Bangladeshi Stock market (only DSE is studied). Panel data pertaining to thesectorsFood and Allied, Fuel and Power, Engineering, Pharmaceuticals and Chemicals, andHealthcare sectors undertaking over the period 2006-2010 is used. The study has chosendividend, profitability, price-earning ratio and leverage as possible determinants of shareprices and employs the fully modified ordinary least squares method to identify the shareprice determinants. The results indicate that the variables dividend, price earning ratio andleverage are significant determinants of share prices for all the sectors under consideration.Further, in the case of Food and Allied, Engineering, and Healthcare sectors respectively,profitability is also found to be a factor influencing share prices.References. 1. Al – Tamimi, Hussein 2007. Factors Affecting Stock Prices in The UAE Financial Markets. Singapore Economic Review Conference. 2. Al-Omar, H. and Al-Mutairi, A. 2008. The Relationship Between the Kuwaiti Banks Share Prices and Their Attributes. Scientific Journal of King Faisal University (Humanities and Management Sciences), 9(1): 325-338. 3. Byers, S.S. and John C. Groth (2000) “Non-Economic Factors and Asset Valuation” Conference Papers on Alternative Perspective on Finance and Accounting. 4. Campbell, John Y., “A Variance Decomposition for Stock Returns,” Economic Journal, 101, (1991): 157-179. 5. Campbell, John Y., and Robert J. Shiller, “Stock Prices, Earnings, and Expected Dividends,” Journal of Finance, 43, (1988): 661-676. 6. Clerc, Laurent and Christian Pfister (2001) “The Role of Financial Factors in the Transmission of Monetary policy” Bank for International Settlements, BIS Papers No 19. 7. Collins, J. 1957. How to Study the Behavior of Bank Stocks. The Analysts Journal, 13(2): 109-113. 8. Engle, R. F. and Granger, C. W. J. 1987. Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55(2): 251-276. 9. Gompers, Paul A., Joy L. Ishii, and Andrew Metrick (2003) “Corporate Governance and Equity Prices” 21
  10. 10. European Journal of Developing Country Studies, Vol.13 2012 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org10. Hartone, J. 2004. The Recency Effect of Accounting Information. Gadjah Mada International Journal of Business, Vol. 6 No. 1.11. Irfan, C. M. and Nishat, M. 2002. Key Fundamental Factors and Long-run Price Changes in an Emerging Market - A Case Study of Karachi Stock Exchange (KSE). The Pakistan Development Review, 41(4): 517–533.12. Karathanassis, G. and Philippas, N. 1988. Estimation of bank stock price parameters and the variance components model. Applied Economics, 20(4): 497- 507.13. Khan, S. H. 2009. Determinants of Share Price Movements in Bangladesh: Dividends and Retained Earnings.14. Mehta, S. K. and Turan, M. S. 2005. Determinants of Stock Prices in India: An Empirical Study. The Journal of Indian Management and Strategy, 10(4): 37-43.15. Midani, A. 1991. Determinants of Kuwaiti Stock Prices: An Empirical Investigation of Industrial Services, and Food Company Shares.16. Pedroni, P. 1999. Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors. Oxford Bulletin of Economics and Statistics, 61: 653-670.17. Pedroni, P. 2000. Fully Modified OLS for Heterogeneous Cointegrated Panels. Advances in Econometrics, 15: 93-130.18. Pradhan, R. S. 2003. Effects of Dividends on Common Stock Prices: The Nepalese Evidence. Research in Nepalese Finance, Buddha Academic Publishers and Distributors Pvt. Ltd., Kathmandu.19. Ross, Stephen A. 1976. An Arbitrage Theory of Capital Asset Pricing. Journal of Economic Theory, 13.20. Somoye, R. O. C., Akintoye, I. R. and Oseni, J. E. 2009. Determinants of Equity Prices in the Stock Markets. International Research Journal of Finance and Economics, 30: 177-189.21. Sunde, T. and Sanderson, A. 2009. A Review of the Determinants of Share Prices. Journal of Social Sciences, 5(3): 188-192.22. Uddin, M. B. 2009. Determinants of market price of stock: A study on bank leasing and insurance companies of Bangladesh. Journal of Modern Accounting and Auditing, 5(7): 1-7.23. Zhang, X. Frank 2004. Information Uncertainty and Stock Returns. An Article Submitted to The Journal of Finance Manuscript 1149. Zahir, M. A. 1992. Factors Affecting Equity Prices in India. The Chartered Accountant, 40(9): 743-748.25. Zahir, M. A. and Khanna, Y. 1982. Determinants of Stock Prices in India. The Chartered Accountant, 30(8): 521-523. 22