Impact Of Exchange Rate Volatility On Stock Market Finance Essay
Exchange rate volatility refers to the amount of uncertainty or risk about the size of changes in price of one country’s currency expressed in terms of another country’s currency. The volatility in price can be both ways, upwards and downwards; meaning exchange rate can appreciate or depreciate on a daily basis depending on the supply and demand.
Impact of exchange rate volatility on stock market
(Oguzhan Aydemir, 2009) Investigates the causal relationship between stock prices and exchange rates; using data from 23 February 2001 to 11 January 2008 about Turkey. The main research Question was that weather a relationship between the exchange rate and the stock prices exists or not. To perform the research, work of many previous related researches was studied and mostly secondary data was collected whose dates are mentioned above. To find the empirical results Augmented Dickey-Fuller (ADF), Phillips- Perron (PP) and KPSS tests were run. The main variables used in the research are turkey stock exchange index National 100, services, financials, industrial, and technology indices are taken as stock price indices. The results of empirical study indicate that there is bi-directional causal relationship between exchange rate and all stock market indices. While the negative causality exists from national 100, services, financials and industrials indices to exchange rate (supporting portfolio balance approach), there is a positive causal relationship from technology indices to exchange rate. On the other hand, negative causal relationship from exchange rate to all stock market indices is determined.
(Charles Adjasi, 2008) Investigates the relationship among the Stock Market and the Foreign exchange Market and determined its impact upon the Ghana Stock Exchange. The study was conducted keeping in mind two main research questions. The first was to determine whether exchange rate volatility has an impact on the Ghana stock market. Second main research question was to determine if other macroeconomic variables effect stock market volatility in Ghana. The variables used to form the model for testing were Exports and Imports, Treasury bill rates, money supply, foreign exchange rates, Trade deficit and Ghana stock exchange indices.To determine the relation among the variables, the method of “The Exponential Generalised Autoregressive Conditional Heteroskedascity (EGARCH)” was used. This is majorly used to model the conditional variance in the financial market and is given preference over GARCH model. Prior to running the regressions, a stationary test was run to eliminate any suppressions in the model. The results found that there exists a negative relation between the exchange rate volatility and stock market returns. If the local currency depreciates, the stock market returns increase in the long run whereas in the short run, the returns are reduced.
(Stavarek, February 2008) This paper has examined the relation between the stock prices and the exchange rate with their mutual interactions in the USA and European Union. To find relations among certain sorts of variables in the financial markets, the previous scholars have run unit root tests to reduce the problems in the regression because of these non stationary macroeconomic variables in a time series. Four old, four new EU countries and USA were chosen for the samples of the variables. Nominal Exchange rates and real Exchange rates were incorporated in monthly form of data. The local stock indices embodied into monthly data lead to some confusion due to the fact that different countries calculated the stock indices differently; hence to reduce the confusion national stock indices with uniform methodology was used. The sample period for each country varied depending upon the availability of the data. NEER, for Austria, France, Germany, UK, and the USA the sample period is December 1969 till December 2003; for Poland December 1993 till December 2003; for the Czech Republic December 1994 till December 2003; for Hungary January 1995 till December 2003 and for Slovakia June 1995 till December 2003. For the Real Exchange rates, sample period for the first group of the countries is January 1978 till December 2003 for others it is the same as the data for nominal exchange rates. To test the said variables first of all the stationery test and co integration analysis was run. The results showed that exchange rates and stock market indices proved to be co integrated in six out of nine analyzed countries. The time series for Hungarian and Poland are identified to be 0, hence the such results are termed as invalid and do not involve into further analysis. Hence then a Vector Error Correction and Granger Causality Test was run to identify the problematic areas in the regression model and to know what causes what in the model on the said variables. As the time period is divided into two categories, the first being 1970–1992 and the second being 1993 to 2003, in the first category the long run relationship between the said variables did not exist, reason might be due to the under estimation of the prevailing exchange rate arrangements in the developed countries. Under the Brettonwood system there was little fluctuations within a tightened frame in the nominal Exchange rate which provided little space for exchange rate volatility. In the second period from 1993-2003 shows much stronger long run causalities in the developed countries. In four out of the nine selected economies, co integration between the stock prices and the exchange rate existed. The nature of the relationship however was not consistent in all the cases. In case of United Kingdom and United States of America, there was evident movement in the stock market as a result of exchange rate developments.
(Kolawole Subair, 2008) In this paper examine the effects of exchange rate volatility on the stock exchange of Nigeria. According to the hypothesis the effect can be either positive or negative. Data obtained for this study was mainly from secondary sources. It included values of exports and imports, foreign exchange rates, inflation rates, net capital flow, external reserve, degree of openness and trade deficit. Nigeria Stock Exchange quarterly publications were used to obtain data for the Stock Exchange index. Exchange rate volatility was generated via GARCH technique. stock market capitalization (SSMC) is expressed as a function of exchange rate volatility (LVOL), interest rate (IR), inflation rate (INF) and gross domestic product (LGGDP). The data set used in the study comprises annual stock market capitalization, gross domestic product, inflation rate, interest rate and exchange rate volatility for the period 1981-2007. Results showed that exchange rate volatility has a very serious implication on the Nigeria stock market. Exchange rate depreciation reduces stock market return.
(Rashid, 2007) In his research employs co integration, the standard Granger causality tests and vector error correction modeling technique to investigate the cause-effect association between exchange rates and stock prices for Pakistan. Main research question is exchange rate or Stock prices, what causes what. The data used is completely secondary in nature. It used weekly data for 70 individual securities and the trade-weighted exchange rate over the span from January 1, 1999 to March 31, 2004. This data is used for the variables defined as stock prices and exchange rates. In the findings, For 65 of the 70 firms, we accepted the null hypothesis of no cointegration. This is indicating that there is no long-run equilibrium relationship between the trade-weighted exchange rate and the stock prices for about 86% examined firms. However, we found that, for only five firms in our sample, there is a long-run stable relationship between stock prices and exchange rates.
(Muhammad, 2001) in his paper examined whether stock prices and exchange rates are related to each other or not. The research is based upon secondary data which is collected on South Asian countries, including Pakistan, India, Bangladesh and Sri- Lanka, for the period January 1994 to December 2000 on monthly basis. The methodology used for this research is co-integration, vector error correction modeling technique and standard Granger causality tests to examine the long-run and short-run association between stock prices and exchange rates. Variables used for this study are major stock prices indices of these countries and the exchange rates between the currencies of these countries with the U.S. dollar. results show no long run and short-run association between stock prices and exchange rates for Pakistan and India. No short-run association was also found for Bangladesh and Sri- Lanka. However, there seem to be a bi-directional long-run causality between these variables for Bangladesh and Sri Lanka.
2.2: Macroeconomic variables and Stock Market volatility
2.2.1 Interest rate changes and its impact on Stock market volatility
(Sánchez-Fung, 2004) This paper investigated the banking instability in relation to day to day interbank market and monetary policy effectiveness in the Dominican Republic. The paper has first established a baseline for the questions such that is there any link banking system instability, interbank market and monetary policy in the developing country. A thorough case study of the Dominican Republic was used to understand the pattern which included the 2002-2003 banking crisis in the country. The variables used for the study included; daily time series of aggregate excess reserves (millions of Dominican Pesos), interbank interest rate (expressed in percentage points). The data taken was from January 1999 to November 2003 –a total of 1,210 observations on each variable from the Central Bank of the Dominican Republic. Firstly an analysis of interbank interest rates as a function of aggregate excess reserves, exogenous policy shocks, and institutional and calendar features using a dynamic time series model was conducted. Secondly the results from the first model are used as a baseline to form the mean equation for the Generalized Auto Regressive Conditional Hetroskedascity GARCH framework. After running the regressions, the results depicted that there exists a negative relationship between the excess banking system reserves and the interbank interest rates and also shows that in crisis, news ‟affect the interbank rate”s volatility asymmetrically and non-linearly. (Urooj, Tahir, & Zafar, 2008) advocate this relationship as well with results revealing a negatively significant relationship between interest rates and index and subsequently the stock returns. Higher rates of interest appreciate investors into keeping their money in bank accounts to earn a higher return and thus demand for stock decreases and so does return.
2.2.2 Inflation, Price changes and the subsequent impact on Stock market
(Ralf Becker, December 15, 2005) This paper has attempted to find the best way to model the stock market volatility conditional on macroeconomic conditions. The variables used for the study consisted of S&P500 daily log returns from the 3rd of January 1955 to the 31st of December 2004. The different macroeconomic variables used in the study include, the GDP growth, inflation rate, the Treasury note rate, the 10 year corporate bond rate and short term/ long term interest rates. The data was sampled quarterly. The Index returns were sampled daily. A four quarter moving average for the samples variables was calculated to exempt any suppression while running the model regression. To run the model, the method of Spline GARCH was used. It is an extension of Generalised Autoregressive conditional Heteroskedascity model to cater to the time varying level of unconditional volatility. Once this method was run, the traditional GARCH method was run. In macro Spline GARCH method two different sets were tested. The first set consisted of macroeconomic variables where as the second one excluded all the uncertainly proxies. As for the results, the MS GARCH model implies that the interest rates have significant power over the unconditional variance of the S&P500 returns. Unconditional volatility is consistently positively related to the level of the short term rate, negatively related to slope of the yield curve for government interest rate instruments and positively related to the spread between commercial and government rates. The GARCH method provided significantly different results that are somewhat inferior to the MS GARCH model as there is very little evidence of reversion towards the unconditional volatility using this method. According to the paper, the future work will have to settle if similar modeling can provide sufficient and consistent improvements in forecasting the volatility in the financial markets.
(Gülin Vardar, 2008) attempts to Investigate the impact of interest rate and exchange rate on the composite and sector price indices which are financial, industrial, services and technology in Istanbul Stock Exchange. This research used secondary data that was a daily sector data over the 2001-2008 period. Analyzing the sources of volatility in the selected indices is crucial for implications regarding asset pricing, risk management, and portfolio selection. The daily closing sector price indices, exchange rates and interest rates are used for the period beginning on 2 April 2001 and ending on 21 July 2008 and data were obtained from Matriks Data Delivery System. The foreign exchanges are stated in US dollars per local currency and interest rate is measured as 2-year Turkish Government Bond yield. These variables are used to demonstrate the impact of exchange and interest rate changes on the underlying index volatility. Composite index, Financial (XUMAL), Industrial (XUSIN), Service (XUHIZ) and Technology (XUTEK) sector indices are employed in the analysis. Composite index is composed of stock market companies except investment trusts. Results imply that most of the persistence in volatility cannot be explained away by information arrivals of interest rate and exchange rate changes. The results also provide evidence that volatility persistency in index return series has increased slightly after the inclusion of the variables. The relatively high value of persistency confirms that even the volatility of the index return series appears to have quite a long memory, the volatility process still returns to its mean. Hence, the results demonstrate that volatility in sector returns is significantly prompted by interest and exchange rate changes.
(Charles Adjasi, 2008) shows that an increase in the trade deficit and any expectation of future rise in trade deficit decreases the stock market volatility. The Increase in the consumer price index leads to an increase in the stock market volatility.
2.3: Drawbacks of Past studies & Incompatibilities
Analyzing the past studies and comparing the results to the study setting of Pakistan, although the relationship of variables are as expected, but the manipulation of trading activities in Pakistan and other developing countries are sometimes a hurdle in the contradictory nature of results. Furthermore, this study has included only one year’s data on a day-on-day basis whereas usually the past studies have either collected quarterly data for a number of years or weekly data ranging for large time periods. This study therefore is focused on the short term relationship of variables with the index and is an attempt to be consistent with, if not match, the past studies.
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