Relationship between Exchange Rate Fluctuation and Stock Market Indices and it is impact on the

Karachi Stock Exchange of Pakistan

Haji HussainAPCOMS Rawalpindihussain82@usa.com

AbstractThe purpose of this study is to find out the relationship between the

stock market of Pakistan and foreign exchange rate. For this purpose secondary data is collected from different business review and financial journals of the world and Pakistan. Research indicates that there is a bi-directional causal relationship between exchange rate fluctuation and stock market indices and a mixed causality also exist. This study also discusses, how exchange rate fluctuation impact on the stock prices and stock market performance, particularly financial markets of Pakistan.

IntroductionStock market of a country is supposed to playa a vital role in the

economy of that country. This marked is a source for corporations and organizations to increase money and capital. They can boost up their additional capital by trading their shares publicly. Therefore this markets is considered the primary indicator of a country‘s economic development.

Stock market is strongly affected by some of the macro economic variables and other internal and external factors, such as; real exchange rate, interest rate, inflation (Kandir, 2008). However the issue is weather stock markets have a relationship with exchange rates or not. Most of the economic theories and empirical literature suggest that stock prices are effecting due to exchange rates fluctuation however, the result of these studies are inconclusive (Juseph, 2002).

Researchers found not a same result for the relationship between the variables. Most of them found a negative relationship; some found a positive relationship while other found a mixed or bidirectional relationship. Negative relationship between stock prices and interest rate will be appeared in the long run but stock prices are positively related with the exchange rate on the other hand (Orwan and Sharma, 2007). All the stocks prices have not same impact on the exchange rate prices. Different stocks have a different association with exchange rate. For instant, in Turkey a bidirectional causal relationship was found between all stock market indices and exchange rate. A negative association was noted

between exchange rate and Natiotal 100, financial, industrial, and service indices on the one hand while a positive relationship between exchange rate and technological indices was found (Aydemir and Fradal, 2009).

Moreover, some studies found very week or no relationship between stock prices and exchange rate fluctuation [Bartove and Bonder (1994)]. Ma and Kao (1990) suggest that there may be different result or relationship occurred due the nature of the countries, for instant, they may or may not be dominant in import or export business. Bahmani Oskooee and Sohrabian (1992) claim that there is bi-directional causality between sock prices and exchange rate in the short run; however, there is no such relationship in the long run.

Most of the empirical studies examine the relationship between stock prices and exchange rates has mainly focus of the developed countries having little attention on the developing countries like Pakistan, India, Bangladesh etc [M.Naeem and Rasheed (2002)]. The economy of Pakistan and India is flux economy. Both face instability in their economies. There is no short run and long run relationship between stock prices and exchange rates for Pakistan and India. So, the association between exchange rates and stock prices in Pakistan and India is bi-directional, therefore, investor cannot use information obtained from one stock market to speculate the performance of the market [M.Naeem,.. (2002)].

Literature Review

Abdulla and Murinde (1997) examine the relationship between exchange rate and stock prices for the emerging financial markets of Korea, India, Pakistan and Philippines. They use bivariate vector autoregressive model using monthly observations of stock prices and exchange prices for their study. They found that unidirectional causality exist from exchange rate to stock prices for Korea, India and Pakistan except Philippines.

Sheng and Shuh (2004) examine the volatility transmission system between stock and foreign exchange markets for the G-7 countries and use EGARCH model. They find that changes in exchange rates have less direct impact on future changes of stock prices and movement of stock prices will effect future exchange rate movement.

Rhaman and Jashim (2009) analyzed the relationship between exchange rate and stock prices of the three emerging countries of South

Asia as Pakistan, India and Bangladesh. They use six years data of Karachi Stock Exchange, Bombay Stock Exchange and Dhaka Stock Exchange General Index from January 2003 to June 2008 to conduct the study. They applied Johansen procedure and found that there is no way causal relationship between exchange rates and stock prices.

Charles, Simon and Daniel (2008) uses Exponential Generalized Autoregressive Conditional Heteroskedascity (EGARCH) model to examine the relationship between Stock Markets and Foreign Exchange Markets in Ghana. They found that there is a significantly negative association between exchange rate volatility and stock market returns. Their result also showed that depreciation in local currency leads to an increase in stock market returns in the long run and it reduces stock market returns in the short run.

Aydemir and Frdal (2009) employed the daily data from February 2001 to January 2008 of National 100, financials, services, technology and industrial indices as stock price indices from Turkey. The results of their study indicate that there is a bi-directional causal association between all stock market indices and exchange rate. They found that there is a negative relationship between exchange rate and national 100, financials, industrial and services indices on the one hand. On the other hand there is a positive relationship between exchange rate and technology indices.

Chaker (2007) chooses the period pre and post euro (1991-2005) to investigate the interaction between exchange rate and stock prices for the United States and some major European markets. He used Exponential Generalized Autoregressive Conditionally Heteroskedastic (EGARCH) model for examine the relationship between the variables. He found that the stock prices have more significant impact on the foreign exchange rate for both the sub-samples.

Orawan and Sharma (2007) examine the relationship between stock prices and macroeconomic factors in the United State. The result of study shows negative relationship between stock prices and interest rate in the long run. On the other hand stock prices positively relate the exchange rate, money supply, production and inflation.

Douglas and Kui (2010) employed the Dynamic Conditional Correlation (DCC) model to examine the relationship between stock return differential relative to the US and real exchange rate (for financial crises of 1997 and 2008). The result to the study shows stochastic association between real exchange rate and relative stock prices.

Ramin, Lee and Hamzah (2004) investigated the dynamic interactions between stock market return and macroeconomic variables in Singapore. They found that sock market and property index significant relationship with all macroeconomic variables in the short run and exchange rate, money supply, interest rates and industrial production in the long run.

Nadeen and Zakir (2009) examine the long run and short run correlation between Lahore stock exchange and macroeconomic variables in Pakistan. They found two results in the long run as; inflation has negative impact on the stock prices on the one hand and real effective exchange rate, industrial production and money supply have a positive impact on the other hand.

Suliaman, Adnan and Ali (2009) uses Multiple Regression Analysis Model examine the relationship between share prices in Karachi Stock Exchange and macroeconomic variables. They use quarterly data of several macroeconomic variables for their study. They found that production and capital formation (internal factors) have no significant impact while exchange rate and reserves (external factors) have a significant impact on the stock prices.

Adnan, Arslan, Narjis and Kashif (2009) use the Robust Time Series Tools (RTS) in order to examine the money demand function of Pakistan for the period 1971 to 2006. The result of their study shows that stock prices have significantly positive impact and exchange rate insignificant impact on money demand in the long run.

Beer and Hebein (2008) employed the Exponentional General Autoregressice Conditional Heteroskedasticity (EGARCH) model to examine the relationship between sock prices and exchange rates for to groups of countries as; developed and emerging countries. They found positive significant correlation between the stock market and exchange rate for Japan, Canada, US and India and opposite result for the emerging economies.

Abdul and Kemal (2006) use EGARCH method to investigate the interaction between foreign exchange market and stock market in Pakistan. The result of their study shows a strong relationship between the volatility of the foreign exchange market and the return in the stock market. By the co-integration analysis they also found that there is a no long run relationship between the two markets.

Zahoor and Farooq (2009) employed Error Correction techniques along with Auto Regressive Distributed Lag Model to examine the relationship between exchange rate instability and economic growth in Pakistan. The result shows that there is a log-run positive relationship between exchange volatility, reserve money and export. They also found that the statistical value of imports and exports are not significant.

Aliyu and Usman (2009) study a possible short- run and long-run associations between stock prices and exchange rate in Nigeria. They found bidirectional relationship between the exchange rate and stock prices in the long run.

Alexandra and livia (2007) uses Granger Causality Test and Bivariate Cointegration model to examine the linkages between sock prices and exchange rate in Romania. They use daily and monthly data for the periods 1999-2007 and empirical results of the study reveal that stock prices and exchange rates have a strong interaction. Stock prices adjusted as changes in the exchange rates during the period of one month.

Thahir and Zaidi (2006) employed MS-VAR model to examine the interaction between stock prices and exchange rates in Malaysia. They used British pound sterling and the Australian dollar against Malaysia ringgit and found that there is a negative relationship between stock prices and exchange rates.

Richards, John and Evans (2009) use Granger Causality model to examine the interaction between stock prices and exchange rates in Australia. Their empirical result show positive co-integrating association between the variables.

Azman, Habbullah, Siong and Affizzh (2007) study the causality relationship between exchange rate and stock prices during the crisis in Malaysia. They use a new Granger non-causality test model to investigate the interaction between the variables. They found that there is a one-way causality running relationship between stock prices and exchange rate. Their empirical study also shows that stock market decline was led by the ringgit depreciation.

Pilinkus and Boguslauskas (2009) examine the relationship between stock prices and other six macroeconomic variables including exchange rate in Lithuania. Their empirical study suggest that sock market prices are effected by the macroeconomic variables and found that money supply and gross domestic product have a positive impact on stock market

prices while exchange rate unemployment and short term interest rates have a negative impact on the stock prices.

Chien (2005) employed Conventional Jonhansen’s maximum Cointegration model and ARDL bound test to investigate the relationship between exchange rate and macro fundamentals in Taiwan. He use monthly data of the period 1986:01-2003:04 for his study and found no empirical evidence for the long run association between macro fundamentals and exchange rate.

Yasushi, Ronald and Victor (1990) study short run interaction of between exchange prices and prices volatility across the Tokyo, London and New York stock markets. He employed the autoregressive condition- ally heteroskedastic (ARCH) to examine the relationship. His empirical result shows one direction price volatility spillovers from London to New York, New York to London, New York and Tokyo, but no price spillover effects was observed in other directions.

Daniel (2008) examines the short run and long run dynamics between exchange rate and stock prices in USA and member countries of EU. He found strong interaction between the variables for countries having developed capital and foreign exchange rate. He also found a long run as well as short run strong relationship during the period 1993-2003 as compare to other periods of time.

Qayyum and Kemal (2006) employed the Engle Granger two step models and the volatility spillover is modeled through bivariate EGARCH method to find out the long run and short run relationship between stock market and foreign exchange market in Pakistan. The result of their empirical result shows that both the market are interlinked with each other and they also found that there is a strong correlation between stock market and foreign exchange market in Pakistan.

Alagidede, Theodore and Zhang (2010) examine the relationship between stock market and foreign exchange market in Canada, Australia, UK, Japan and Switzerland. They employed Cointegration tests and found no evidence of long run relationship between the variables. They also use Granger causality test for further investigation and found interaction between the variables for UK, Canada and Switzerland.

Joseph (2009) examines the long-run association between macroeconomic fundamental (as exchange rate, money supply, price index, interest rate) and stock prince on Ghana Stock Exchange. He found that exchange rate has a positive and rests of the variables (as money supply, price index, interest rate) have negative impact on the sock prices.

Pilinkus (2010) employed vector autoregression model and Johansen multiple Cointegration test model to investigate the short run and long run relationship macroeconomic indicators and stock market indices in the Baltic States. His empirical results show that the interaction between the stock prices and macroeconomic indicators is more reliable.

Yun and Chung (2006) use linear and non-linear time series methods to investigate the short-run and long-run interaction between stock prices and exchange rate for the period 1991:1 to 2005:7 in Taiwan and Japan. They found a relationship between the variables. But they also found that there is no long-run interaction between the stock prices and exchange rate in Taiwan and Japan.

Daniel (2004) examines the relationship between effective exchange rate and stock prices in eight EU member countries (Austria, France, Germany, UK, Czech Republic, Poland, Hungary, and Slovakia) and United States of America. He found no evidence of interactions between the variables for the long-run in 1970s, 1980s and 1990s. But from 1993 to 2003, he found much stronger causality in the developing countries.

Shahbaz, Nadeem and Liaquat (2008) employed Engle Granger causality and ARDL tests to investigate the relationship economic growth and stock market development in Pakistan. Their empirical results show a strong association between the stock market development and economic growth. They study also suggest that that this relationship is bi-directional in the long-run and one way causality in the short-run.

Mohiuddin, Alam and Abdullah (2008) examine the relationship between stock prices and macroeconomic variables (exchange rate, inflation rate, interest rate, production index, and money supply) in Bangladesh. They used share prices of Dhaka Stock Exchange as the dependent variable. They found no evidence of interaction between the variables.

Arshad and Tariq (2009) examine the long-run dynamic relationship between equity market prices and monetary variables (as foreign exchange rates, money supply consumer price index and Treasury bill rates) in Pakistan. They found that exchange rate have a negative impact on the equity returns in the short-run while other variables are a significant source of volatility for equity returns. They also found that inflation rate have a negative shock on equity return.

Mark and Nabil (2002) examine the non-linear association between Asian equity market and foreign exchange markets. They use regime- switching Markov model and found non-linearity evidence for Hong Kong only. Their results also show that increase or decrease in stock returns have a negative impact on the equity markets.

Dimtrova (2005) examine the relationship between exchange rate and stock prices. He employed multivariate model and found very weak interaction between the variables.

Kate and Ravazzolo (2005) employed Cointegration methodology and multivariate Granger causality test to investigate the long-run and short-run interrelationship between stock prices and exchange rates in Pacific Basin countries. They found positive correlation between the exchange rates and stock prices.

Gue, Kivilcim and Peha (2001) examine the long term and short term interrelationship between stock returns and monetary variables in the emerging markets. Their empirical results suggest that the evidence of significant relationship does not exist between the variables.

Richard and Stefan (1997) use monthly data from 10 industrialized countries to investigate the relationship between stock market and effective exchange rate. They found a significant positive association between stock market returns, exchange rate.

Lean, Naresh and Smyth (2006) use Cointegration and Granger causality test to investigate the relationship between stock prices and exchange rate in eight Asian countries. Their empirical result show a weak relationship between the variables for Korea only and no evidence of co-integration between for other countries.

Gramboyas (2003) examine the relationship between exchange rate fluctuations and equity prices in three emerging countries (Greece, Czech Republic and Hungary) of Europe. His empirical study argued that changes in stock market prices may affect exchange rate and it has a direct impact in the case of euro-zone.

Johnston and Elton (1997) use various fundamental variables from different theoretical models to study the exchange rate changes. They found a significant interaction between economic fundamental variables and exchange rate changes.

Naeem and Rasheed (2002) examine the long-run and short-run relationship between stock prices and exchange rate for four Asian countries. Their empirical results suggest that sock prices and exchange rate not related in the short run and long-run in Pakistan and India however a bi-directional association was found for Bangladesh and Sri Lanka in the short-run.

Fazal and Tariq (2001) examine the causal relationship between stock prices and macroeconomic variable in Pakistan. They employed Cointegration and error correction model and used annual data from 1959-1960 for their study. They found a long-run relationship between the stock prices and macroeconomic variables.

Yan (2005) examine the relationship between exchange rate and stock market. He used stable aggregate currency (ASC) and ordinary least squares (OLS) model for his study. He found that stock market and exchange market are two independent markets but evidence show the impact of exchange rates on the stock market.

Zakria, Atazaz and Mazhar (2007) examine the nominal and real variables that determine the rate of nominal exchange in Pakistan. They employed Generalized Method of Movement (GMM) estimation to investigate the role of nominal and real variables. They found that exchange depend on various endogenous variables and policy variables in the economy. They also found that shocks are the main cause of volatility in nominal exchange rate.

Variables and Theoretical Framework

The primary trading partners of Pakistan are U.S, China, EU, Japan, UAE and Afghanistan etc. Pakistani currency exchange rate is considered against U.S dollar as a variable and the other variables are from Pakistan’s Stock Index. There are three stock exchange are operating independently in Islamic Republic of Pakistan, Karachi Stock Exchange, Lahore Stock Exchange and Islamabad Stock Exchange. But this study just chooses Karachi Stock Exchange. In this market stock are price in the local currency and also quoted in U.S dollars for international investors. According to the post/previous theoretical and empirical studies, there are supposed to be association between stock prices and exchange rate. It means that, the increase or decrease in the exchange rate will also affect the stock price and vice versa. Base on these assumptions, following theoretical framework is developed:

Independent/Dependent Variables

Independent/Dependent Variables

U.S Dollar/Pak Rupees

Financial Stocks(KSE)

Service Stocks(KSE)

Trading Stocks(KSE)

Industrial Stocks(KSE)

Technology Stocks(KSE)

Hypotheses

There are five hypotheses are explored in this study to examine the relationship between stock prices and exchange rate. Each of the resulting hypotheses is stated in the null format. Hence the all there hypotheses are as follows:

H0 1a: There is a positive relationship between stock prices and exchange rate.H0 2a: There is no positive relationship between stock prices and exchange rate.

H0 1b: There is negative relationship between stock prices and exchange rate.H0 2b: There is no negative relationship between stock prices and exchange rate.

H0 1c: There is a bi-directional relationship between stock prices and exchange rate.H0 2c: There is no bi-directional relationship between stock prices and exchange rate.

Data and Methodology

The secondary data was collected from the website of Karachi Stock Exchange and Foreign Exchange Market. To test the relationship between socks prices and exchange rate, average data of five stocks indices was capture from 2005 to 2008. For empirical study five stock prices taken and a simple correlation and linear regression method were employed.

Sample was selected using convenient sampling technique. The sample characteristic is describes in the following table:

Type of Stock NPercentage

Stock

Financials 1 20%Trading 1 20%Industrial 1 20%Service 1 20%

 Technology 1 20%

    5 100%

Results

Traditionally to test for the relationship between variables, correlation test has been employed. This test states that, how much relationship exit between the individual variables which is describes on the following table.

Correlation Analysis

  Mean S.Dev  Financials

Trading

Technology

Industrial

service Ex.Rate

Financials 93.123 23.893   1.000 0.944 0.873 -0.133 0.055 0.176

Trading1968.81

8 339.873   0.944 1.000 0.669 -0.450 0.372 0.475Technology 286.735 132.462   0.873 0.669 1.000 0.362 -0.438 -0.325

Industrial 17.390 5.258   -0.133 -0.450 0.362 1.000-

0.988* -0.977*

Service 101.370 40.171   0.055 0.372 -0.438 -0.988 1.000 0.990*

Ex.Rate 62.899 5.285   0.176 0.475 -0.325 -0.977 0.990 1.000* Correlation is significant at the 0.05 level (2-tailed).

The above table suggest that there is a correlation is exists between the variables. It also states that there are significantly positive relation service stocks and exchange rates on the one hand and a negatively significant correlation was found between industrial stocks and exchange rates on the other hand.

To find out the overall relationship between the variables, linear regression test was also employed which is shown on the following table

Regression Analysis

Model

Unstandardized Coefficients 

Standardized Coefficients t Sig.

    BStd. Error Beta    

1(Constant) 28.52486 0   . .

 Financials 0.03715 0 0.16796 . .

 Industrial 0.584954 0 0.582053 . .

  Service 0.204615 0 1.555365 . .N = 5, where technology and trading stocks are constant.

No relationship was found between the variables by regression test. So, the data not support the hypothesis as “H0 1a: There is a positive relationship between stock prices and exchange rate, H0 1b: There is negative relationship between stock prices and exchange rate, There is a bi-directional relationship between stock prices and exchange rate”. Therefore the alternative hypothesis accepted.

Conclusion

This paper examines the relationship between stock prices and exchange rate relationship in Pakistan for the period January 2005 to December 2008. We used yearly average data and employed simple correlation and linear regression tests to examine the association. Our results show no overall relationship between the variables but a mixed correlation was found between individual variables. We also found a positively significant correlation between service stocks and exchange rate. A negatively significant relationship was also found between industrial stocks and exchange rates. Our empirical result states that there is a mixed causality between these variable in Pakistan. We however, suggest that the significant of our results could be possibly improved by using daily or monthly data and employed standard technique of co-integration or granger causality test.

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