Exchange Rate And Stock Prices Of India Economics Essay
This is the era of globalization where each and every market is interconnected in some or other way and is affected by each other. Same is the case with stock market where exchange rate can influence the trading of stock. Stock markets are a centre place for buying and selling in listed scrip and have always been investment hub for any country. Most of the investors willing to invest in any country, be its investment is in listed company or not, study the trends of the stock markets within different cities of the country. The price of scrip listed on stock markets goes up or down due to so many factors which include financial, economical as well as political factors of the country. Foreign exchange rate is also one of the factors which may have certain impacts on the movement of the stock price. Since exchange rate of local currency with respect to any foreign currency tends to change i.e. either the currency devalues or appreciates on daily basis as a result of supply and demand mechanism, this movement in the exchange rate shows the degree of stability in any particular currency which serves as one of the basis for the investment in the country for investors. As far as policy makers of any country are concern it is equally important for them to know the relationship between exchange rate and stock prices so that they can use their monetary and fiscal tools more effectively.
The purpose of this particular research is to check the relationship between exchange rate and stock prices of India which will assist the decision makers to make proper economic and financial decisions.
1.2 PROBLEM STATEMENT
To Study the Association between Exchange Rate and Stock Prices of India
H1: There is inverse relationship between exchange rate and stock prices of India
There have been lots of researches in past years that are related to stock prices and exchange rate with respect to different countries. Usually the articles are on Non-Asian countries but now in recent years we also have studies based on Asian countries. Some authors have studied the causal link between the two variables and applied different techniques like co-integration, unit root and correlation but there wasn’t any reasonable findings of whether there is any particular relationship between the two variables or not because some findings suggest there is relationship and some suggest there isn’t any relationship between them so it is a mixed opinion about their relationship. There are many other factors which affect the stock prices other than the exchange rate like inflation rate, gross domestic product, money supply, employment, business activities, dividends, and enterprise performance. Sometimes even political and law and order situations and other macro-economic factors also influence the stock prices.
Aydemir & Demirhan (2009) discussed that there is bidirectional causal relationship between exchange rate and stock prices with respect to Turkey stock market. They also found that there is negative causality between national 100, services, financial and industrials indices and exchange rate whereas there is a positive causal relationship between technology indices and exchange rate, rest of the stock market had negative causality from exchange rate. 23 February 2001 to 11 January 2008 data was used about Turkey as this period was consisting of floating exchange rates which were tested against the stock price indices of national 100, services, financials, industrials, and technology sector
Alagidede, Panagiotidis & Zhang (2010), explained about the causal link between the stock markets and foreign exchange markets of Australia, Canada, Japan, Switzerland, and UK. The cointegration technique was applied to check the long-run relationship between the stock prices and exchange rate but there wasn’t any relationship found between the two variables. The average exchange rates of Australia, Canada, Japan, Switzerland, and United Kingdom against US dollar were employed and Dow-Jones composite average index for the stock prices were used of the respective countries for the time period of January 1992 to December 2005.Three variations of Granger causality were applied to test the causality between the two variables of Australia, Canada, Japan, Switzerland, and UK, they found weak causal relation between the two variables in the Switzerland market only. Furthermore the Hiemstra-Jones test was applied for the testing of non-linear causality and results indicated that there was causality in Japan market and reverse direction weak causality in Switzerland market.
Phylaktis & Ravazzolo (2005) studied the long-run and short-run dynamics of stock prices and exchange rate in Pacific Basin countries for the period of 1980-1998. They applied cointegration and multivariate Granger causality techniques for finding the linkage of external shocks on these markets and found that stock and foreign exchange markets have positive relation. Furthermore, they found that US is the main linkage for the relation among these markets and this relation is also influenced by financial crisis.
Sabri (2004) examined five geographical areas of Mexico, Korea, South Africa, Turkey, and Malaysia including emerging economies to determine the indicators that increase the volatility in the stock return and leads to the instability in the emerging stock markets. He used backward multiple-regression to find the relationship between stock price indices and associating local as well international variables along with the causes of increasing stock price volatility which leads to the crisis in the emerging stock markets. He considered the monthly data of forty-eight months, January 1997- December 2000 and found that the most affecting variables to increase stock price volatility were “stock trading volume” and “currency exchange rate” having the highest positive correlation among all variables whereas, “international stock price index”, “deposit interest rate” and “bond trading volume” were moderately affecting the volatility of increase in stock prices. The least affecting variable was “inflation rate” which had least positive correlation among the rest variables.
Adjasi, Biekpe & Osei (2011) studied the stock market of seven African countries to find whether there is any relationship between the exchange rate and stock prices or not and they came to a conclusion that there is long-run relationship between the two variables in Tunisia and also found the stock returns are reduced when exchange rate is induced in Ghana, Kenya, Mauritius and Nigeria whereas increase in Egypt and South Africa.
Adjasi, Agyapong & Harvey (2008) studied the pattern of the Ghana stock market to know how it is affected by the changes in the exchange rate. By using Exponential Generalised Autoregressive Conditional Heteroskedascity (EGARCH) model they found in the long-run there is negative relationship between the two subject variables (i.e. if the local currency depreciates, the stock market returns rise). However in the short run they noticed a decrease in the stock market returns.
Azali, Habibullah & Saini examined the causal relationship / behavior between nominal Malaysian Ringgit exchange rate and the main and second board indices of Kaula Lumpur using the data that relates to the period before the 1997 Asian financial crisis and also the data that relates to the period of crisis. They had split the results of their research in two parts i.e. “Pre Crisis and During Crisis”. They used the sample data from the period January 1991 to August 1998 and for testing the causality linkage they used Granger non-causality test prescribed by Toda and Yamamoto (1995). In all the cases, the bivariate analysis recommended the bi-directional causal relations. The multivariate analysis in contrast revealed that during the pre crisis period the exchange rate led the second board index whereas during the crises period exchange rate is led by the main board index.
Kumar (2009) studied the relationship between the two variables for the Indian stock market, he used the data of S&P CNX Nifty index returns and foreign exchange rate i.e. INR/USD . For finding the long term relationship between the variables, he used unit root and the co-integration tests from which the results suggested that there is no long term relationship between them. He also used linear and non linear granger causality tests from which he found a bidirectional linear and non linear granger causality between Indian stock index and exchange rate.
Tabak (2006) touched the Brazilian economy for finding out the relationship between stock prices and exchange rate. He, like Kumar (2009), employed the linear Granger causality tests the results of which rejected the traditional approach but supported the portfolio approach (i.e. causality from stock prices to exchange rate). He further applied non linear granger causality tests which supported the traditional approach i.e. there is causality from exchange rate to stock prices. Finally, for the relationship between the two variables in the long run, the unit root and co-integration tests were employed which again suggested that no long term relationship existed between the subject variables i.e. stock market prices and exchange rate. For conducting the research, he obtained data for the period August 1, 1994 to M ay 14, 2002 from the Sao Paulo Stock Exchange and foreign exchange rate of real pre US dollar.
Hussain and Sohail (2009) conducted their study mainly to identify the relationship both the long run and the short run between the Lahore Stock Exchange and macroeconomic variables (consumer price index, real effective exchange rate, three month treasury bills rate, industrial production index, money supply (M2), and LSE25 index) in Pakistan. By using the monthly data from December 2002 to June 2008 they applied the co-integration test. They also used the unit root test and vector autoregressive (for short run causality). The results, inter alia, suggested that the exchange rate had a significant positive impact on the stock returns in the long run.
Ibrahim (.) studied the interactions of stock prices and exchange rate for the Malaysian stock market like Azali, Habibullah & Saini did by applying the Grager causality test. But he used three variations of “exchange rate” in the research that were, the real effective exchange rate, the nominal effective exchange rate, and the RM/US$ rate. He came to a conclusion that there is no long-run relationship between exchange rate and stock prices but there is some evidence of cointegration when M2 money supply and reserves’ impact is included. The findings also suggested that important role in Malaysian market for the short-run is due to RM/US$ rate as the Malaysian ringgit is strongly affected by US dollar due to dependency in the international economic transactions, mainly exports which played important role for Malaysian economy to achieve high growth over the past two decades and created causal link in Malaysian equity market.
Agrawal, Srivastav & Srivastava (2010) examined the Indian Stock Market like Kumar (2009) for analyzing the relationship between Nifty returns and Indian rupee-US Dollar along with the impact of time series on both. With the help of various statistical tests they were able to found that there is negative correlation between the two variables, stationary at the level form itself (using unit root) and have unidirectional relationship (using Granger Causality test) considering the data from October, 2007 to March, 2009 using daily closing indices.
STAVÁREK (2005), analyzed short and long term causal relationship between stock prices and effective exchange rates for (Austria, France, Germany, and the UK) the four old EU member countries, (Czech Republic, Hungary, Poland, and Slovakia) four new EU member countries and United States using monthly data. He also examined the intensity in old and new EU member countries that whether there is any change in the relationship or not. The findings suggested that there were more powerful long and short term relationship among the variables during 1993-2003 than during 1970-92. The real effective exchange rate determined stronger relationship than the nominal effective exchange rate. The UK & USA stock market effectively helped in the exchange rate development although short-run relationships were mixed whereas, Granger causalities test determined unidirectional relationship from stock price to exchange rate in all the cases.
Asif and Aurangzeb (2012) studied the impact of time on three variables include stock prices, short-term interest rates (3 months t-bill rates) & exchange rate on stock exchange of Pakistani economy considering the monthly data of each variable respectively. They applied quadratic regression analysis and found time has significant impact on stock prices and exchange rates but no impact on the short term interest rate.
Muhammad & Rasheed (2002) studied four South Asian countries’ stock markets include Pakistan, India, Bangladesh and Sri Lanka in order to analyze the long run and short run relationship among the stock prices and exchange rates considering the monthly data from January 1994 to December 2000 period. They employed cointegration, error correction modeling approach, and standard Granger causality tests and found no long run and short run relationship among the variables in the Pakistani and Indian stock market where as, Sri Lanka and Bangladesh market had bi-directional long-run causality but no association in the short-run. The study suggested there isn’t any association between the South Asian countries stock prices and exchange rate at least in the short run.
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