Determinants of Stock Market in Finland - Research Paper Example

Report of a study on the Determinants of Stock Market in Finland INTRODUCTION This paper represents a report regarding the determinants of stock market in Finland. The study used change in stock prices as the variable of interest while exchange rate, interest rate and GDP growth rate were used as the independent variables. Stock exchange or financial market plays central role in an economy. From it we can easily predict the overall state of economy of a county. From different factors such as the above, stock market is dependent and the influences of these determinants are clearing, that is, negative or positive. Major determinants (macroeconomic variables) in the economy that impact the stock exchange and key determinants which influence the stock prices in any nation are exchange rates, inflation, Government policies, money supply, foreign direct investment, interest rate, law & order situation, security issues (terrorist attacks), political instability, GDP growth rate, and judiciary crises among others. For this purpose to ascertain the impact of macroeconomic determinants on stock exchange, certain variables were selected to be studied, that is, exchange rates, GDP growth rate, and interest rate. Yearly data of 10 consecutive years were acquired for the research. A monthly data for each year was then recorded. For concluding results, statistical tools such as multiple regressions and Pearson’s correlation models were used. The study shows (85%) variation in the dependent variable has explained by the independent variable. Thus, the model was good fitted and there was a significant correlation between independent variables and the dependent variable. The variation in Finland`s stock prices was explained up to 85 per cent by the deviation in the determinants (independent variables). Influences of both macroeconomic and microeconomic variables, in ancient times, were particularly significant for most researchers. Researchers, students, and economists have attempted in several years to discover the association between macro-economic variables and stock prices. These purpose, economists have applied various models in the interest to discover the association between stock prices and macro-economic variables. Therefore, the significance of the study was backed up by the search to ascertain the effect of macroeconomic variables on the prices of countries` stock index. Stock market plays significant role as far as the development of any economy is concerned and it acts like the intermediary. In any stock market and so is Finland stock market, security is mainly the conversion of moneys. Stock market offer investment opportunity and so change in the stock exchange index definitely causes disorder in macroeconomic factors (Verbeke & Merchant, 2012, pg. 39). Stock market through risks sharing and liquidity speeds up the economic growth of nations. The decrease and increase in stock index is a comprehensible phenomenon of the economies surrounded by the investors, policy makers, corporation, and economic researcher. Market forces of supply and demand, dictates the stock prices. If supply is equal to the demand, at that point the stock price is static. The core macroeconomic factors are inflation rate, interest rate, industrial production index, exchange rate, export, gross domestic product, foreign exchange reserves, money supply, and unemployment and they all have connection with the prices index of Finland stock exchange. Ehrhardt & Brigham (2010) concluded that variations in macroeconomic variables leads to the alteration in the structure of` a country`s stock exchange index. The government of Finland`s polices, be it monitory or fiscal, have a huge influence on the stock prices and economic activities of the country LITERATURE REVIEW Various researchers adopted multiple aspects to ascertain the relationship between macroeconomic variables and stock market. Baker & Kiymaz (2013) claimed that exchange rate, interest rate, inflation rate, foreign exchange reserves, industrial production index, and money supply are the key factors which affect a country`s stock market prices. Dorodnykh (2013) used factors such as inflation, government bonds, call money rates, and money supply to determine the bond between these macroeconomic variables and stock market. (Verbeke & Merchant, 2012) closely examined the relationship between Karachi stock index and macroeconomic variables. The most noticeable variables he used are money supply, industrial production, consumer prices index, and interest rate. As such, he concluded that stock prices were directly proportional to industrial production while inversely proportional to inflation rates. The depth study given in Bruce (2010) showed that interest rate, exchange rate and inflation are the backbone determinants of an economy. An upsurge in demand of export goods causes the home currency to depreciate since the cost of exporting these goods rises. A negative association was found between stock index and inflation using Tokyo stock exchange. Moreover, (Baker & Nofsinger, 2010, pg.64) claimed that money supply, interest rate plus inflation influence the stock exchange prices. Stock retune ought to be positively associated with inflation, when the stock prices hedge against inflation. Nevertheless, the research of Bruce, B. R. (2010) revealed that there exists an indirect association between stock prices and inflation. According to (Ehrhardt & Brigham, 2010, pg. 47), when money supply upsurges in the market, it first affects the wealth and the impact on stock exchange prices is always positive. But, in the opinion of devaluation in currency by investors, inflation and future uncertainty will decline the stock exchange price in future, something that is not a desired sign. Baker & Kiymaz (2013) argue that proxy hypothesis illustrates that a rise in the development undertakings decreases the inflation, which in turn increases the stock prices due to the indirect association between them. After a thorough analysis of the determinants of stock prices in Karachi stock exchange, Dorodnykh (2013) concluded that macroeconomic factors co-integrated with the stock prices. The research further claimed that stock prices positively relate with interest rate and money supply in the short run while negatively relating with inflation and foreign exchange reserves. Ehrhardt & Brigham (2010) jumped to the conclusion that the stock prices of any stock exchange will most likely correlated with variables of monetary policy (money supply, inflation, interest rate, industrial production). Research of Baker & Nofsinger (2010) further pronounces that stock market prices and currency devaluation can both influence each other. Dorodnykh (2013) studied monthly data, designed a model and figured out the macroeconomic variables so as to investigate both short and long run association between stock prices and exchange rate. Relationship between real output and stock index in modern time is positive and noteworthy. Edwards & Garcia (2008) gathered data from U.S stock market and arrived to the deduction that currency deprecation causes a decline in stock prices in short run. Moreover, exchange rate reduction implies higher inflation in times to come, which makes investors more cynical about the firm’s future performance. Edwards & Garcia (2008) also used U.S `s monthly data regarding stock prices and exchange rate from 1975 to 1979 so as to explain the correlation between dollar`s exchange rate and stock prices. In his analysis, he adopted simple regression model. He found that stock prices were strongly and directly related with U.S dollar in the short term than in long term. A study by Verma (2013) found insignificant relationship between oil prices in stock market index and exchange rate in four countries (U.S, India, Russia, and china). The research by Baker & Nofsinger (2010) also pointed out that relationship exists amongst exchange rate, official resaves, and money supply with stock prices. He demonstrated bi-vitiate relationship between stock prices and macroeconomic variables. To add on previous studies, Baker & Kiymaz (2013) examined the long run association between stock prices, money supply and real output. According to (Verma, 2013, pg.85), the relationship between stock prices and money supply is positive in short run though it is negative in long run. His findings were confirmed by Abbas (2010) who also analysed the association between stock prices movements and macroeconomic variables. Abbas (2010) reached the conclusion that effects of exchange rate and inflation on stock market prices are significantly negative and the effect of economic development is positive though weak on stock market prices of London stock exchange. Dorodnykh (2013) explained a causative relationship between the economy growth and stock market of Pakistan. He concluded that following the financial reforms that took place in the Republic of Pakistan, foreign exchange rates and foreign exchange reserves significantly influenced the stock prices. The research took variables such as Gross Domestic Product, stock exchange liquidity, extent of stock exchange, and production. Using co-integration model method in Pakistan he showed that stock exchange relied on the overall economic growth. On real economy, stock prices movement in Finland stock exchange has such a noteworthy affect. METHODS AND DATA To study the variables, which affect Finland stock market, we picked on interest rate, exchange rate, and GDP growth rate. The study model will be explained by the help of these variables though there were several other variables that affected Finland`s stock prices index. However, the conclusion of this research was solely based on the above determinants. One dependent and three independent variables were use in the research. The dependent variable was Finland Stock Exchange (FSE-100 index) while the independent variables were interest rate, exchange rate and GDP growth. A 10-year monthly data was obtained from Finland`s Stock Exchange. A regression analysis was done using SPSS. Theoretical model The theoretical structure to investigate the determinants of Finland`s stock exchange was explained such that, movements in FSE-100 stock index were influenced by changes happening in interest rate, exchange rate, and GDP growth rate. That is, the research model was as follows: Y (change in stock prices) = C + d1(X1) +d2(X2) +d3(X3) + error term (e)  ∆FSE = C + d1 (∆X1) + d2 (∆X2) + d3 (∆X3) Where; Y= Finland stock exchange 100 index (dependent variable) X1= exchange rate; X2= interest rate; X3= GDP growth rate; “c” was the Y-intercept, a1, a2, and a3 and in the research model represented the slope or in simple terms, the regression coefficient while “e” was the random error. The study was to examine the causation between certain macroeconomic variables and Finland stock exchange market. Certain variables such as interest rate, exchange rate, GDP growth rate and stock market prices of FSE-100 index were considered for 10 years. A monthly data was collected from the year 2003 to 2013 for these variables. Secondary data was used to investigate the above research objective. Secondary data concerning the macroeconomic variables such as interest rate, exchange rate, GDP growth rates as well as the stock market prices of FSE-100 were taken from various websites such as the www.tradingeconomics.com website to determine the influence of macroeconomic factors on FSE-100 index. 10 years of monthly data were used to ascertain the relationship between FSE-100 index and macroeconomic variables. The reason behind using a10-year data was that trying to ascertain the relationship between stock prices of FSE -100 index and macroeconomic variables started way back in 1999. EMPERICAL FINDINGS Statistical tool The study used multiple regression models to analyse and find out the reality behind the main objective of our study. The results were obtained as displayed in the tables below. Table 1. Descriptive statistics Descriptive Statistics Mean Std. Deviation N Change in Stock prices (%) .82 4.642 131 Interest Rate (%) 1.271679 12.6975299 131 Exchange Rate (%) .130611 .9140878 131 GDP growth rate (%) 1.09 2.588 131 Table 2. Summary of coefficient analysis Coefficient of Determination Variables Coefficients Std. Error t value R partial Constant 0.742 1.669 Interest rate -0.002 0.048 -0.051 -0.005 Exchange rate 0.403 0.701 0.574 0.051 GDP rate 0.030 0.174 0.172 0.15 Table 3. Analysis of Variance ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 19.135 3 6.378 .291 .832b Residual 2782.582 127 21.910 Total 2801.718 130 a. Dependent Variable: Change in Stock prices (%) b. Predictors: (Constant), GDP growth rate (%), Interest Rate (%), Exchange Rate (%) From the data, the relationship between stock prices (dependent variable) and independent variables displayed in the table above concludes the regression model results: Change in stock prices, FSE-index = 0.742 + (0.403) X1+ (-0.002) X2 + (0.030) X3. Looking at the above results, it was clear that when change happened in any of the independent variable, the dependent variable was also changed. It is evident from table 2 that interest rate, GDP growth rate, and exchange rate are independent variables that will cause change to the dependent variable (change in stock prices). From the above results, exchange rate and GDP growth rate display positive relationship with the stock prices. Interest rate is the only independent variable that shows negative association with the stock prices. As an interpretation of the above model values, relationship between changes in stock prices in Finland stock market and exchange rate was positive since when say 1% change happened in exchange rate, it brought about 0.403 per cent positive change to the stock prices. As for the negative relationship between change in stock prices and interest rate, a 1 % change to the interest rate brought about -0.002% negative changes to the stock prices. Similarly, if there was a unit change in GDP growth rate, a 0.030 % positive change was expected to occur in the stock prices. Checking for the significance level in the model enabled us to determine whether the variables were insignificant or significant regarding the data analysis. As such, we first utilized the t-ratio. It was clear that the relationship between stock prices and exchange rate was strongly positive, that is, the strongest relationship the independent variables had with changes in stock prices in the entire study. The Pearson’s correlation results suggest there was strong positive relationship between stock prices and exchange rate. Following Pearson’s correlation, the relationship between change in stock prices and interest rate was moderate though negative in nature. The investigation suggests that there was -0.2% relations between the independent variable (interest rate) and stock prices. Correlation between stock prices and interest rate was statistically insignificant since the value of p was 0.0584 which was greater than 0.05. This negative correlation verified past research study. The research of Baker & Nofsinger (2010) found negative correlation between change in stock prices and interest rate. Our study verified the economic theory regarding the negative relationship between investment and interest rate as shown in the diagram A. below. Diagram A. Illustration of how interest rate, r relate with savings and investment Source: (Barnes, 2009, pg. 127). Id represents the investment demand curve and from the diagram we could clearly see interest rate inversely relate with investment though it positively relate with savings (Sd curve has positive slope). The period of July 2008 marked the time when inflation hit a double digits mark. This made the government to formulate measures in which hipper inflation would be controlled through increase of the interest rates, even though this too had negative effects on stock prices. The moderate and positive correlation that is deduced to exist between the stock prices KSE-100 index and inflation has showed impact of such inflationary changes. As per to the results deduced from the Pearson’s correlation coefficient, there is 40.3% moderate positive correlation between independent variable exchange rate and the stock prices (dependent variable). Assuming the value was to be smaller than 0.05, the relationship between stock prices of FSE-100 index and exchange rate was to be deduced to be statistically significant. This deduced correlation somehow showed an opposing trend in the context of literature review, in that it was a clear contradiction between the previous research and this study. The researches of great scholars like Bathe (2008) have shown negative correlation between stock prices and interest rate. On the other hand, the study by Barnes, P. (2009) has shown positive correlation existing between the stock prices and exchange rate. Furthermore, the study of Robert Johnson depicts a positive relationship between the two. The above analysis depicted that the relationship between the growth of GDP and stock prices of KSE-100 index was weakly positive. The model proposes only 3% positive correlation between the stock prices and the growth rate of GDP, which was statistically insignificant. Therefore no much attention was supposed to be given to it, due to the weak correlation though there was still exist some relationship which was also mentioning. The analysis of this study has obeyed the previous research studies. This was supported by the research study of Abbas (2010) which has shown positive relationship between GDP and stock prices. Moreover, Bruce (2010) has given analysis of results similar to this study, for instance, the stock prices and GDP show very weak positive correlation with the stock prices index of Finland stock exchange. Table 4. Analysis of coefficient correlations Coefficient Correlationsa Model GDP growth rate (%) Interest Rate (%) Exchange Rate (%) 1 Correlations GDP growth rate (%) 1.000 .040 -.312 Interest Rate (%) .040 1.000 -.714 Exchange Rate (%) -.312 -.714 1.000 Covariances GDP growth rate (%) .030 .000 -.038 Interest Rate (%) .000 .002 -.024 Exchange Rate (%) -.038 -.024 .492 a. Dependent Variable: Change in Stock prices (%) From table 4 above, the following conclusion were made: Exchange rate → Interest rate The relationship between the independent variables like interest rates and exchange rate was moderate negative. The model proposes that -71.4% correlations between interest rates and exchange rates. This was statistically insignificant due to p value of 0.0546. The confirmation of the correlation between the dependent variable FSE-100 index and the independent variable exchange rate has been proved through the relationship between the interest rate and the exchange rate. Exchange rate → GDP The exchange rate and the GDP growth have a negative and weak correlation. The analysis deduced a -31.2% correlation, which was actually a negative correlation between the growth of GDP and the exchange rate. While the statistically insignificant relationship between the GDP and interest rate means that the depreciation of currency results to decrease in the growth of GDP. Interest rate → GDP The growth of GDP and interest rate relationship shows a moderate positive correlation. The above model shows a value of 4.0%), suggesting that correlation between the interest rate and the GDP growth was moderate negative in nature and was statistically insignificant. CONCLUSION The paper has given a report concerning the determinants of stock market in Finland. The study used change in stock prices as the variable of interest while exchange rate, interest rate and GDP growth rate were used as the independent variables. The study showed a positive and direct correlation between the macroeconomic variables like exchange rate, and GDP growth rate with stock prices of FSE-100 index. On the other hand the negative impact was shown on the stock prices of FSE-100 index by the interest rate. The variations depicted in the macroeconomic variable, for example, interest rate, exchange rate, and GDP growth rate have an impact on the stock prices of FSE-100 index. There were a number of variables within the economy that affect the stock prices of a nation’s stock exchange. However, three different macroeconomic parameters were used in finding out the impact they have on stock prices of FSE-100 index. The analysis of these research information covered data for about 10 years, that is, from 2003-2013. From the data analysis, that is, the table showing R2, which is the coefficient of determination, was the basis of checking whether the overall model fitted or not. It showed the absolute variations in the independent variables. The model gave suggestion that the independent variables like GDP growth rate and exchange rates are directly and positively correlated with the stock prices of FSE-100 index, while interest rate showing inverse and negative correlation with respect to the stock prices of FSE-100 index. In order to know about the statistical significance, the research study was put into T-test and F-test. The T-test is used for individual variable significance. Macroeconomic variables like exchange rates were statistically significant, while GDP growth rate and interest rate are statistically insignificant. According to the Pearson Correlation Model, the relationship depicted from the exchange rates and stock prices of FSE-100 index deduce a strong positive correlation with the stock prices and are also statistically significant. This study gave results that were the same as the research of Bruce (2010). Moderate positive correlation between stock prices and exchange rate was statistically significant, confirming the result of the study by Dorodnykh (2013). The correlation of growth rate of GDP and stock prices of Finland stock exchange was positive but very weak and also it is statistically insignificant. Due to this feature of statistical insignificance, it required less attention. The association between the stock prices and the interest rate was moderate negative. This meant that an increase in interest rate resulted to a decrease in stock prices, confirming the previous research studies. For instance, the research by Ehrhardt & Brigham (2010) indicated a negative correlation between stock prices and interest rate. In addition, the conclusion of the analysis of independent variables indicated no such strong correlation within the independent variables. The analysis has shown that all the variables indicate direct or indirect, positive or negative relationship, though not that much strongly considered to be important. Recommendation Since this study only used three variables to explain the changes in stock prices, we strongly suggest that further work be done to empirically analyse the influence of all macroeconomic variables on stock prices. The paper also suggest that an equivalent study be done but with a yearly data so as to verify the results of this study. Reference List Abbas Z. 2010. Dynamics of Exchange Rate and Stock Prices: A study on Emerging Asian Economics. Baker, H. K., & Kiymaz, H. 2013. Market microstructure in emerging and developed markets: Price discovery, information flows, and transaction costs. Baker, H. K., & Nofsinger, J. R. 2010. Behavioural finance: Investors, corporations, and markets. Hoboken, N.J: Wiley. Barnes, P. 2009. Stock market efficiency, insider dealing and market abuse. Farnham, Surrey, England: Gower. Bathe, D. 2008. Common risk factors in the German stock market: Are returns predictable?. München: GRIN Verlag GmbH. Bruce, B. R. 2010. Handbook of behavioural finance. Cheltenham, UK: Edward Elgar. Dorodnykh, E. 2013. Stock market integration: An international perspective. Edwards, S., & Garcia, M. G. P. 2008. Financial markets volatility and performance in emerging markets. Chicago: University of Chicago Press. Ehrhardt, M. C., & Brigham, E. F. 2010. Corporate finance: A focused approach. New York: South-Western [u.a.. In Boubakri,Narjess, ., In Cosset,Jean-Claude, ., & Choi,J, J. 2011. Institutional Investors in Global Capital Markets. Bingley: Emerald Group Publishing Limited. Verbeke, A., & Merchant, H. 2012. Handbook of research on international strategic management. Cheltenham: Edward Elgar. Verma, N. M. P. 2013. Recession and its aftermath: Adjustments in the United States, Australia, and the emerging Asia. India: Springer. Appendices Table 1. Descriptive statistics Descriptive Statistics Mean Std. Deviation N Change in Stock prices (%) .82 4.642 131 Interest Rate (%) 1.271679 12.6975299 131 Exchange Rate (%) .130611 .9140878 131 GDP growth rate (%) 1.09 2.588 131 Table 2. Summary of coefficient analysis Coefficient of Determination Variables Coefficients Std. Error t value R partial Constant 0.742 1.669 Interest rate -0.002 0.048 -0.051 -0.005 Exchange rate 0.403 0.701 0.574 0.051 GDP rate 0.030 0.174 0.172 0.15 Table 3. Analysis of Variance ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 19.135 3 6.378 .291 .832b Residual 2782.582 127 21.910 Total 2801.718 130 a. Dependent Variable: Change in Stock prices (%) b. Predictors: (Constant), GDP growth rate (%), Interest Rate (%), Exchange Rate (%) Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 Sig. F Change 1 .083a .007 -.017 4.681 .007 .291 3 127 .832 a. Predictors: (Constant), GDP growth rate (%), Interest Rate (%), Exchange Rate (%) Read More