Financial Crisis in Stock Exchanges-An Empirical Analysis of the Factors that can affect the Movement of Stock Market Index

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1 Global Journal of Management and Business Research: C Finance Volume 15 Issue 10 Version 1.0 Year 2015 Type: Double Blind Peer Reviewed International Research Journal Publisher: Global Journals Inc. (USA) Online ISSN: & Print ISSN: Financial Crisis in Stock Exchanges-An Empirical Analysis of the Factors that can affect the Movement of Stock Market Index By Rabianajaf, Khakan Najaf, Imran Hussain Shah & Amir Iqbal University of Lahore, Pakistan Abstract- This paper focuses on the factors that can affect the movement of stock market index, which creates volatility in the prices of companies listed in the stock market. Stock Market Efficiency Theory focuses on the market news, information, economic conditions, etc. Good or bad news also impact on the market behavior. Initial Public Offering (IPO) is considered as convenient way to raise funds from market. Therefore, important econometric advantages in examining the role of stock markets in the relationship between financial development and growth using time series methods. Summing up the test indicates that the consumer price index and political stability have no relation with the fluctuation in Karachi stock exchange kse100. Secondly the test shows one variable associates with other variable. Keywords: financial crisis, KSE, IPO, FDI, stock market efficiency. GJMBR - C Classification : JEL Code: O16 FinancialCrisisinStockExchanges-AnEmpiricalAnalysisoftheFactorsthatcanaffecttheMovementofStockMarketIndex Strictly as per the compliance and regulations of: Rabianajaf, Khakan Najaf, Imran Hussain Shah & Amir Iqbal. This is a research/review paper, distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

2 Financial Crisis in Stock Exchanges-An Empirical Analysis of the Factors that can affect the Movement of Rabia Najaf α, Khakan Najaf σ, Imran Hussain Shah ρ & Amir Iqbal Ѡ Abstract- This paper focuses on the factors that can affect the movement of stock market index, which creates volatility in the prices of companies listed in the stock market. Stock Market Efficiency Theory focuses on the market news, information, economic conditions, etc. Good or bad news also impact on the market behavior. Initial Public Offering (IPO) is considered as convenient way to raise funds from market. Therefore, important econometric advantages in examining the role of stock markets in the relationship between financial development and growth using time series methods. Summing up the test indicates that the consumer price index and political stability have no relation with the fluctuation in Karachi stock exchange kse100. Secondly the test shows one variable associates with other variable. Where FDI is positively correlated while exchange rate, interest rate, CPI and political stability are negatively correlated, that shows the negative relationship between kse100 and exchange rate that if the exchange rate increases then the kse100 index will decrease. Keywords: financial crisis, kse, ipo, fdi, stock market efficiency. I. Introduction Stock market development is an important indicator of economic growth. Levine and Zarkos (1998) argued that market capitalization and index growth reflect economic growth (Levine & Zervos 1998). Many studies have concentrated on cross section regressions which as pointed by Levine and Renelt (1992) among others should be viewed with caution. Time series analysis can address the issue (Levine & Renelt 1992). Purpose of this research is to analyze why the stock market fluctuate and does the exchange rate, inflation rate, foreign direct investment and political events effect the movement. Research indicates that fluctuation is effected by change occurred in exchange rate, inflation rate, foreign direct investment, political events and many other factors. So the study of these factors can help to predict the change in share price that can help in avoiding loses caused by the bubble created. Author α: Ph.D Scholar, Lahore School of Accounting and Finance, University of Lahore Pakistan. Author σ: Lecturer, Lahore School of Accounting and Finance, University of Lahore Pakistan. Author ρ: Professor, Lahore School of Accounting and Finance, University of Lahore Pakistan. Author Ѡ: Head of Department, Lahore School of Accounting and Finance, University of Lahore Pakistan. II. Objectives of the Study To determine the relationship between KSE100, exchange rate, inflation rate, foreign direct investment and political events in Pakistan. To determine the effective change caused by the independent variables on dependent variables. To facilitate the buyers and sellers in the stock market so that they can trade effectively and efficiently, can make timely entry and exist while considering the above mentioned factors. To analyze the important dimensions of stock index investment in Pakistan in the light of the various studies carried out by different researchers. a) Significance Of The Study The study explains the factors affecting the movement and patterns of share prices in stock exchange. III. Literature Review Nieh and Lee (2001) examined both short-run movements and long-run equilibrium relationships between stock prices and exchange rates by using daily closing stock market indices and foreign exchange rates for the time period from October 1993 to February 1996, by applying Engle-Granger two steps. It has been observed that no long run equilibrium relationship exists between stock prices and exchange rate. However, in the short-run the two markets have a one-day predictive power in certain countries (Nieh& Lee 2001). Bodnar and Gentry (1993) examined the relationship between changes in exchange rates and industry values where the return on the industry portfolio is regressed against the return on the nominal stock market and percentage change in the trade-weighted nominal exchange rate, and found that in all three countries, between 20 to 35 percent of the industries reveal statistically significant exchange rate exposure (Bodnar& Gentry 1993). Jorion (1990) studied the exchange rates and commons stocks of companies 287 U.S. multinationals with and without foreign operations, and found that the degree of a firm s foreign involvement positively affects the exposure estimates. On the other hand, domestic firms without foreign operations have very similar exposures (Jorion 1990). Abdalla and Murinde (1997) examined the relationship between stock prices and exchange rates 55

3 56 for emerging markets such as India, Korea, Pakistan, and the Philippines for the period from 1985 to 1994 using co-integration techniques, and reported unidirectional causality from exchange rates to stock prices for all countries except the Philippines (Abdalla & Murinde 1997). Bahmani-Oskooee and Sohrabian (1992) studied bidirectional causality between changes of exchange rates and stock prices by employing the Granger causality test and standard (Engle and Granger) co-integration techniques for the data of U.S. stock market index for the period from 1973 to 1988, and found that the short-term horizon, bidirectional causality exists between exchange rate and the U.S. stock market index (Oskooee & Sohrabian 1992). Johnson and Soenen (2004) studied the effects of U.S. equity markets on the value of the U.S. dollar, for the period from 1971 to 2002, and found that the significance of the exposure estimates changes for each U.S. dollar structural change (i.e. strong or weak U.S. dollar period) (Johnson & Soenen 2004). Soenen and Hannigar (1988) studied the linkage between stock prices and U.S. effective exchange rates, and found that stock prices and the value of the U.S. dollar are negatively correlated (Soenen & Hennigar 1988). Aggrawal (2004) attempted to determine the relationship between changes in stock indices and changes in dollar exchange rates under a floating exchange rate regime, and observed that stock prices and U.S. exchange rates are positively correlated and stronger over a short term horizon than over a long term horizon (Aggarwal 2004). Zohrabyan (2005) studied the effect of currency movements on Stock Markets because both foreign currency markets and stock markets are important indicators of economy-wide performance, and much attention has been given to modeling both markets, by both OLS regression and more sophisticated time series methods. In addition, causality will be examined through Directed Acyclic Graphs (DAG). The results support the evidence that exchange rates and stock markets are weakly correlated to each other, which implies that Where KSE: Karachi Stock exchange Βn: Slop B0 : Constant X1: Exchange Rate X2: Interest Rate X3: Inflation Rate X4: Foreign Direct Investment X5: Political Stability exchange rates are not useful tools to predict stock market movements. Boone, Giorno and Richardson (1998) studied the likely influence of stock market fluctuations, using the Johansen technique, and suggested that a 20 percent fall in equity prices in G7 stock markets, would have a significant impact on the world economy (Boone, et al., 1998). Khan and Ahmed (2008) studied the relationship between aggregate stock market trading volume and daily stock returns during in which the events are happened in Pakistan and evaluated the instability in the stock market due to the events, and concluded that the event effect the value of Pearson correlation and due to event the value is decrease from their pre event value. Robbani and Anantharaman (2002) have studied the effect of political events on the prices of some of the selected emerging stock market indices for the four-year period, from July 1, 1997 to June 30, 2001 and for each market, results also support the notion that emerging stock markets too are of semi-strong forms efficiency in the sense that they reflect not only relevant economic information but also important political information through their pricing (Anantharaman & Robbani 2002). IV. Methodology To assess the desired results, foreign direct investment, exchange rate, inflation rate, interest rate and political situation are considered as regressers and fluctuation in stock market as transgressers. SPSS is used for the empirical analysis through regression and correlation. V. Data Collection The sample of 59 months starting from Jan 5, 2005 to Nov 9, 2008 is observed for completion of this study. Data is collected from the reliable sources of State Bank of Pakistan, Federal Bureau of Statistics and the Karachi Stock Exchange. KSE100 = C + [1 (ex.rate) + [2 (i.rate) + [3 (cpi) + [4 (fdi) + [5 (p.stay) + i

4 VI. Empirical Analysis Descriptive analysis used to describe the data by using descriptive summary as well as, scattered plots, correlation and regressions analysis with normal distribution curve. Inferential analysis used to describe the relation between variables by checking the Table1 : Descriptive Analysis of Data acceptance or rejection of hypothesis and to see the nature of relationship between variables. In inferential portion the study tested the relationship between kse100, exchange rate (ex.rate), interest rate (i.rate), inflation rate (cpi), foreign direct investment (fdi) and political stability (p.stay). N Minimum Maximum Mean Std. Deviation KSE EX.RATE I.RATE CPI FDI P.STAY Valid N (listwise) 59 Table 1 presents the descriptive statistics that show the overall picture of all the six variables. In the above table the mean values and the values of standard deviation of all the six variables have been shown. Mean value provides the idea about the central tendency of the values of a variable. The mean of different variables like kse-100 (mean: 10119), Ex.Rate (mean: ), I.Rate (mean: 10.55), CPI (mean: 11.76), FDI (mean: ) and P.Stability (mean: 0.745). Standard deviation gives the idea about the dispersion of the values of a variable from its mean value. In kse100 the maximum value is and the minimum value is The standard deviation is , means that the value of kse100 can increase and can decrease In exchange rate the maximum value is and the minimum value is The standard deviation is 8.727, means that the value of exchange rate can increase and can decrease In interest rate the maximum value is 15 and the minimum value is 7.5. The standard deviation is 2.28, means that the value of exchange rate can increase 2.28 and can decrease In CPI inflation rate the maximum value is 25.3 and the minimum value is 6.2. The standard deviation is 5.756, means that the value of CPI inflation can increase and can decrease In FDI the maximum value is and the minimum value is The standard deviation is , means that the value of FDI can increase and can decrease In political stability the maximum value is 1 and the minimum value is 0. The standard deviation is 0.439, means that the value of political stability can increase and can decrease Scatter plot or graph of two variables shows how the scores for an individual on one variable associates with his or her scores on the other variable and if the correlation is high positive the plotted point will be close to a straight from the lower left corner of the plot to the upper right. The linear regression line will slope downward from the upper left to the lower right if the correlation is high negative. 57

5 58 Figure 1 shows the results of scatter plot matrix and linear regression among variables. Linear description in scatter plot shows negative relation of KSE-100 index with exchange rate, interest rate, CPI and : Null (H0) and alternative (H1). Figure 1 shows the results of scatter plot matrix and linear regression among variables. Linear description in scatter plot shows negative relation of KSE-100 index with exchange rate, interest rate, CPI and Figure 1 : Linear Regression of Variables H 1 : there is relationship between kse100 and exchange rate H 1-0 : there is no relationship between kse100 and exchange rate political stability while positive relation with FDI. Correlation is used to check the mutual relationship among variables. For checking the relationship we will make two hypothese political stability while positive relation with FDI. Correlation is used to check the mutual relationship among variables. For checking the relationship we will make two hypotheses: Null (H0) and alternative (H1). H 1 : there is relationship between kse100 and exchange rate H 1-0 : there is no relationship between kse100 and exchange rate H2: there is relationship between kse100 and interest rate H 2-0 : there is no relationship between kse100 and interest rate H3: there is relationship between kse100 and CPI inflation rate H 3-0 : there is no relationship between kse100 and CPI inflation rate H 4 : there is relationship between kse100 and FDI foreign direct investment H 4-0 : there is no relationship between kse100 and FDI foreign direct investment H 5 : there is relationship between kse100 and political stability H 5-0 : there is no relationship between kse100 and political stability.

6 Table 2 : Correlations among Variables Correlations KSE100 EX.RATE I.RATE CPI FDI P.STAY KSE100 Pearson Correlation ** -.279* -.268*.368** -.296* Sig. (2-tailed) EX.RATE Pearson Correlation -.457** 1.915**.627** Sig. (2-tailed) I.RATE Pearson Correlation -.279*.915** 1.719** Sig. (2-tailed) CPI Pearson Correlation -.268*.627**.719** Sig. (2-tailed) FDI Pearson Correlation.368** Sig. (2-tailed) P.STAY Pearson Correlation -.296* Sig. (2-tailed) Table-2 represents the correlations where FDI is positively correlated r=.368 while exchange rate, interest rate, CPI and political stability are negatively correlated (r=-.457, -.279, -.268, respectively). The magnitudes of the above discussed two correlations are greater than 0.33 in the absolute terms, which shows the moderate correlations between the said pairs of the variables but the correlation of interest rate, CPI and political stability intention is lesser than 0.33 in absolute terms, which shows the weak correlation between them. All the above correlations are statistically significant at less than five percent level of significant. In the case of these correlations the null hypothesis that were stated above of no correlation are rejected as the P-values are lesser than 0.05 and following statement are found correct. H 1 : there is relationship between KSE100 and exchange rate. They will change 45.7% in same direction and change 54.3% due to other factor. H 2: there is relationship between kse100 and interest rate. They will change 27.9% in same direction and change 72.1% due to other factor. H 3 : there is relationship between kse100 and CPI inflation rate. They will change 26.8% in same direction and change 73.2% due to other factor. H 4 : there is relationship between kse100 and FDI foreign direct investment. They will change 36.8% in same direction and change 63.2% due to other factor. H 5 : there is relationship between kse100 and political stability. They will change 29.6% in same direction and change 70.4% due to other factor. Regression is used to check the effect size of independent variable to dependent variable. Table 3 : Regression of Variables Mode R R Square Adjusted R Square Std. Error of the Estimate l 1.649a a. Predictors: (Constant), P.STAY, I.RATE, FDI, CPI, EX.RATE The modal summary depicts the values of R- square that observed the changes in dependent and independent variables, the value of R square is.421 that mean if kse100 is changed 100 % than the 42.5% change will be due to the independent variables (exchange rate, interest rate, CPI, FDI and political stability) and rest 57.5% is because of other factors. H 2 : there is relationship between kse100 and interest rate H 2-0 : there is no relationship between kse100 and interest rate H 3 : there is relationship between kse100 and CPI inflation rate 59

7 Table 4 : f-test among variables ANOVA 60 ANOVA Model Sum of Squares Df Mean Square F Si g. 1 Regression a Residual Total a. Predictors: (Constant), P.STAY, I.R, FDI, CPI, EX.RATE b. Dependent Variable: KSE100 F-test will determine the combine relationship of independent variables on dependent variables and the value of f is H 0 : independent variables jointly don t affect the dependent variables H 1 : independent variables jointly do affect the dependent variables The significance value is.000 and it is less than 0.05 so we will reject H0and accept H1 that indicates Table 5 : ANOVA table independent variables jointly do affect the dependent variables. Coefficients Model Unstandardized Coefficients Standardized Coefficients t Si g. B Std. Error Beta 1 (Constant) EX.RATE I.RATE CPI FDI P.STAY a. Dependent Variable: KSE100 Coefficient table presents the results of the regression analysis. The objective of the regression in this study is to find such an equation that could be used a) Regression Equation to find the impact of independent on dependent variables. The specified regression equation takes the following form: KSE = β0 + β1x1 + β2x2 + β3x3 + β4ln(x4) + β5x5 + ei Now put the values of independent variables in equation. Kse100 = (1) (1) (1) (1) (1) + i Kse100 = H 1 : there is effect of exchange rate on kse100 H 1-0 : there is no effect of exchange rate on kse100 H 2 : there is effect of interest rate on kse100 H 2-0 : there is no effect of interest rate on kse100 H 3 : there is effect of CPI on kse100 H 3-0 : there is no effect of CPI on kse100 H 4 : there is effect of FDI on kse100 H 4-0 : there is no effect of FDI on kse100 H 5 : there is effect of P.stay on kse100 H 5-0 : there is no effect of P.stay on kse100 H 1 : the significance level is.001 which is less than.05 so H 1-0 will be rejected and H 1 is accepted that there is effect of exchange rate on kse100, means that if value of exchange rate decreases 1 unit kse100 will increase 301 units.

8 H 2 : the significance level is.013 which is less than.05 so H 2-0 will be rejected and H 2 is accepted that there is effect of interest rate on kse100, means that if value of interest rate increases 1 unit kse100 will decrease 915 units. H 3 : the significance level is.188 which is greater than.05 so H 3 will be rejected and H 3-0 will be accepted that there is no effect of CPI on kse100. H 4 : the significance level is.046 which is less than.05 so H 4-0 will be rejected and H 4 will be accepted that there is effect of FDI on kse100, means that if value of FDI increase 1 unit kse100 will increase 2.17 units. H 5 : the significance level is.083 which is greater than.05 so H 5 will be rejected and H 5-0 will be accepted that there is no effect of P.stay on kse100. The result shows that there is no effect of CPI and political stability on KSE100 while exchange rate, interest rate and FDI affect the KSE100. VIII. Conclusion Summing up the test indicates that the consumer price index and political stability have no relation with the fluctuation in Karachi stock exchange kse100. Secondly the test shows one variable associates with other variable. Where FDI is positively correlated while exchange rate, interest rate, CPI and political stability are negatively correlated, that shows the negative relationship between kse100 and exchange rate that if the exchange rate increases then the kse100 index will decrease. The magnitudes of FDI and exchange rate show the moderate correlations between the said pairs of the variables whereas the correlation of interest rate, CPI and political stability shows the weak correlation. All the correlations are statistically significant at less than five percent level of significant. There was negative relationship between kse 100 and interest rate was observed, this means that if the interest rate increase then the kse100 index will decrease. Negative relation was also observed in CPI, exchange rate and kse100, means that if the CPI inflation rate increase then the kse100 index will decrease. This means that if the exchange rate increase then the kse100 index will decrease. Positive relationship between kse100 and FDI was observed. This means that if FDI will increase in the country it will affect positively then the kse100 will increase. The FDI, interest rate and exchange rate have relationship between the Karachi stock exchange while the consumer price index and political stability have no relation with the fluctuation in Karachi stock exchange kse100. It shows that there is effect of exchange rate on kse100, means that if value of exchange rate decreases 1 unit kse100 will increase 301 units. The effect of interest rate on kse100 shows that if value of interest rate increases 1 unit kse100 will decrease 915 units. The effect of FDI on kse100, shows that if value of FDI increase 1 unit kse100 will increase 2.17 units The study gives the touch to highlight the important dimensions of stock index investment in Pakistan in the light of the various studies carried out by different researchers. The Karachi stock exchange has great importance in the Asia as it is one on the emerging market of the world. That is the mean reason that foreigners hold major stake in the Karachi stock exchange IX. Policy Recomendations The study conducted may facilitate the buyers and sellers and give a substantial clue to the market practitioner for minimizing risks while investing in stocks market and also give a clue that every event has different effect the on stock market which includes the trading volume and stock return. Recommendations are as follows: 1. The relationship between the variables also shows the linkage to somehow predict the prices prevailing in the stock market on the basis of variables, so one must consider that factors before investing in the stock market. 2. Foreign direct investment can boost market activities so more the foreign inflows better will be the performance. 3. Stable exchange rate can boost the market performance and foreigners to invest more in the market. 4. Stable interest rate or lower interest rate will attract more investors to the market. 5. Political situation has almost no effect on the market and the effect is for a short period of time like in case of death of any leader. References Références Referencias 1. Abdalla I. and Murinde V. (1997): Exchange rate and stock price interactions in emerging financial markets: evidence on India, Korea, Pakistan and the Philippines. Applied Financial Economics,7(1): Aggarwal R. (2004): Exchange rates and stock prices: A study of the US capital markets under floating exchange rates. Akron Business and Economic Review,12: Anantharaman and Robbani (2002: An Econometric Analysis of Stock Market Reaction to Political Events in Emerging Markets. Pittsburgh, Pennsylvania, Second Annual ABIT Conference. 4. Bodnar G.M. and Gentry W.M. (1993): Exchange rate exposure and industry characteristics: Evidence 61

9 62 from Canade, Japan and the USA. Journal of International Money and Finance,12: Boone L., Giorno C. and Richardson P. (1998): Stock market fluctuations and consumption behaviour: some recent evidence. OECD Economics Department Working Paper, Volume Johnson R. and Soenen L. (2004): The US stock market and the international value of the US dollar. Journal of Economics and Business, Elsevier,56(6): Jorion P. (1990): The Exchange-Rate Exposure of U.S. Multinationals. Journal of Business, pp Levine R. and Renelt D. (1992): A Sensitivity Analysis of Cross- Country Growth Regression. American Economic Review, pp Levine R. and Zervos S. (1998): Stock Market, Banks and Economic Growth. American Economic Review, pp Nieh C.C. and Lee C. (2001): Dynamic relationship between stock prices and exchange rates for G7 countries. Quarterly Review of Economics and Finance,41(4): Oskooee M.B. and Sohrabian A. (1992): Stock Prices and the effective exchange rate of the dollar. Applied Economics,24: Soenen L. and Hennigar E. (1988) An Analysis of Exchange Rates and Stock Prices: the U.S. Experience between 1980 and Akron Business and Economic Review,pp