THE RELATIONSHIP BETWEEN SHARE PRICES AND INTEREST RATES: EVIDENCE FROM KENYA Dan Chirchir1 School of Business, University of Nairobi, Nairobi, Kenya Correspondence: Dan Chirchir, Department of Finance and Accounting, School of Business, University of Nairobi, P.O Box 30197-00100, Nairobi, Kenya Tel: +254 723 838534 E-mail: dchirchir@uonbi.ac.ke Abstract The changes in interest rates have a diverse effect across the economic spectrum in any country The sectoral and economy wide effects of interest rates may ultimately be reflected in the stock prices Policy makers, scholars, economists, business owners, regulators and the general Kenyan public are grappling with figuring out the relationship of stock prices and interest rates The objective of this research is to examine how changes in interest rates (represented by the weighted average lending rate by commercial banks in Kenya) and stock prices (proxied by the NSE 20 share index) are related to each other for Kenya over the period October 2002- September 2012 The research used Toda and Yamamoto (1995) method to determine the relationship between stock prices and interest rates This method is applicable “whether the Vector Auto Regression (VAR) may be stationary (around a deterministic trend), integrated of an arbitrary order, or cointegrated of an arbitrary order” (Toda, Yamamoto, 1995, pp 227) The results therefore indicated that there is no significant causal relationship between interest rate and share price As regards the sign of causality, negative causality exists in both directions Table of Contents Chapter One Introduction 1.1 1.2 1.3 1.4 Background Research Problem Research Objective Value of the Study Chapter Two Literature Review 2.1 2.2 2.3 2.4 2.5 2.6 2.7 Introduction Share price and markets theories Interest rate theories Theories linking interest rates and share prices Research hypothesis Empirical evidence Conclusion Chapter Three Research Methodology 3.1 3.2 3.3 3.4 3.5 Introduction Research design Population and sample design Data collection Data analysis Chapter four 11 Data Analysis, Results and Discussions .11 4.1 4.2 4.3 Introduction 11 Data analysis and results 11 Discussion 14 Chapter five 16 Summary, Conclusion and Recommendations 16 5.1 5.2 Summary of findings 16 Conclusion 16 ii 5.3 5.4 Limitations of the study 16 Recommendations 16 References .17 List of Tables Table 1: Results of the Augmented Dickey-Fuller unit root test in levels 13 Table 2: Results of the Augmented Dickey-Fuller unit root test in first difference 13 Table 3: Results of the Toda-Yamamoto Causality Test 14 List of Figures Figure 1: Graphical analysis of share prices series 12 Figure 2: Graphical analysis of interest rates series 12 iii LIST OF ABBREVIATIONS AIC Akaike Information Criterion CBK Central Bank of Kenya CBR Central Bank Rate DMAX Maximum order of intergration EMH Efficient Market Hypothesis MWALD Modified WALD NSE Nairobi Stock Exchange VAR Vector Auto Regression iv Chapter One Introduction 1.1 Background The issue of whether stock prices and interest rate are related or not, is an important one especially with increased international trade and the integration of the global financial markets If stock prices and interest rates are related and the causation runs from interest rates to stock prices then crises in the stock markets can be prevented by controlling the interest rates Moreover, developing countries can exploit such a link to attract foreign portfolio investment in their own countries Similarly, if the causation runs from stock prices to interest rates then authorities can focus on domestic economic policies to stabilize the stock market Research gap There are studies done by Hsing (2004), Arango (2002), Gazi and Mahmudul (2009) in different countries that have found a negative relationship between interest rates and share prices However, Lee (1997) found the relationship changing gradually from a significantly negative to no relationship, or even a positive although insignificant relationship Gupta, Chevalier and Sayekt (n.d) in their research failed to establish any consistent causality relationships between interest rates and share prices Therefore, there is still no unanimity in the study of the relationship between interest rate and share prices 1.2 Research Problem Undoubtedly, the changes in interest rates have a diverse effect across the economic spectrum in any country For instance, interest rates will impact the cost of doing business The sectoral and economy wide effects of interest rates may ultimately be reflected in the stock prices On the converse, performance of companies and businesses in Kenya may impact on economic growth The economic growth may eventually affect levels of interest rates Policy makers, scholars, economists, business owners, regulators and the general Kenyan public are grappling with figuring out the relationship of stock prices and interest rates Research question The research question is: Is there a relationship between stock prices and interest rates? 1.3 Research Objective The objective of this research is to examine how changes in interest rates (represented by the weighted average lending rate by commercial banks in Kenya) and stock prices (proxied by the NSE 20 share index) are related to each other for Kenya over the period October 2002- September 2012 1.4 Value of the Study The results of this study will help investors to manage well their portfolios of investments The findings can be used by regulators such as CBK in managing the interest rate policy This linkage of stock price and interest rates has implications for the management of publicly owned companies in Kenya The empirical findings of this proposed research will contribute to the body of knowledge Chapter Two Literature Review 2.1 Introduction The literature review is organized into four main areas The first is the review of the theories that affect the individual variables that form part of the research question namely share prices and interest rates The second section summarizes the conceptual framework and the hypothesis that link share prices to interest rates The third section reviews the empirical evidence Finally, the chapter concludes with summary of how this research will contribute to the existing literature 2.2 Share price and markets theories The pricing of shares in a stock market is one of the most important subjects in finance The investors and other stakeholders in the capital market are interested in understanding the factors that affect the movement of share prices There are two broad theories that attempt to explain the movement in share prices in stock market The first is the Efficient Market Hypothesis which basically contends that all information affecting a share price is reflected immediately in its price At the heart of this hypothesis is the assumption that investors are rational The other theory is behavioural finance which contends that investors are not always rational and that their behavior affects the share prices The two theories are discussed below: Efficient Market Hypothesis Fama (1965) published his dissertation arguing for the random walk hypothesis He defined market efficiency as follows: "In an efficient market, competition among the many intelligent participants leads to a situation where, at any point in time, actual prices of individual securities already reflect the effects of information based both on events that have already occurred and on events which, as of now, the market expects to take place in the future In other words, in an efficient market at any point in time the actual price of a security will be a good estimate of its inherent value." Behavioral finance theory The assumption that investors are rational and behave in a rational manner is at the core of the EMH Over the years another school of thought has emerged This school of thought hypothesizes that investors are not always rational and therefore the study of market efficiencies and security pricing should take into account the behavior of investors This school of thought has evolved into a branch of finance known as behavioural finance Sewell (2005) defined behavioural finance as the study of the influence of psychology on the behaviour of financial practitioners and the study of subsequent effect of markets Belsky and Gilovich (1999) referred to behavioural finance as behavioural economics in that "Behavioural economics combines the twin disciplines of psychology and economics to explain why and how people make seemingly irrational or illogical decisions when they spend, invest, save, and borrow Much of economic and financial theories presume that individuals act rationally and consider all available information in the investment decision-making process 2.3 Interest rate theories Interest rate is the price paid for money borrowed which is in turn invested in viable economic activities with a view of generating returns Interest rate in any country is determined by a number of factors The key theory is the demand for money and supply of money framework Some of the other factors include the growth in the economy, monetary policy driven by central banks, rate of inflation among others 2.4 Theories linking interest rates and share prices Theoretical framework Fama (1981) argues that expected inflation is negatively correlated with anticipated real activity, which in turn is positively related to returns on the stock market Therefore, stock market returns should be negatively correlated with expected inflation, which is often proxied by the short-term interest rate In theory, the interest rates and the stock price have a negative correlation (Hamrita & Abdelkader, 2011) This is because a rise in the interest rate reduces the present value of future dividend’s income, which should depress stock prices Conversely, low interest rates result in a lower opportunity cost of borrowing Lower interest rates stimulate investments and economic activities, which would cause prices to rise 2.5 Research hypothesis Null hypothesis  There is no significant causality relationship between stock prices and interest rates Alternative hypothesis  There is a significant causality relationship between stock prices and interest rates 2.6 Empirical evidence Hamrita and Abdelkader (2011) examined the multi-scale relationship between the interest rate, exchange rate and stock price using a wavelet transform in US over the period from January 1990 to December 2008 The exchange rate returns and stock index returns were found to have a bidirectional relationship in this period at longer horizons Gazi and Mahmudul (2009) sought to find evidence supporting the existence of share market efficiency based on the monthly data from January 1988 to March 2003 and also shows empirical relationship between stock index and interest rate for fifteen developed and developing countries For all of the countries it is found that interest rate has significant negative relationship with share price and for six countries it is found that changes of interest rate has significant negative relationship with changes of share price Hsing (2004) adopted a structural VAR model that allows for the simultaneous determination of several endogenous variables such as, output, real interest rate, exchange rate, the stock market index and found that there is an inverse relationship between stock prices and interest rate Lee (1997) used three-year rolling regressions to analyze the relationship between the stock market and the short-term interest rate He found that the relationship is not stable over time It gradually changes from a significantly negative to no relationship, or even a Positive, although insignificant relationship Ishfaq, M., Ramiz, Rehman & Awais, Raoof (2010) examined the relationship between stock return, interest rate and exchange rates in Pakistani economy over the period of 1998-2009 A multiple regression model was applied to test the significance of change in interest rate and exchange on stock returns The results indicated that both the change in interest rate and change in exchange rate have a significant impact on stock returns over the sample period Hashemdah and Taylor (1988) found bi-directional relationship causality present in regression models between money supply and stock return However, with respect to interest rates the result was inconclusive Gupta et al (n.d) studied the relationship between exchange rate, interest rate and stock prices in Indonesia The study was conducted for five year period from 1993 to 1997 which was divided into three sub periods The overall evidence, however, failed to establish any consistent causality relationships between any of the macro economic variables under study 2.7 Conclusion From the literature and empirical evidence review there is mixed findings There are studies done by Hsing (2004), Arango (2002), Gazi and Mahmudul (2009) in different countries that have found a negative relationship between interest rates and share prices However, Lee (1997) found the relationship changing gradually from a significantly negative to no relationship, or even a positive although insignificant relationship Gupta et al (n.d) in their research failed to establish any consistent causality relationships between interest rates and share prices Therefore, there is still no unanimity in the study of the relationship between interest rate and share prices This proposed research will contribute to the growing literature by employing the Toda and Yamamoto (1995) method in the Kenyan scene Toda and Yamamoto (1995) proposed a simple procedure requiring the estimation of an “augmented” VAR, even when there is cointegration of different orders, which guarantees the asymptotic distribution of the MWALD statistic Chapter Three Research Methodology 3.1 Introduction Research methodology refers to the procedures to be adopted to obtain answers to the research question and the tasks needed to complete the different components of the research process This chapter is organized as follows: section 3.2 deals with research design, section 3.3 defines the population and sample, section 3.4 covers data collection, and section 3.5 addresses data analysis 3.2 Research design A research design is a plan, structure and strategy of investigation so conceived as to obtain answers to research questions or problems The study will use an empirical design in which the secondary data will be analyzed and the research hypothesis tested This design will help to build on what is already known in the subject area The research is designed to perform causality test The Toda and Yamamoto (1995) method of testing causality is employed to test the relationship between stock prices and interest rates in Kenya In summary, in order to apply Toda and Yamamoto method, firstly, the VAR order, k, and the maximum order of integration of the variables, dmax, should be determined in the VAR model To employ causality test, modified Wald test (MWALD), is applied to the first k VAR coefficients to investigate causality 3.3 Population and sample design The two variables used in the research are interest rates stated as the monthly weighted average lending rate by commercial banks in Kenya and the NSE share index The NSE share index used in the study is NSE 20 share index This index tracks the performance of the shares of twenty companies as selected by the management of NSE from time to time The sample data is based on the NSE stock index values for the time periods between October 2002 and September 2012 The prevailing interest rates for the same time period of between October 2002 and September 2012 are selected for use in the research The 10 year period provides 120 data points which are considered adequate In addition it is the most recent 10 year period at the time of this research 3.4 Data collection The data used in this research is secondary data The monthly data on the NSE share index (1964=100) was obtained from the NSE Monthly data on the average interest rate was obtained from CBK 3.5 Data analysis Traditionally to test for the causal relationship between two variables, the standard Granger (1969) test has been employed This test states that, if past values of a variable Y significantly contribute to forecast the value of another variable Xt+1 then Y is said to Granger cause X and vice versa To analyze Granger causality between interest rate and stock market price the research will use Toda, Yamamoto (1995) procedure, as explained below: Toda and Yamamoto Model The integrated properties of the stock price series and interest rates series are not important in Toda and Yamamoto method, providing that the risk of misspecification of the order of integration of the series is minimized Thus, the causality relationship between series which are integrated different orders can be investigated In order to apply Toda and Yamamoto method, firstly, the VAR order, k, and the maximum order of integration of the variables, dmax, should be determined in the VAR model The sum of k and dmax, is taken into consideration as the total order of VAR, that is (k+dmax)th order of VAR is estimated Then, in order to employ causality test, modified Wald test (MWALD), proposed by Toda and Yamamoto (1995), is applied to the first k VAR coefficients to investigate causality This test has an asymptotic chi square (χ2) distribution when a VAR (k + dmax) is estimated A Monte Carlo experiment, presented in Zapata and Rambaldi (1997), provides evidence that the MWALD test has a comparable performance in size and power to the likelihood ratio and WALD tests if (i) the correct number of lags for estimating k + dmax is identified and (ii) no important variables are omitted, provided a sample of 50 or more observations is available According to Zapata and Rambaldi (1997), the advantage of this procedure is that it does not require the knowledge of cointegration properties of the system Moreover, according to Toda and Yamamoto, the MWald statistic is valid regardless whether a series is I (0), I (1) or I (2), non-cointegrated or cointegrated of an arbitrary order To analyse Granger causality between interest rate and stock market price by using Toda and Yamamoto procedure, the following VAR system should be estimated dmax k k dmax int = α0 + ∑ α1iint-i + ∑ α2iint-i + ∑ λ2jstpt-j + ∑ λ2jstpt-j + µ1t i=1 k j=k+1 dmax i=1 j=k+1 k dmax stpt = β0 + ∑ β1istpt-i + ∑ β2istpt-i + ∑ Φ2jint-j + ∑ Φ2jint-j + µ2t i=1 j=k+1 j=k+1 i=1 Where int is the weighted average lending rate by commercial banks in Kenya and stpt is the NSE 20 share index 10 Chapter four Data Analysis, Results and Discussions 4.1 Introduction This chapter provides a summary of the data analysis, results of the study and the discussion on the results of the study The chapter is organized as follows: section 4.2 describes the data analysis and the results of the study and section 4.3 discusses the implication of the findings of the study 4.2 Data analysis and results We obtained the data for the stock prices and corresponding interest rates for the period between October 2002 and September 2012 The data for share prices and interest rates were obtained from NSE and the CBK respectively Based on the monthly data obtained we generated the two series one for interest rates and the other for share prices and plotted on separate graphs By observing the trends on the two graphs in figures one and two below, one for interest rates and the other share prices we note an important relationship The two series trend in opposite directions For example, between 2002 and 2005 the share prices trended upwards while the interest rates were trending downwards However, for the period 2007/2008 the share prices plummeted sharply while the interest rates increased marginal The correlation coefficient is negative 0.356 This indicates weak negative correlation The following figures one and two depict the graphical analysis of the share prices and interest rates series: 11 Figure 1: Graphical analysis of share prices series SHAREPRICE 6,000 5,000 4,000 3,000 2,000 1,000 03 04 05 06 07 08 09 10 11 12 Year (2002-2012) Figure 2: Graphical analysis of interest rates series INTERESTRATE 22 20 18 16 14 12 10 03 04 05 06 07 08 09 10 11 12 Year (2002-2012) 12 We therefore perform causality test in order to empirically establish any relationship between interest rates and share prices Toda Yamamoto method for causality test Firstly, we perform unit root tests on the time series to investigate whether they are stationary or not The Augmented Dickey-Fuller (ADF) unit root test is used for this purpose The tests are based on the null hypothesis (H0): interest rate is not I (0) and share price is not I (0) If the calculated ADF statistics are less than their critical values from Fuller’s table, then the null hypothesis (H0) is accepted and the series are nonstationary or not integrated of order zero The test is repeated until we obtain the level in which the series become stationary We then determine dmax as the maximum order of integration The results of the unit root tests are summarised below: Table 1: Results of the Augmented Dickey-Fuller unit root test in levels Variables Test Critical Value (1%) Test Statistic P values Interest rate -3.486551 -1.195912 0.6747 Share price -3.486551 -2.465983 0.1264 The results in table above suggest that none of the variables are stationary, that is, integrated of order since the variables are not statistically significant at 1% However, the results in table below suggest that both variables are stationary, that is, integrated of order since the variables are statistically significant at 1% in their first difference Therefore maximum order of integration (dmax) is Table 2: Results of the Augmented Dickey-Fuller unit root test in first difference Variables Test Critical Value (1%) Test Statistic P values Interest rate -3.486551 -8.173242 0.0000 Share price -3.486551 -9.966756 0.0000 Having determined that dmax as 1, we then proceed in estimating the lag structure of 13 a system of VAR in levels and our results indicate that the optimal lag length (VAR order k) using AIC optimal lag technique to be We then estimate a system of VAR in levels with a total of (dmax+k) lags Therefore the lag length is determined to be (6+1) The MWALD test statistic is then computed using the systems of VAR computed above The MWALD statistic will be asymptotically distributed as a Chi Square, irrespective of whether the series are I (0), I (1) or I (2), non-cointegrated or cointegrated of an arbitrary order The result of the Toda-Yamamoto causality test is shown below: Table 3: Results of the Toda-Yamamoto Causality Test Null Hypothesis Stock price does not cause dmax and Var(k) MWALD P values The Sign of the Sum of statistic Lagged Coefficients (1,7) 9.801052 0.7766* (-) (1,7) 9.801052 0.8655* (-) interest rates Interest rates does not cause stock price *Insignificant at 5% Based on the results of the MWALD test statistic as well as its p-values we fail to reject the two null hypotheses at 5% significance level respectively The results showed in the table indicate that there may be no significant causal relationship between interest rate and share price in both directions As regards the sign of causality, negative relationship albeit insignificant exists in both directions 4.3 Discussion The study has established insignificant negative relationship between share price and interest rates When interest rates increase the share prices decline which attests to the expected relationship as proposed by Fama (1981) The findings have implications for investors, investment managers, regulators, listed companies, financial institutions and other market players 14 Portfolio managers are mandated to maximize the wealth for their clients by optimizing portfolio values The sharp fluctuations in share prices as a result of oscillations in interest rates cause panic among portfolio managers This may predispose them to liquidate some of the holdings in their portfolios This may result to a slump in the stock market On the contrary, when the interest rates decline the portfolio of equity securities may appreciate in value Therefore, the portfolio managers need a thorough understanding of the relationship between interest rates and share prices Based, on the results of this study, portfolio managers are better when they dispose shares in their portfolio if they predict increased interest rates On the flip side, the portfolio managers should increase their positions in equity shares when they forecast a decrease in interest rates The regulators such as CBK who are in charge of monetary policy have a reason to be concerned with volatility in interest rates and the resulting impact on the stock market The findings in this research will assist CBK in mastering the relationship between interest rates and share prices This may help them employ the monetary policy tools at their disposal to control the interest rates and consequently averting adverse effect on the stock market Based on the finding of this research, the consistent sharp increase in interest rates may erode the value of shares The CBK may intervene to stabilize the interest rates The stock market is an important institution for price discovery The forces of demand and supply in the market determine the market price of shares This market price is useful in valuation of companies, evaluating portfolio performance, facilitating transfer or disposal of securities among others High volatility in the interest rates and by extension the stock market will have an adverse effect on pricing efficiency If volatility persists for a long time there will be a disruption in the price discovery process in the market This disruption in price discovery process renders the stock market inefficient 15 Chapter five Summary, Conclusion and Recommendations 5.1 Summary of findings The study examined the relationship between interest rates and stock prices in Kenya for the period between October 2002 and September 2012 Based on the results of the MWALD test statistic as well as its p-values the two null hypotheses were accepted at 5% significance level The results therefore indicated that there is no significant causal relationship between interest rate and share price As regards the sign of causality, negative causality exists in both directions The findings are similar to those of Gupta et al (n.d) They did not find any consistent causal relationship between interest rates and share prices in Indonesia However, this research finds negative relationship albeit weak similar to other studies carried in different countries 5.2 Conclusion The empirical evidence from the study shows that there is no significant causal relationship between interest rate and share price 5.3 Limitations of the study There were no limitations in so far as data collection and analysis is concerned However, this research considered only two variables; interest rates and share prices The study was limited to average monthly data as opposed to more frequent data observations such as daily or weekly which may have an impact on the findings 5.4 Recommendations This research considered only two variables; interest rates and share prices Another study may be done using additional variables We, also suggest that the significance of our results could possibly be improved upon by applying daily or weekly data The use of more frequent observations may better capture the dynamics of stock prices and interest rates interrelationships 16 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