Factors Affecting Share Prices

inter topicist look into diary of finance and political economic system ISSN 1450-2887 libe set 30 (2009) Eurojournals Publishing, Inc. 2009 http//www. eurojournals. com/finance. htm Determinants of Equity harms in the demarcation securities industrys Somoye, Russell Olukayode Christopher Dept. of Banking & finance, power of Management Science Olabisi Onabanjo University, Ago Iwoye, Nigeria P. O. Box 1104 Ijebu-Ode, Ijebu-Ode, Ogun State, Nigeria electronic mail emailprotected com Akintoye, Ishola Rufus Dept. of Accounting, Faculty of Management Science Olabisi Onabanjo University, Ago Iwoye, Nigeria E-mail emailprotected com Oseni, Jimoh Ezekiel Dept. f Banking and Finance, Faculty of Management Science Olabisi Onabanjo University, Ago Iwoye, Nigeria E-mail emailprotected com Abstract Brav & Heaton (2003) alleges trade indefinity (a situation where it is impossible to determine whether an addition is address- workively or inefficiently outlayd) in the seam mart. Ka ng (2008) betoken that data-based tests of running(a) incontr e very(prenominal)placetible value mock ups betoken presence of mis set in plus pricing. asset pricing is considered efficient if the asset expenditure reflects all available food foodstuff nurture to the force out no informed trader apprize outperform the grocery store and / or the untaught trader.This reckon examined the extent to which nigh nurture instruments or market indices affect the deport price. A instance specify by Al-Tamimi (2007) was physical exertion to retro form the multivariates ( inventory prices, net income per sh atomic human action 18, gross domestic point of intersection, loaning c be group regulate and inappropriate exchange tell) by and by testing for multicollinarity among the mugwump variables. The multicollinarity test revealed genuinely pixilated correlation coefficient between gross domestic product and oil colour(a) oil price, gross domestic p roduct and foreign exchange tramp, alter interest rank and inflation rate.All the variables gain commanding correlation to assembly line prices with the barelyion of change interest rate and foreign exchange rate. The outcomes of the study agree with earlier studies by Udegbunam and Eriki (2001) Ibrahim (2003) and Chaudhuri and Smiles (2004). This study has enriched the live oning literary works art object it would help constitution makers who argon interested in deploying instruments of m startary policy and opposite frugal indices for the exploitation of the detonating device market. Keywords monetary fund prices, CAPM, baby-sits, coefficient, efficient, job market. worldwide research daybook of Finance and economic science egression 30 (2009) 78 1. 0. Introduction The price of a commodity, the economist makes us to believe is hardened by the forces of demand and planning in a indigent deliverance. level off if we accept the economists view, what fact ors enamor demand and supply behavior? Price? Yes, only if non all the fourth dimension, at least on that point be few otherwise factors. In the securities market, whether the primary or the secondary market, the price of justness is really influenced by a number of factors which include view as hold dear of the sloshed, dividend per mete out, earnings per sh atomic number 18, price earning proportionality and dividend cover (Gompers, Ishii & Metrick, 2003).The close to basic factors that influence price of beauteousness sh be ar demand and supply factors. If virtually mass start buying then prices move up and if people start selling prices go down. Government policies, firms and persistences performance and potentials wipe out set up on demand behaviour of investors, both in the primary and secondary markets. The factors affecting the price of an fair-mindedness share underside be viewed from the macro and micro economic perspectives. macro economic facto rs include politics, general economic conditions i. e. how the economy is performing, government regulations, etc.Then in that location may be other factors interchangeable demand and supply conditions which can be influenced by the performance of the company and, of course, the performance of the company twin the industry and the other players in the industry. In a study of the meeting of dividend and earnings on striving prices, Hartone (2004) argues that a operatively positive partake is made on honor prices if positive earnings information occurs after ostracise dividend information. Also, a evidentially banish impact occurs in candor pricing if positive dividend information is followed by negative earning information.Docking and Koch (2005) discovers that in that respect is a direct relationship between dividend announcement and rectitude price behavior. Al-Qenae, Li & Wearing (2002) in their study of the effects of earning (micro-economic factor), inflation and interest rate (macro-economic factors) on the stock prices on the Kuwait Stock Exchange, discover that the macro-economic factors significantly impact stock prices negatively. A previous study by Udegbunam and Eriki (2001) of the Nigerian majuscule market also shows that inflation is inversely correlated to stock market price behaviour.A number of postures actual for asset pricing are 2 variable patterns. For instance the Capital asset pricing model (CAPM) developed by Sharpe (1964) considers the risk-free coming back and volatility of the risk-free soften to market return as the determinants of asset price. asset price as described by CAPM is additively related to the twain self-reliant variables. around(prenominal) studies have concluded that over the years assets were being underpriced (Smith, 1977 Loderer, Sheehan & Kadlec, 1991) and this raises the question of the adequacy of the various asset pricing models to ensure efficient asset pricing.Brav & Heaton (2003) alleges market indeterminacy, a situation where it is impossible to determine whether an asset is efficiently or inefficiently priced. Kang (2008) found that empirical tests of linear asset pricing models show presence of mispricing in asset pricing. plus pricing is considered efficient if the asset price reflects all available market information to the extent no informed trader can outperform the market and / or the uninformed trader. This study aims at examining the extent to which some information factors or market indices affect the stock price.The rest of the paper is designed as follows portion 2 reviews literature on factors influencing asset prices, effects of inefficient asset pricing and some of the actual asset pricing techniques. Section 3 produces the data and the sources, the data restructuring and the model employ for data analysis part Section 4 discussed and interpret the results of the data analysis. Lastly, section 4 is the conclusion. 2. 0. conceptual Frame work and Literature Review 2. 1. Conceptual Framework Several attempts have been made to identify or study the factors that affect asset prices.Some researchers have also tried to determine the correlation between selected factors (internal and external, 179 world-wide look into journal of Finance and economics Issue 30 (2009) market and non-market factors, economic and non-economic factors) and asset prices. The outcomes of the studies vary depending on the scope of the study, the assets and factors examined. Zhang (2004) designed a multi-index model to determine the effect of industry, country and international factors on asset pricing. Byers and Groth (2000) defined the asset pricing process as a single- surveyd function improvement (economic factors) and non-economic (psychic) factors.Clerc and Pfister (2001) posit that mo finalary policy is capable of influencing asset prices in the gigantic run. Any change in interest rates especially unforeseen change affects growth e xpectations and the rates for tax write-offing investment prox interchange gos. Ross (1977) wedded(predicate) model which could be taken as a protest of one factor model of CAPM which assumes that asset price depends only 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 the defects of ingenious in break of its advancement of asset pricing model is that the factors to be included in asset pricing are unspecified. Al Tamimi (2007) identified company primitive factors (performance of the company, a change in board of directors, appointment of new management, and the foundation garment of new assets, dividends, earnings), and external factors ( government rules and regulations, inflation, and other economic conditions, investor behavior, market conditions, capital of the United States supply, competition, uncontrolled natural or environmental circumstances ) as influencers of asset prices.He developed a simple obsession model to measure the coefficients of correlation between the independent and dependent variables. SP = f (EPS, DPS, OL, gross domestic product, CPI, INT, MS) Where, SP Stock price EPS Earnings per share DPS Dividend per share OL Oil price gross domestic product Gross domestic product CPI Consumer price index INT Interest rate and MS money supply. He discovered that the firms fundamental factors exercise the most significant impact on stock prices.The EPS was found to be the most influencing factor over the market. Studying the effects of the Iraq war on US fiscal markets, Rigobon and Sack (2004) discovered that increases in war risk ca employ declines in Treasury yields and candour prices, a widening of lower-grade corporate spreads, a make up in the dollar, and a rise in oil prices. A positive correlation exists between the price of oil and war. They argue that war has a significant impact on the oil price.Tymoigne (2002) argue that in the fiscal market, banking convention and financial convention work to spring upher to fix the assets market prices. According to him the financial convention creates a speculative sen seasonnt of whether capitalists are much prone to sell, or to buy assets while the banking convention determines the state of credit as evidenced by the confidence of the banking sphere and dexterity of investors accessing credit leverage for asset acquisition purpose.He concluded that conventions do not determine asset-price, it is the law of supply and demand that does so, conventionsonly influence the behaviors of financial actors Inflation as an external factor exerts a very significant negative influence on the stock prices in Nigeria (Zhao,1999 & Udegbunam and Eriki, 2001). Factors affecting asset prices are numerous and inexhaustible. The factors can be categorized into firm, industry, country and international or market and non-market factors, and economic and noneconom ic factors. All the factors can be summarized into two classes micro and macro factors.Factors in each(prenominal) class of the classification are inexhaustible. For instance, the firm factors include, ownership structure, management quality, labour force quality, earnings ratios, dividend giftments, net sacred scripture take account, etc. have impact on the investors pricing decision. Molodovsky (1995) believes that dividends are the hard core of stock pass judgment. The pry of any asset equals the puzzle apprize of all cash flows of the asset. 2. 2. Effects Of Inefficient summation set Inefficient asset pricing could be a accelerator to inefficient resource allocation among competing productive investment opportunities.Underpricing can table service as positive signal to the market (Giammariano & Lewis, 1989) to compensate the uninformed and get them to participate in the new International Research ledger of Finance and economics Issue 30 (2009) 180 offer (Rock, 19 86 Allen & Faulhaber, 1989 Grinblatt & Hwang, 1989 Welch, 1989). The market is information-sensitive. Prices list to take a declining trend a few(prenominal) days to the release of a firms new offer and the price recovery starts few days after the completion of the offer, especially if he offer is in full subscribed (Barclay and Litzenberger, 1988). Easley, Hridkjaer and OHara (2001) agree that market is information sensitive at least to the extent that private (insider) information affect asset returns and rede that it should not be ignored for efficient asset pricing. The firms beta ratios, its market honor to intensity hold dear, its current price to earnings ratio and the diachronic growth rate in earning per share are identified by Moore & Beltz (2002) as possessing strong influence on the rectitude price of the firm.They also argue that the identified factors have varying effects on the price and the effects vary from clipping to time, sector to sector and even from firm to firm within the same industry. For instance, they argue that fairness prices of individual firm in heavy industries (chemical, petroleum, metal and manufacturing) are wholly influenced by the firms beta and market to book value while firms in the technology sector are influenced by the historical growth rate in earning per share as well as beta and market to book value ratio.The equity price in transportation industry is affected by beta and price to earning ratio. Though, Moore & Beltz (2002) constructed a tree relating the impact of each identified factors in each of the selected model yet did not construct a model that could be utilize in assessing direct impact of the identified factors on the equity price. Asset pricing could be a challenge.Hordahl & Packer (2006) argue that a unaccented understanding of the assets stochastic discount factor and upcoming payoffs is necessary to understand the factors that determine the price of an asset. Unfortunately, only Governm ent instruments bear their stochastic discount factor in advance while the futurity payoffs are not observable directly entirely could be come ind from some other data. Corwin (2003 identifies uncertainty and asymmetric information as a strong influence on the firms equity pricing and as a matter of fact lead to underpriced instrument.In the light of the preceding literature review, many factors both micro and macro-economics, have impact on equity pricing in the stock market, the impact differs from firm to firm, industry to industry, economy to economy and from time to time, but one comforting conclusion is that most of the factors appear to have the same behaviour regardless(prenominal) of time, industry or firm constraints.For instance, increase inflation and interest rates, declining dividends, earnings, poor management cave in negative impact on equity pricing and vice-versa 2. 3. Asset determine Techniques on that point are several asset pricing models aside from CAPM and APT which are both linear model. A few of the available (non-linear) asset pricing techniques are reviewed in this section. 2. 3. 1. Residual Income valuation This is one of the oldest rating model with a trace to the work of Preinreich (1938).The valuation model discounts the future evaluate dividends and potential value of shareholders funds to the present value, giving effect to a proposition that the price of equity can be derived from the present value of all future dividends. Lo and Lys (2000) reviewed the Olhson influence (OM) developed in by Ohlson (1995) and which has been acknowledged with wide acceptance (Joos & Zhdanov, 2007 Chen & Zhao, 2008). The OM provides a platform for the empirical test of the residual income valuation (RIV).Lo and Lys (2000) defined RIV as RIV = Pt = ? R-r Et (dt+r) Where Pt is defined as the equity market price at time t, dt represents dividends at the end of time t, R is the unity plus the discount rate (r) and Et is the expectation fac tor at time t. The RIV from the present value of expected dividend is based on the assumptions that (i) the method of accounting dodge meets the clean spare relation i. e. 181 International Research Journal of Finance and frugals Issue 30 (2009) To derive RIV from PVED, two spare assumptions are made.First, an accounting system that satisfies a clean surplus relation (CSR) is assumed bt = bt-1 + xt dt, bt represents the book value of equity at time t, xt represents the earnings at time t, and (ii) it is assumed that the book value of equity would grow at a rate less than R, that is R-r Et (bt+r) ) 0 The assumptions form the basis to argue that the present value of expected dividend is a function of both the book value and discounted expected ab pattern earnings.In that case RIV signifying the price of the asset can be stated thus Pt = bt +? t=1 R-r Et (xat+r) Where xat = xt rbt-1. leavening RIV empirically could be a contention on the expound that it has only one sided a ssumption asset price is a function present value of future dividends. A rejection of the hypothesis when tested empirically may arouse dissenting voices from researchers who had believed in the efficacy of the model. In fact, lee (2006) expressed the view that residual income valuation model provides a fall in valuation than the dividend model.John and Williams (1985), and Miller and Rock (1985), argue that dividend is a communication cats-paw for the firm to pass information to the market in the event of information asymmetry which implies that there is a positive correlation between information asymmetry and a firms dividend policy. 2. 3. 2. Economic Valuation feigning This model traced to Tully (2000) is developed to recognize economic attains as against the use of book sugar in the valuation of asset.The model builds on the expound of profit maximization by owners of the firm and the profit is not to be restricted to book value, rather it covers the opportunity cost of n ot put in profitable projects. Economical profit is differentiated from the book profit as the difference from revenues and economical costs (i. e. book costs plus opportunity cost of failure to invest in profitable project. The book profit can be defined as revenue less costs while economic profit is defined as make sense revenue from investment less cost of capital.Economic profit is taller than normal book profit because of the opportunity cost considered in the former. thither are two approaches to the estimation of economic value added (Koller, Goedhart & Wessels, 2005 Jennergren, 2008). The first is NOPLAT less capital charge (i. e. WACC multiplied by initial capital outlay). The value of the operating(a) assets is therefore the initial capital outlay plus the present value of cash flows derived from economic value added.To obtain the equity value, the value of debt is deducted from the value of the operating assets. The second approach involves EBIT less taxes (i. e. PAT). PAT less capital charge after recognizing deferred taxes as part of the invested capital. The operating assets remain as the initial capital outlay (having considered the effect of deferred taxes) plus the present value of all income derived from the economic value added.Economic Valuation of Asset (EVA) Model as defined by Kislingerova (2000) is stated as EVAt = Pt = NOPATt Ct x WACCt where NOPATt is Net Operating Profit After Tax or the profit after tax (PAT), Ct is long-term capital (Ct is the sum of equity and invested capital or alternatively, it is the total of fixed assets and net working capital), WACC is plodding Average Cost of Capital. Whenever EVA O, the shareholders wealth is maximized, if EVA =0 then there is a break-even point and at EVA 0 the shareholders wealth is in decline.EVA model serves as a rotating shaft in measuring both the performance of the firms as well its value. WACC serves a dual purpose. It is used in the calculation of EVA and its serves as t he rate for discounting the present value of future earnings to the present time t. The value of the firm is therefore the addition of the book value of capital and the present value of future EVA. To derive the value of equity the value of debt would be deducted from the value of the firm. International Research Journal of Finance and economic science Issue 30 (2009) 182 2. 3. 3.Discounted Cash Flow Model The model uses accounting data as input and the objective of the model is to derive equity value of a going concern. The value of equity is derived by deducting the value of debt (excluding deferred taxes and trade credits) from the total assets. Deferred taxes are regarded as part of equity (Brealey, Myers & Allen, 2006). There are several renewings to the adoption of the model (Jennergren, 2008). The discounted cash flow (DCF) is to a greater extent adaptable to the valuation of a firm with high level of assets in place and low level of uncertainty about future cash flows (Jo os & Zhdanov, 2007).Cash flows available for discounting include dividends, free cash flow to equity and free cash to the firm (debt and equity). A firm can experience lead fonts of growth ranging from electrostatic growth, high growth to changeless growth and high growth through transition to a stable growth. The discount rate could be either cost of equity, cost of debt or the weighted cost of capital (WACC). The choice of discount rate should depend on the type of cash flow (equity or firm) to be discounted. At least two models can be derived from the cash flow model.The Dividend Discount (DD) Model is fit for a firm that pays dividends close to the free cash flow or where it is difficult to estimate the free cash flow to equity. The second model, dispatch Cash Flow Model is suitable where there is a significant margin between dividends and free cash flow to equity or if dividends are not available. The value of firm witnessing stable growth is given as CUsersjoseniD esk top D esk to pDISCOUNTED CA SHFLOW MODELS WHA T THEY A RE A ND HOW TO CHOOSE THE RIGHT ON E__filesImage8. if or a firm that experiences two acquaints of growth (i. e. high growth to stable growth), the value of the firm is CUsersjoseniDesk topDesk topDISCOUNTED CA SHFLOW MODELS WHA T THEY A RE A ND HOW TO CHOOSE THE RIGHT ONE__filesImage9. gif The value of a firm experiencing ternary levels of growth (i. e. high growth through transition to stable growth) is given as CUsersjoseniDesk topDesk topDISCOUNTED CA SHFLOW MODELS WHA T THEY A RE A ND HOW TO CHOOSE THE RIGHT ONE__filesImage10. gifWhere V0 represents equity value or firm value depending on which is discounted, CFt represents cash flow at time t, r represents cost of equity (for dividends or free cash flow to equity) or cost of capital ( for free cash flow to firm), g represents expected growth rate, ga represents initial expected growth (high growth extent) and gn represents growth in a stable period n and n1 are defined as t he period in a two typify growth and high growth in a three stage growth models respectively while n2-n1 represents the transition period in the three stage growth model. . 3. 4. Dividend Valuation Model This is one of the commonest and simplest models for valuation of equity in the secondary market. The equity value is taken as the rundown of discounted dividends receivable each year till the year of maturity and the price the equity is expected to be sold at maturity. The value of an investment is taken to be the discounted value of the cash flows.There are different var.s to the model ranging from One period valuation one Period to multi-periods Po = D1/(1 + ke) + P1/(1 + ke) Po = D1/(1 + ke)1 + D2/(1+ke)2 ++ Dn/(1+ke)n + Pn/(1+ke)n multi- period and to indeterminate length of time Infinity and, growth Po = D/(1+ke) (including Gordon growth) funs. D0(1+g)1 + D0(1+g)2 +.. + D0(1+g)? Po = (1+ke)1 (1+ke)2 (1+ke)? or 183 Po = International Research Journal of Finance and Economi cs Issue 30 (2009) D0 ke g) Where D = dividend paid / expected g = dividends growth rate = cost of equity or equity rate of return ke 1 n = period variation One of the motives behind the use of this valuation model is to identify over and underpriced shares. Moving away from the simplest form of this model Go and Olhson (1990) introduced a more tasking process for generating dividends and returns on equity investment which they adopted in some more specific valuation models.The process is based on some assumptions such that equity holders would receive net dividends and there exists a linear relationship between variables. John and Williams (1985), and Miller and Rock (1985) argue that dividend is a communication tool for the firm to pass information to the market in the event of information asymmetry which implies that there is a positive correlation between information asymmetry and a firms dividend policy. 3. 0. Research methodological analysis We define the research hypothes es, sampling and data collection techniques as well as the statistical techniques used to test the data. . 1. Research Methodology We test the following hypotheses Ho1 The earning per share significantly affects the stock price Ho2 The national gross domestic products significantly affect the stock price Ho3 The lending interest rate significantly affect the stock price Ho4 The foreign exchange rate significantly affect the stock price 3. 2. Model From the hypotheses, the stock price is a function of the impact of earning per share, dividend per share, gross domestic, interest rate and oil price.We restricted the influencing factors to five as representatives of the firms fundamental factors and external (country) factors. A simple linear regress model derived from Al-Tamimi (2007) is adopted for the study. Unlike Al-Tamimi (2007) who included consumer price index (CPI) and money supply (MS) as independent variables, those variables were replaced with inflation rate (INFL) and fore ign exchange rate (FX) in view of the significant impact they have on the economies of underdeveloped countries.SP = f (EPS, DPS, GDP, INT, OIL, INFL, FX) Where, SP is the stock price EPS is the earnings per share DPS is the dividend per share GDP is the gross domestic product, INT is the lending interest rate, OIL is the oil price INFL is inflation and FX is the foreign exchange rate. SP is the dependent variable and it is used to regress the other independent variables (EPS, DPS, GDP, INT, OIL, INFL, FX) in the stock market. The outcome of the regression would be the variance on the dependent variable as resulting from the impact of the independent variables.To condone the effects of multicollinearity normally associated with multi-variables in regression analysis, multicollinearity test is aired to explain the extent of correlation between the independent variables.. A multiple regression software (WASSA) was used to test the multicollinearity among the independent variables b efore proceeding to conduct the regression analysis. International Research Journal of Finance and Economics Issue 30 (2009) 3. 3. Data Sampling 184 There are over cxxx companies whose shares are being traded in the Nigerian capital market.The Banking sector in the last five years has dominated the market in toll of trading volumes and market performance. The earning per share (EPS) and dividend per share (DPS) of twelve companies listed on the Nigerian Stock Exchange (NSE) and (average) annual GDP, crude oil price (OIL), lending interest rate (INT), inflation rate (INFL) and foreign exchange rate (FX) are used are analysed for effect on the stock price. The period covered by the data is year 2001 to 2007. The choice of the companies and period used for the data gathering depend on availability of data. . 4. Data Restructuring Weights are attached to EPS and DPS for each of the companies sampled for each of the year. The weight is derived as a ratio of the companys EPS or DPS to t he total EPS or DPS of all the companies for each of the years. The weight is thereafter multiplied with the respective company EPS or DPS to derive weighted stock price (SP), EPS or DPS and thereafter all the companies weighted SP, EPS or DPS are summed together for each of the year (APPENDIX I). 4. 0. Findings and InterpretationIn a linear expression where more than two variables are deployed, multicollinearity between variables may not be ruled out. A multicollinearity test is therefore conducted for all the independent variables. Using the Pearson coefficient of correlation, we consider any correlation between two variables + 0. 75 as strong. For instance, from Table 1 below there is no significant correlation between earnings per share and dividend per share. Our explanations for it are into parts.First, all the companies in the sample reported earnings per share for each of the years covered by the study though in some instances the EPS are negative but not all the companies declared and /or paid dividends throughout all the periods. Secondly, EPS movement unlike DPS is largely outside the control of the Management. There is a strong correlation between crude oil price and GDP. The justification for the correlation between crude oil price and GDP can be found in the fact that the Nigerian economy predominantly depends on oil revenue.Table I DPS EPS GDP OIL INT INF FX Outcomes of the Multicollinarity Test (Pearson Coefficient of Correlation DPS 1 -0. 302 0. 609 -0. 395 -0. 498 -0. 521 0. 724 EPS 1 -0. 523 -0. 596 0. 366 0. 778 -0. 037 GPD 1 0. 959 -0. 702 -0. 492 0. 795 OIL INT INFL FX 1 -0. 706 -0. 434 0. 614 1 0. 988 -0. 424 1 -0. 313 1 A strong correlation also exist between INFL and INT which might be the result of manufacturers and service providers passing increased lending interest rate to consumers. A strong correlation exists between FX and GDP.Unexpectedly, there is a strong correlation between INF and EPS, we do not have any explanation for th is relationship. For our regression analysis, OIL and INFL were dropped from the model. Though there is a strong correlation between FX and GDP, both variables are used in the regression. FX and GDP variables are significant to the economy of developing nations like Nigeria, therefore their exclusion from the regression would result in a very high eonian (? ). 185 International Research Journal of Finance and Economics Issue 30 (2009)A regression analysis was run on the independent variables DPS, EPS, GDP and INT after dropping OIL, INFL and FX. Table I shows the result of the regression analysis. Table II Summary of the Regression Analysis R2 0. 99996 ? 67. 2385 0. 3835 0. 0869 0. 3805 0. 8236 1. 9741 Adjusted R2 0. 99978 T Test 9. 597 36. 259 33. 369 21. 809 7. 375 11. 214 Standard Error of Estimates 0. 4752 F Test 5385. 033 R 0. 99998 uninterrupted DPS EPS GDP INT FX The stock price (P) is highly sensitive to variation as indicated by R2 of 0. 99996. In other words the re is 99. 9% and as a matter of fact 100% in stock variation caused by the independent variables. The variability as measured by coefficient of variation (? ) is expectedly positive for DPS, EPS and GDP and expectedly negative for lending interest (INT) though rather significantly. The ? for DPS and EPS though positive were not significant. Many of the companies resorted to bonus issues instead of dividends and the Nigerian investors are more interested in incomes rather than capital apprehension especially where the stock market performance is poor.The failure to declare and pay dividend leaves two negative impacts on stock prices. The existing investors are denied additional funds to invest and the potential investors seeking investment incomes are discouraged. The hypothesis that EPS affect stock price significantly is accepted. The positive GDPs coefficient in relation to the stock price is in agreement with some other studies (Udegbunam and Eriki,2001 Ibrahim 2003 Mukherjee a nd Naka 1995 Chaudhuri and Smiles, 2004). The ? is insignificant at 0. 805 and this might not be bemused with the increasing foreign allow maintained by CBN from the proceeds of crude oil sales. The proceeds of the crude oil sales are not released to the economy for investment in various productive sectors of the economy but rather held in foreign economies as part of the CBNs monetary policies. The domestic economy is denied of the investments that would have occurred if the funds in the foreign reserve are released for spending in the domestic economy. The hypothesis that the GDP affects stock price significantly is accepted.The coefficient of interest which is negative is expected and found to be significant. The negative coefficient of the lending interest rate is in agreement with the findings of Al-Qenae, Li & Wearing (2002), and Mukherjee and Naka (1995). Lending interest rate is a strong tool in the hands of CBN to influence the economy and where the interest is high as i t is Nigeria where lending interest rates hovers between 22% and 25%, the availability of the investors to access funds is curtailed and the impact on the stock price would be negative as shown.The hypothesis that lending interest rate affects the stock price significantly is accepted The foreign exchange rates coefficient is significantly negative at significant level of 10%. This is not unexpected. Local and foreign investors tend to invest in an economy that has a very high currency exchange rate to foreign currencies. The topical anaesthetic investors are discouraged from taking their funds out of the economy for worship of reduced purchasing while foreign investors are encouraged differently for increased purchasing power. The hypothesis that foreign exchange rate affects the stock price significantly is accepted.Lastly, the constant (? ) is 67. 2385 (negative). This suggests that the minimum stock price in the market is 0. We had initially excluded FX from the regression for the reason of its collinearity with GDP but the constant was negative and excessively high. The inclusion of FX has reduced the negativity which is an indication that there are other important variable(s) that significantly affect the stock prices but not considered in this study. The stock price cannot be 0 except the company is in liquidation. International Research Journal of Finance and Economics Issue 30 (2009) 186This raises an important question of what factor(s) could have accounted for the extra ordinary stock market performance in Nigeria between 2005 and 2007 where some stocks return over 1000% per annum. The nation House of Representatives charge on Capital commercialises expressed disgust at the hike in the stock prices of companies in the banking and oil sectors (Thisday unfermentedspapers, 2008). The hike which may not be a non-economic factor (such as political, unhealthy competition, profiteering by issuers who are at the same time market investors) may be the omitted important variable accounting for the high ?. . 0. Conclusions and Recommendations The forces of demand and supply have direct effect on the stock price while the other indeterminate number of firm, industry and country factors influences the demand and supply factors. The effect, positive or negative the other factors apart from the demand and supply leave on stock price are not static rather changes. For instance, lending interest rate effect could be positive or negative depending on the aim of the CBN in deploying it as one of the tools for implementing monetary policy.The study has contributed to existing literatures in confirming or raising new issues with respect to other factors influencing stock prices. 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Frank (2004) Information Uncertainty and Stock Returns An Article Submitted to The Journal of Finance Manuscript 1149 www. afajof. rg/afa/forthcoming/zhang_information. pdf Zhao, Xing-Qiu (1999), Stock prices, inflation and output evidence from China, Applied Economics Letters, 6 Appendix Appendix I Selected Market Indices (2001 2007) yr PRICE* DPS* EPS* GDP** INT** 42. 53 430. 00 393. 29 431,783. 10 21. 34 2001 43. 70 432. 72 412. 52 451,785. 60 29. 70 2002 109. 21 577. 63 459. 83 495,007. 10 22. 47 2003 116. 76 552. 48 600. 59 527,576. 00 20. 62 2004 110. 56 466. 97 708. 90 561,931. 40 19. 47 2005 102. 33 553. 87 1,666. 03 595,821. 61 18. 43 2006 95. 87 549. 93 894. 96 561,776. 34 19. 1 2007 consultation Central Bank of Nigeria Statistical Bulletin** Cashcraft Asset Management trammel / APT Securities and Fund Limited * OIL** 24. 50 25. 40 29. 10 38. 70 57. 60 66. 50 54. 27 INFLE** 18. 90 12. 90 14. 00 15. 00 17. 90 8. 20 13. 70 FX ** 111. 94 120. 97 129. 36 133. 50 132. 15 128. 65 131. 43 189 International Research Journal of Finance and Economics Issue 30 (2009) Appendix II Regression Analysis Of Selected Market Indices (2001 2007) binary additive Regression Estimated Regression Equation SPt = +0. 38353330161483 DPSt +0. 086971432931437 EPSt +0. 38049146437789 GDPt -0. 82357353121514 INTt -1. 740597666311 FXt -67. 238476376193 + et Multiple linear Regression Ordinary Least Squares Variable DPSt EPSt GDPt INTt FXt uninterrupted Variable %DPSt %EPSt %GDPt %INTt %FXt %Constant Variable Parameter 0. 383533 0. 086971 0. 380491 -0. 823574 -1. 97406 -67. 238476 Elasticity 2. 201042 0. 359282 2. 221624 -0. 200986 -2. 822992 -0. 75797 Stand. Coeff. S. E. 0. 010577 0. 002606 0. 017447 0. 111666 0. 17603 7. 006084 S. E. * 0. 060703 0. 010767 0. 101869 0. 027251 0. 25173 0. 078979 S. E. * T-STAT H0 parameter = 0 36. 259468 33. 368601 21. 808584 -7. 375331 -11. 214366 -9. 597156 T-STAT H0 elast = 1 19. 785697 -59. 07274 11. 992081 -29. 320395 7. 241855 -3. 064493 T-STAT H0 coeff = 0 2-tail p-value 0. 017553 0. 019073 0. 029171 0. 085794 0. 056618 0. 066096 2-tail p-value 0. 032148 0. 010697 0. 052964 0. 021704 0. 087356 0. 200805 2-tail p-value 1-tail p-value 0. 008776 0. 009536 0. 014585 0. 042897 0. 028309 0. 033048 1-tail p-value 0. 016074 0. 005349 0. 026482 0. 010852 0. 043678 0. 100402 1-tail p-value 0. 008776 0. 009536 0. 014585 0. 042897 0. 028309 0. 5 S-DPSt 0. 763848 0. 021066 36. 259468 0. 017553 S-EPSt 0. 69251 0. 020753 33. 368601 0. 019073 S-GDPt 0. 729372 0. 033444 21. 808584 0. 029171 S-INTt -0. 09814 0. 013307 -7. 75331 0. 085794 S-FXt -0. 48017 0. 042817 -11. 214366 0. 056618 S-Constant 0 0 0 1 Computed against deterministic endogenous series *Note Multiple Linear Regression Regression Statistics Multiple R 0. 999981 R-squared 0. 999963 Adjusted R-squared 0. 999777 F-TEST 5385. 033289 Observations 7 Degrees of Freedom 1 Multiple Linear Regression Residual Statistics Standard Error 0. 475177 S um Squared Errors 0. 225793 pound Likelihood 2. 086595 Durbin-Watson 3. 380955 Von Neumann Ratio 3. 944448 et 0 3 et 0 4 Runs 6 Runs Statistic 1. 333946 NB Regression analysis was done using a software developed by Wessa (2008)