Influence of Macroeconomic Variables on KSE 100-Index in Arbitrage Pricing Theory (APT) Framework in Order to Determine the Casualty of Variables

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1 ASIAN JOURNAL OF EDUCATIONAL RESEARCH & TECHNOLOGY Vol. 5 (2), July 2015: ISSN (Print): Website: ISSN (Online): RESEARCH ARTICLE Influence of Macroeconomic Variables on KSE 100-Index in Arbitrage Pricing Theory (APT) Framework in Order to Determine the Casualty of Variables Bilal Aziz 1, Sundus Shah Nawaz 2, Athar Ashraf 2 and Muhammad Zubair 2 1 Professional Development Center (PDC), IBM, University of Engineering and Technology (UET) Lahore, Pakistan 2 University of Lahore, Pakistan biiilal@live.com Received: 15 th April 2015, Revised: 5 th May 2015, Accepted: 12 th June 2015 ABSTRACT The objectives of this study are analyzing the influence of Macroeconomic Variables on the Pakistani Stock Exchange Market in the Arbitrage Pricing Theory (APT) framework and deciding the direction of causality of variables. This study encompasses four Macroeconomic Variables (oil price, gold price, Inflation, Foreign Exchange Rate USD$/PKR) and the major Pakistani Stock Market Index (the Karachi Stock Exchange Index-100). Time series monthly data for almost eleven years period, which spans from July 2003 to August 2014, has been used. The relationship between KSE-100 Index return and four macroeconomic explanatory factors, has been designed in a multiple regression model. In addition Granger Causality Test is used for determining the direction of causality of each variable under study. E-Views Software for testing a multiple regression model has been used for this time series data. This study concludes that Gold price and Inflation has negative influence on KSE-100 Index returns while oil price has positive impact on KSE-100 Index Returns in Pakistan. The Exchange rate does not induce any significance influence on KSE-100 Index returns while its relation is negative with KSE-100 Index. Besides this, there is unidirectional causality running from Oil price, Gold price and Inflation to KSE-100 Index return and from KSE-100 Index return to US$/PKR Exchange rate. The surprising positive oil-stock relationship result in Pakistan is justifying Cost-Push Inflation theory. Key words: Macroeconomic Variables, Multiple Regression Model, Granger Causality Test, Pakistani Stock Exchange, KSE-100 Index Stock Returns, Cost Push Inflation. INTRODUCTION Stocks are affected by number of direct and indirect factors and events. Not only the internal factors such as dividends, bonuses, stock split influences stock prices but external factors also do impact. The external factors, which are beyond the control of firm, may include economic trends, world events, technological revolution, investors confidence, etc. Common stock returns are influenced by all kinds of properties, behavioural reaction of a large group of decision makers, changes of political and economic conditions, risk and many known and unknown factors. Investors do comparison of all of these factors and feel comfort by knowing what basic elements of his country s economy leads common stock prices. By concerning long term trends basic elements can be analyzed and evaluated and ultimately an expectable fair prices and real rate of return can be woven from investment. After acknowledging that besides market factor, some other explanatory variables also explain for part of asset returns not detected by beta, Ross (1976) suggested the Arbitrage Pricing Theory (APT). The Arbitrage pricing theory (APT) is basically a substitute to Capital Asset Pricing Model (CAPM) with similarity of being an equilibrium model. By using factor analysis as a Statistical tool, APT allows the determination of equilibrium returns of assets by many variables. Not only one factor such as beta but many factors determine the equilibrium returns of assets. But there were also many criticisms. The major criticism was derivation of variables statistically without pre-specification of variables. Roll and Ross (1980) accepted this inadequacy of APT in their first APT study. They stated that although the statistical tool, factor analysis derive the factors but these

2 factors should be primary economic factors include as interest rates, Gross National Product (GNP) etc. They gave suggestions finally that such economic factors should be investigated, that are proxies by derived variables in Arbitrage Price Theory (Roll and Ross, 1980). In APT macroeconomic factors were used as proxies for the undetermined factors for the first time by Chen, Roll and Ross (1986). Their study was an attempt to explore that stock equity return is the linear function of macroeconomic variables and the factor specific beta coefficient represents sensitivity to changes in each factor. The general opinion is that rise and fall of the prices of commodity are affected by general macroeconomic variables consisting of inflation, exchange rates etc. (Hammoudeh et al., 2008). Both commodities oil and the gold have received attention due to their price volatilities and great economic use. The world s very frequent merchandizing good, the crude oil is used for investment purpose due to its volatility in price. Gold is considered the leader among precious metals because other metals price more parallel with the charge of gold prices (Sari et al., 2010). STOCK MARKET OF PAKISTAN Pakistan includes three organized Capital markets, namely, Karachi Stock Exchange (KSE) in Karachi, Lahore Stock Exchange (LSE) in Lahore, and Islamabad Stock Exchange (ISE) in the capital city Islamabad. This study is focusing on the single biggest and above all most liquid security market in Pakistan i.e. Karachi Stock Exchange. KSE includes both local and foreign listing and both domestic and foreign traders. KSE has won the award in 2002, namely, Best performing stock exchange of the world award *1. Till year 2009, KSE has 200 members/brokers as owners, 1850 terminals for trading existing at the end of broker, 654 listed companies, 4 indices including KSE-100, KSE-30, KSE-All Share Index and KMI-30 and its Market Capitalization is about US$ OBJECTIVES OF STUDY This study is about determining the influence of fluctuations of four major macroeconomic variables including oil prices, gold prices, inflation and foreign exchange rates on Karachi Stock Index-100 (KSE-100) returns. In methodology firstly, Ordinary Least Square technique has been used and it has been observed that each macroeconomic variable under study has its individual influence on stock return using a multi-regression model. Secondly, Granger Causality Test has been used to examine the direction of pairwise causality of the variables used in this study. LITERATURE REVIEW Chen et al. (1986) used macroeconomic factors for judging U.S. stock returns and applied the framework of Arbitrage Price Theory (APT). They analyzed seven macroeconomic variables including the term structure, the industrial production, the risk premium, the inflation, the market return, the consumptions and the oil prices from the time interval of January 1953 to November According to the empirical results a firm relationship was observed between the macroeconomic variables and the expected returns on shares for the time span examined. Cheng et al. (2006) explained the relationship between macroeconomic variables and the Malaysian stock indices for the period ranging from 1996 to Their results showed that there is long-run relationship of the studied factors including the rate of inflation, the index of industrial production, prices of crude oil and rate of Treasury Bills with the stock index of Malaysian capital market. Türsoy et al. (2008) applied the test of the Arbitrage Price Theory (APT) in stock market of Turkey. Kandir (2008) implicated Arbitrage Price Theory (APT) tests in Istanbul Stock Exchange of Turkey. His research results revealed that significant findings were analyzed for the impact of some factors on every portfolio returns. These variables included foreign ~ 117 ~

3 exchange rates, interest rate and world market return. But the findings of rate of inflation did not prove significant for all the twelve but only three portfolios. Oil Prices is one of the fundamental economic factors that cause the fluctuations in the economy of world. Oil prices remained stable until Since then, world economy was greatly impacted by influence of oil price shocks (Hamilton, 2003). The critical role of oil induces the economist to expect correlation between fluctuations in oil price and changes in stock price accordingly (Huang et al., 1996). Also Jones and Kaul (1996) are pioneer economists that studied oil-stock relationship by employing cash-flow/divided valuation model, in four advanced economies. They concluded that influence of shocks of oil price, in United States and Canadian financial market, is significance but insignificant for Japan and UK market. Due to critical role of oil in an economy, many studies on oil price and stock price relationship were conducted but mostly in developed economies. The emerging economies of developing country are importers of oil so under-developing countries are receiving special attention to interpret the interaction between oil price s volatilities and performance of financial market. Gold, a precious metal, is a store of value while stocks are viewed as return on the value, (Levin and Wright, 2006). In nineteenth century this considering was appealing due to stability in political and economic environment in USA a developed country. But in severe declining political and economic conditions, when stock prices declines then gold is used as an alternative investment tool. Moore (1990) studied the capital market and results showed that capital markets decline when gold prices rise. Inflation is that rate upon which prices level, of the commodities as well as services, boosts and it influences not only the buying power of people but impacts on security market also. Negative correlation between inflation and stock market prices is characteristic of many major industrial countries. Rise in inflation increases the nominal interest rate and ultimately results in rising in the discount rates. Dividend Discount Model implements that high discount rate resulting in lowering of stock prices and ultimately the stock returns. Pakistan is facing high rate of inflation so it may results in lowering stock prices and returns. Study of inflationary impacts in an under developing country always remain interesting for the economists. Chang and Tan (2002), Mousa et al. (2002), Al-Rjoub (2005), studies has proved this negative influence of inflation on stock prices and returns. The Foreign Currency Exchange rate is rate at which the local currency is converted into currency of any other country and mostly expressed in terms of US dollar. The local currency depreciation decreases foreign currency exchange rate and local currency appreciation increases foreign currency exchange rate. Exchange rate fluctuations impact the international trade, thereby influence the stock market. The depreciation of local currency in an import dominated country hits the industrial sector by exerting high pressure on the costs such as oil, imported coal, metal, minerals thus reduces the profit ultimately. So in case of depreciation of local currency in an import dominated country, foreign exchange rate has negative influence on stock prices and returns, (ASSOCHAM INDIA, 2012). The currency appreciation produces positive influence on the local stock market for any import dominating country and produces negative influence for any export dominating country, (Ma and Kao, 1990). DATA & RESEARCH METHODOLOGY In this study a Multiple Regression Model has been used to examine the impacts of macroeconomic variables on KSE-100 Index. The reason for selection of a Multiple Regression Model is that this study sample is justifying the Ordinary Least Square (OLS) method s assumption i.e., Time series data is stationary at level. If time series data is stationary at first difference then Co-Integration is used instead of Ordinary Least Square Method. The following Multiple Regression Model is used in order to examine how the above identified macroeconomic explanatory variables can explain KSE-100 index returns, ~ 118 ~

4 KSE t = β 0 + β 1 OIL t + β 2 GLD t + β 3 INFL t + β4 FRX t + t.(1) Where, β 0 = Constant β β 4 =Co-efficient of Variables t = Residual error Karachi Stock Exchange-100 Index returns that are calculated by using the following equation: R t = ln(p t) ln(p t-1).(2) Where, R t = Return for month t, ln = Natural log P t = Closing values of KSE-100 Index for month t P t-1 = Closing values of KSE-100 Index for month t-1 The data for KSE-100 Index has been obtained from Yahoo Finance. The source of explanatory variables, including Oil prices and Gold prices, is Index Mundi Pakistan Economic data. Inflation rate has been gotten from Trading Economics while the source of Exchange rate is State Bank of Pakistan. Before doing empirical analysis, the natural log of all the independent variable values except inflation, has been taken so that the large values can be converted into smaller one on the natural log scale. Then the first logarithmic difference, of all explanatory variables except inflation rate, has been taken to convert them into a monthly continuous increase rate as follows, G(V i) t = ln(v i) t ln(v i) t-1.(3) Here, G(V i) t = Continuous growth of variable i for month t ln = Natural log, (V i) t = Variable i for month t, (V i) t-1 = Variable i for month t-1 In addition, for justifying the results of a Multiple Regression Model, Granger Causality Test is used for testing the direction of causality for two variables x t and y t while estimating the Vector Autoregressive model (VAR) as follows, y t = a 1 + i x t-i + j Y t-j + e 1t.(4) x t = a 2 + i x t-i + j Y t-j + e 2t.(5) Where, this has been assumed that ϵ yt and ϵ xt are uncorrelated white noise error terms. In order to meet aim of this study, the EXCEL for ordinary calculations and econometrical software program E Views were applied on the data. EMPIRICAL RESULTS 1. Descriptive Statistics: Table Ι: Descriptive Statistics KSE OIL GLD INFL FRX Mean Median Maximum Minimum Std. Dev Skewness Kurtosis Jarque-Bera Probability * * * * * Observations Note: Asterisk (*) denotes the null of normality was rejected at 1% significance level. ~ 119 ~

5 The properties of 133 observations (i.e. monthly data from July 2003 to August 2014) of dependent variable (KSE 100 Index) and four Explanatory Variables (oil, gold, inflation and exchange rate) have been described in Table Ι. The measures of central tendency i.e. Mean and Median are showing that inflation has the greatest monthly average growth rate and oil has the lowest monthly average rate. Also it can be analyzed from Table Ι that the mean and median values of each variable are not equal and are occurring at irregular points so there is not a normal distribution but asymmetrical. In terms of Standard deviation, the variability of data from the monthly average values, there is more volatility of inflation and foreign exchange rate has lesser volatility from mean values. Skewness and Kurtosis Results are also showing that returns and growth rate have nonsymmetric distribution. The Skewness results, which describes the direction of fat tails of asymmetrical distribution, shows that only one variable has positive skewness i.e. inflation. It is indicating that fat tails are directing towards right hand side relatively with left hand side of distribution. In contrast, four variables i.e. KSE-100 Index, oil, gold and exchange rate have negative skewness depicting the direction of fat tails towards left hand side of distribution. Kurtosis, another measure of normality of distribution, calculates the frequency of extreme movements in either direction. As the Kurtosis value of all variables distribution except exchange rate is higher than 3, so the extreme movements are occurring in higher frequency practically and so these values are indicating that the distribution is asymmetrical. The Jarque-Bera Statistics is another strong tool of measuring normality distribution. Jarque-Bera measures whether the Skewness and Kurtosis of our sample is matching with its normality of distribution. Probability (P-Values) in correspondence with Jarque- Bera, have been rejected at 1% significance level for all variables. So there is confirmation of non-normality of distribution of values about mean and variance of monthly periodic changes. Asymmetric distribution of our study sample is indicator of inefficiency of stock market of Pakistan. It gives the opportunity to earn abnormal rate of return. 2. Inferential Statistics: Inferential Statistics helps in establishing relationship between the variables and in addition it assists in drawing inferences and conclusions about population by studying the data. For this study, there are four parts of Inferential Statistics. First, Correlation Analysis has been done to confirm the extent of interdependency between the variables and for analyzing Multicollinearity problem. Second, before conducting a Multiple Regression analysis, Unit Root Test has been taken to check the stationarity of data as Ordinary Least Square Method i.e. Linear or Multiple Regression equation for time series data assumes that times series data is stationary at level Multicollinearity and Correlation Analysis: Basically the Multicollinearity is correlation between the independent variables under study. It is a very basic assumption of Ordinary Least Square Method (OLS) that there is not the presence of high correlation between the predictor variables. Table ΙΙ: Pearson Coefficient of Correlation Matrix OIL GLD INFL FRX OIL GLD INFL FRX ~ 120 ~

6 It is clear from the results that no variable has Correlation Co-efficient near to 1 or greater than 0.8. So in this study there is no problem of Multicollinearity Stationary Data and Unit Root Test: Stationary data is one of the properties of Time Series data. If mean, variance and covariance of time series data of any variable Y t is constant for all time t then time series Y t is stationary. Table ΙΙΙ: Unit Root Test Results ADF Unit Root Test (at level) PP Unit Root Test (at level) Variables Intercept(k) Trend & Intercept (k) Intercept(k) Trend & Intercept(k) KSE -8.72*(0) -8.70*(0) -8.73*(1) -8.71*(1) Oil -4.98*(1) -4.96*(1) -7.35*(1) -7.33*(1) Gld -4.82*(4) -4.86*(3) *(3) *(4) INFL -2.89**(3) -2.82(4) -2.31(7) -2.12(7) FRX -0.54(7) -2.04(7) 2.89*(7) -3.45*(0) Note: Numbers in parentheses show number of optimum lags (k) based on Schwarz Information Criterion (SIC). Critical values for models without Trend, and with Trend at 5% are and -3.41, respectively and Critical values for models without Trend, and with Trend at 1% are and respectively. *Significant at 1%, ** Significant at 5% 2.3. Multiple Regression Analysis: After getting conclusion about stationarity of all time series data, the input of four macroeconomic variables i.e. oil, gold, inflation and US$ exchange rate, on KSE-100 Index has been observed by Ordinary Least Square (OLS) estimation. Multiple Regression Analysis or Ordinary Least Square (OLS) estimation results are presented in Table ΙV The results of the study are estimating the following Multiple regression equation. KSE t = OIL t GLD t INFL t FRX t Table ΙV: Regression Analysis Results (Explained Variable: KSE) Variables Coefficient Std. Error t-statistic Probability Constant OIL ** GLD ** INFL * FRX R-squared Adjusted R-squared F-statistic Probability (F-statistic) Durbin-Watson stat Note: Asterisks (*), (**) & (***) indicates significance at 1%, 5% & 10% respectively. F-Statistic value helps in diagnosing the results of Regression. In Table 4 as computed F- value is greater than the Prob.(F.Statistic) , so it is concluded that null hypothesis, about zero coefficient of variables, is rejected. Therefore it is accepted that ~ 121 ~

7 multi regression of this study is significant overall. In this study Durbin Watson Statistic is near to 2, so this output gives confirmation that there is very slight serial correlation or we can say there is no serial correlation. Adjusted R-Squared Value helps in describing the amount of variance explained in dependent variable by the explanatory variables. In Table 4, Adjusted R-Squared value is This value suggests that 62.38% variability of dependent variable, Karachi Stock Price Index return, is explained by oil price, gold price, inflation and US$ exchange rate. Hence from 62.38% Adjusted R-Squared value, it can be determined that this study s multiple regression model has served the purpose of determining the influence of macroeconomic variables on Karachi stock price index Pair-wise Granger Causality test: Table V: Granger Causality Test Results Null Hypothesis: Obs. F-Statistic Probability OIL does not Granger Cause KSE KSE does not Granger Cause OIL GLD does not Granger Cause KSE KSE does not Granger Cause GLD INFL does not Granger Cause KSE KSE does not Granger Cause INFL FRX does not Granger Cause KSE KSE does not Granger Cause FRX IR does not Granger Cause KSE KSE does not Granger Cause IR On the basis of Probability Values as reported in Table V, the null hypothesis that OIL does not Granger Cause KSE can be rejected because its probability value is much lesser than 10% significance level, but the second one null hypothesis that KSE does not Granger Cause OIL cannot be rejected because probability value is much greater than 10% significance level. So the results of Oil and KSE-100 Index Returns are concluding that Granger causality is running only single way, from prices of OIL to KSE-100 Index returns, but not from KSE-100 Index returns to OIL prices. Besides this, there is unidirectional causality running from Gold price and Inflation to KSE-100 Index return and from KSE-100 Index return to US$/PKR Exchange rate. CONCLUSION AND IMPLICATIONS Empirical results of this study are revealing that oil prices, gold prices and inflation seem to influence the stock market portfolio returns of Pakistan but Exchange rate has no influence on the portfolio returns. In addition, though oil price has significant impact but relationship between oil price growth and stock Index returns is positive instead of negative. The positive oil-stock relation in Pakistan may be due to Cost Push Inflation. There are many causes of Cost- Push Inflation but one important cause is Material Push Inflation. According to Material Push Inflation theory, Increased production cost results in sustained increases in prices of goods and services i.e. the increased cost of inputs especially imported goods such as oil, chemicals etc., induces the manufacturers to raise the prices of goods and services so it helps in maintaining the rising rates of return. In this way the manufacturers pass on such high cost to consumers but sustain their own return rates upward. So Cost- Push Inflation theory is justifying the positive relation of oil and KSE-100 Index returns in Pakistan, although Pakistan is importer of oil. Summing up, although Pakistan is importer of oil but Oil Prices in Pakistan impacts positively on stock returns so the companies put efforts in maintaining the returns in ~ 122 ~

8 accordance with changes in oil prices. In simple words there is well-functioning of Pakistani Stock markets in respect of boosting oil prices. The findings suggest that investors may maintain their investments in stock of companies that are dependent on oil as blasting oil prices do not reduce the return rates in stock market. These results are surprising but beneficial for the stock investors. Gold is used as an alternative investment tool in Pakistan. When gold prices rises, people prefer to invest in gold rather than stock, resulting in declining Stock Prices. These findings suggest the policy makers to implement such policies that help in maintaining the stock returns as well while the gold prices are rising. Such policies may include imposing higher taxes on investors on the bulk of gold investment. Pakistani Stock cannot be used as a hedge against inflation because of its negative relationship. The depreciation of Pakistani currency in terms of US$ is not significantly impacting on the stock return. This is study based upon only four macroeconomics Variables so future study can consider other Macroeconomic Variables as well. REFERENCES 1. Al-Rjoub, S. A. (2005). The adjustments of stock prices to information about inflation: Evidence from MENA countries. Applied Economics Letters, 12(14), ASSOCHAM INDIA; the Associated Chamber of Commerce and Industry of India. (2012). Rupee exchange depreciation: Impact analysis. Available from [January 11, 2012]. 3. Chen, N. F., Roll, R. & Ross, S. A. (1986). Economic forces and the stock market. Journal of Business, 59(3), Cheng, M. Y., & Tan, H. B. (2002). Inflation in Malaysia. International Journal of Social Economics, 29(5), Hamilton, J. D. (2003). What is an oil shock? Journal of Econometrics, 113, Hammoudeh, S., Sari, R., & Ewing, B. T. (2008). Relationships among strategic commodities and with financial variables: A new look. Contemporary Economic Policy, 27(2), Huang, R. D., Masulis, R. W. & Stoll, H. R. (1996). Energy shocks and financial markets. Journal of Futures Markets, 16(1), Jones, C. M., & Kaul, G. (1996). Oil and the stock markets. Journal of Finance, 51(2), Kandir, S. Y., (2008). Macroeconomic variables, firm characteristics and stock returns: Evidence from Turkey. International Research Journal of Finance and Economics, 16(1), Levin, E. J., & Wright, R. E. (2006). Short-run and long-run determinants of the price of gold (Research Study no. 32). London: World Gold Council Research. 11. Ma, C. K., & Kao, G. W. (1990). On exchange rate changes and stock price reactions. Journal of Business Finance and Accounting, 17(3), Moore, G. H. (1990). Gold prices and a leading index of inflation. Challenge, 33(4), Mousa S.N., Safi W.A., Hasoneh A.B. and Abo-orabi M.M. (2012). The relationship between inflation and stock prices (A case of Jordan). International Journal of Research and Reviews in Applied Sciences, 10(1), Sari, R., Hammoudeh, S., Soytas, U. (2010). Dynamics of oil price, precious metal prices, and exchange rate. Energy Economics, 32(2), Türsoy, T., Günsel, N., & Rjoub, H. (2008). Macroeconomic factors, the APT and the Istanbul Stock Market. International Research Journal of Finance and Economics, 22, ~ 123 ~