What is the impact of currency fluctuation toward share? This question remains controversial among economists and investor. This is because the value of currency of one country is very important in order to make sure all economic activities are running smoothly. Malaysia currency is known as Malaysia Ringgit. Currency fluctuation or currency movement is very important to all countries all over the world. This is because the value of currency may change the economic activities directly or indirectly. In 1997, Asian was caught in economic recession and our currency was depreciated rapidly. It not only affected Malaysia currency but also affected all Asian countries. The value of Malaysia ringgit was depreciated from RM2.50/1USD to RM4.50/1USD against USD. Because of that, many foreign investors refuse to invest in Malaysia and led to the decreasing in the stock price.
Stock markets can be volatile and varies depend on the financial economic factors such as interest rate, exchange rate, and also import and export. The volatilities of stock price can be very complex. Stock prices are affected by a number of factors and events, some of which influence stock prices directly and others that do so indirectly. Foreign currency rates have a direct impact on the price and value of stocks in foreign countries, and changes in exchange rates will increase or decrease the cost of doing business in a country, which will affect the price of stocks of companies doing business abroad. Other then that, long-term movements in exchange rates are affected by various fundamental market forces of supply and demand and purchase price parity, short-term movements are driven by news, calendar effect, events and futures trading and are difficult to predict.
According to Maskay (2007), the stock price is determined by the present value of the future cash flows. The present value of the future cash flows can be calculated by discounting the future cash flows at a discount rate.
The price of stock can be predicted by the movement of share price in some length of time using various ways such as graph and chart. A chart by itself tells a little more the market reaction. (Gitman, Joehnk, and Smart, 2011). There are a lot of chart can be use such Triple Top Chart, Head and Shoulders Chart, Flag and Pennant Chart and also Point and Figure Chart. They also mention that chart is very popular among chartist because is provide visual summary of activity over time.
Furthermore, the stock markets are becoming a very important part of economies of many countries. Mohamed and Abdelkader (2011) suggest that, the importance of the stock market has motivated people to formulate many theories to describe the working of the stock markets. They argued that, the factor which is linked to the stock markets is interest rates and stock price fluctuations. In theory, the interest rates and the stock price have a negative correlation. This is because a rise in the interest rate reduces the present value of future dividend's income, which might depress stock prices. Conversely, low interest rates result in a lower opportunity cost of borrowing. Thus, the ways on how these two economic factors linked each other.
A trade and economic activity was increasingly globalized over the past several decades. The companies throughout the world have expanded operations abroad instead of in their own countries. They aimed to increase market share and sales, achieve economies of scale and also to improve and increase their profit margins. Malaysia's companies also have expended business and operation outside of Malaysia. Acorrding to Dimitrova (2005) in his investigation about the relationship between exchange rates and stock prices, the equity and fixed income trading of international investor is seen to be very important. This is important to increase the fund of other investors and their firm's wealth management.
Bank Negara Malaysia (2012) reported that the performance of the ringgit is affected by the uncertainty in financial markets mainly due to international of external developments. Between January and July 2011, dollars was strong because the inflows of substantial portfolio. Strong fundamentals and positive investor sentiment continues to attract capital flows towards the regional market. Therefore, this research is conducted to study the relationship between the currency fluctuations and share indexes of 4 ASEAN counties which Malaysia, Indonesia, Thailand and Singapore.
Share prices are unpredictable. Many factors such as the performance of the company, of the whole industry, or even of the overall economic activities may affect the price of shares. In fact, studying the past and the forecast of company performance, considering the securities analysts' opinions, industry trend, as well as follow up different types of information that are disclosed can reduce the risk of unpredictable share price. This is what this paper is going to research, that is the factors that affect the share market value.
I have two objectives in this paper. First, I want to examine the reaction of stock markets around currency devaluations using daily returns (share indexes). This analysis helps explain how international equity markets respond to such events. Second, I would like to study whether the past share price have significant relationship with the current share price. The market return is from 2004-2011 and it is taken from stock market each country. In this paper we estimate the impact of exchange-rate movements and past share price on the stock-market valuations of selected countries.
1.1 BACKGROUND OF STUDY
A stock market or equity market is a public entity for the trading of company share and also derivative at an agreed price. These securities can be listed on share market and also can be traded privately. (Wikipedia, 2011). The stocks are listed and traded on stock exchanges which are entities of a corporation or mutual organized specialized in the business of bringing buyers and sellers of the organizations to a listing of stocks and securities together. The largest stock market in the United States, by market capitalization, is the New York Stock Exchange (NYSE). In Canada, the largest stock market is the Toronto Stock Exchange. Major European examples of stock exchanges include the Amsterdam Stock Exchange, London Stock Exchange, Paris Bourse, and the Deutsche Borse Frankfurt Stock Exchange. According to Firth (1977), in his research he mentions that the share market is very important role as a medium of exchange of ownership of shares and a mechanism for companies to raise capital. He also mentions that the role gives a market place to investor, where purchases and sales can be made there and the share prices can be set by supply and demand relationships.
1.1.1 FTSE BURSA MALAYSIA KLCI (FBMKLCI)
FBMKLCI is a public entity was introduced in 1986, it is now known as the FTSE Bursa Malaysia KLCI. The enhancements to adopt FTSE Bursa Malaysia Index methodology were implemented on Monday, July 6, 2009 and comprises of the largest 30 companies by full market capitalisation on Bursa Malaysia's Main Board. The highest market capitalization volume in FBMKLCI as at 6 March 2012 are leading by Malayan Banking Berhad with RM 66,997,900,000 market capatalization. Then followed by Sime Darby Berhad, CIMB Group Holding Brhad, Petronas Chemical Berhad, Public Bank Berhad, Maxis Berhad, Axiata Group Berhad, GentingBerhad and IOI Corpoaration.
1.1.2 STRAITS TIMES INDEX (STI)
The Straits Times Index (STI) is the most globally-recognised benchmark index and market barometer for Siangapore. With a history dating back to 1966, it tracks the performance of the top 30 companies listed on the Singapore Exchange ranked by market capitalisation. The STI adopts FTSE's international methodology for compiling stock indices and has been designed to be tradable to meet the needs of both domestic and international investors. It is also the headline index of the FTSE ST Index Series, a family of indices created by Singapore Press Holdings (SPH), Singapore Exchange (SGX) and FTSE Group (FTSE), that aims to offer a wider set of investment choices and opportunities by segmenting the Singapore market. The most top 10 constitute in STI are DBS Group Holdings (banking institution), Singapore Telecom (communication), Oversea-Chinese Banking (banking institution), United Overseas Bank (banking institution and Hongkong Land Holdings (real estate). During the last 12 months, the Straits Times Singapore Index had a rank of 18 with a return of 16%. The top ranked index during the last year was the DAX Stock Index, with a return of 34%.
1.1.3 STOCK EXCHANGE OF THAILAND (SET)
SET is the national Stock Exchange in Thailand. It is located in Bangkok. As of 31 December 2011, the Stock Exchange of Thailand had 545 listed companies with a combined market capitalization of BT 8,490 billion. Top 10 largest public companies in Thailand as of 25 June 2012 included PTT (energy and utilities) with BT 885, 452.88 million and also Siam Commercial Bank (banking institution with market value of BT 481, 885.83 million. Currently, The Stock Exchange of Thailand (SET) can supply SET Total Return Index (SET TRI), SET50 Total Return Index (SET50 TRI), SET100 Total Return Index (SET100 TRI), SETHD Total Return Index (SETHD TRI), mai Total Return Index ( mai TRI ) and Total Return Index by Industries (Industry TRI).
1.1.4 INDONESIA STOCK EXCHANGE (DXI)]
Indonesia Stock Exchange also known as Bursa Efek Indonesia. It is a stock exchange based in Jakarta Indonesia. DXI is previously known as Jakarta Stock Exchange and was changed after being merged with Surabaya Stock Exchange in 1997. In November 2011, Indonesian Stock Exchange market capitalization was $400 billion or 50.48 percent of Gross Domestic Product (GDP), while U.S. ratio was 100 percent and Singapore with 170.82 percent. DXI had 341 listed companies. Two of the primary stock market indices used to measure and report value changes in representative stock groupings are the Jakarta Composite Index and the Jakarta Islamic Index (JII). There were 30 listed companies in JII.
STOCK INDEX MOVEMENT
Figure 1: Stock Index Movement.
From figure 1, it shows that stock index was drop rapidly in 2009 for all country accept for Indonesia. The rapid drop is due to the economic recession in that year. Thailand is seen to be a very low in their stock index followed by Malaysia.
PLOT OF EXCHANGE RATE DATA
Figure 2: Plot of Exchange Rate Data.
The figure above show the trend of the currency fluctuation of 4 countries involved in this study which are Malaysia, Singapore, Thailand and Indonesia. The figure shows that the Singapore dollar has higher value then other currency. It indicated that the Singapore Dollar has high price compare to the other. The average value from period 2004 until 2011 is around USD 0.7026/1 SGD. The latest was USD 0.8200/1SGD as at 23 November 2012. From 4 countries, Malaysia Ringgit was the second currency that has high value against USD. The average value from period 2004 until 2011 is around USD 0.3120/RM1. The latest values was USD 0.3300/RM
1.2 PROBLEM STATEMENT
Economic globalization has provided a worldwide market for companies willing to operate internationally. Numerous companies increasingly engage in global activities such as outsourcing, exports, imports, and establishment of production and sales abroad (Moosa 2003). In contrast to companies that only operate within a country, multinational companies (MNCs) face gains and/or losses arising from exchange rate risks caused by the uncertainty of the exchange rates prevailing in the future. (Lyna and Feiyi, 2008)
Granger, Huang and Yang (2000) derives a Multivariate model of the research whether currency depreciation led to lower stock prices or whether declining stock prices led to depreciating currencies during the Asian Crisis of 1997. Stock prices are expected to react ambiguously to exchange rates. The authors explain this with the effect of currency changes on the balance sheets of multinational companies. Depreciation could either raise or lower the value of a company, depending on whether the company mainly imports or mainly exports.
Ringgit, Asia's best performing currency in 2010 has appreciated by 6% against the US Dollar, 19% against the Euro and 16% against British Pound on the back of stronger economic fundamental and higher interest rate. The appreciation of Ringgit Malaysia is followed by increasing of economy growth about 10.1% in the first quarters of years, the higher in over a decade. It goes same to the export and it seems to be very well because of the appreciated of Ringgit against the top 3 currency in the world.
There are many macroeconomic variables that could influence and have interaction with shares that will affect its prices. However, there are only certain macroeconomic fundamental that will have high integration with share price in the market. The common macroeconomic factor that influence share price in the global economy is currency exchange.
Many author agreed that the appreciation of Ringgit Malaysia will give big impact stock market. However many author not agreed each other. So, this research was conducted to know how currency fluctuation may affect the value (share price) of selected country in ASEAN. This research also is aimed to reveal which independent variable is able to influence share price directly. Ma and Kao (1990), Timothy and David (2003), Arnold, Nell, and Ryan found that the share price and exchange rate have negative relationship, As the currency appreciated will lead share price rise. John Evans found the same result, but the negative figure indicate the positive movement since he use direct quotation which USD/AUS as an indicator of his research.
1.3 RESEARCH OBJECTIVE
The problem that this study needs to solve is what the relationship between exchange rate and share price. So, the objectives of this study are:-
To identify whether there is a relationship exist between exchange rate fluctuation, past stock price and current stock price of selected countries.
To analyze which variable is the most elastic in explaining the relationship with share price index.
1.4 SCOPE OF STUDY
To be able to answer the research question, historical data from DataStream are used. These studies are focus on 4 ASEAN (Association of Southeast Asian Nation) countries which are Malaysia, Indonesia, Thailand, and Singapore. The data of Exchange Rate or Currency Movement is taken from Data Stream and in daily basis. The share index from each country also was taken in daily basis and five day a week. The share return is in indexes measurement of each country.
The share return for Malaysia is from FBMKLCI, Thailand is from Stock Exchange of Thailand, Indonesia Stock Exchange (DXI) and the last one is Strait Times Index (STI) for Singapore. The period of the study will be from January 2004 until December 2011. I'm limited my analysis of exchange rate risk to 4 exchange rates of USD/MYR, USD/THB, USD/SGD, and USD/IDR. This is due to the specific home currency used in the selection countries. The data that has been collected then will be transferred into Microsoft Excel Format and the research can run the data using STATA software. Lastly, the data were be analyzed to support my finding using Panel data and the result must be efficient and parallel to the hypothesis made in next chapter.
1.5 LIMITATION OF STUDY
There are two obvious limitation occurred in order to complete this research. Thus, the limitation face by researcher to complete this research is as follow:
1.5.1 DATA COLLECTION
In this research, it was very hard to get the suitable data especially for share market index because there are a lot of data available for share indexes in DataStream. The data collected may be limited. As the data gathered from the secondary sources, some the sources found may leads to the less accuracy and reliability of the result. It is because the data provided was fixed and can't be change. So, from the inconsistent or missing data it will affect the results of this study. But some how, this is not really effect the result since the software used can detect the missing data.
1.5.2 REFERENCES MATERIAL
There was a lot of previous study done by researcher and it can be reference sources and useful material for me. But the limitation is the way they run the data is totally different from what we are going to do. So, it was very hard for me to compare the result obtained in this research.
1.5.3 LACK OF EXPERIENCE AND KNOWLEDGE.
In order to complete this research, the researcher needs to read a lot and try to understand the topic chosen very well. Because of lack of experience and knowledge, it a little bit difficult to the researcher. Even before this, researcher has learned how to conduct research in theory but it is very hard to apply in this research studies. The guidance from advisor and the previous research is very useful for me in order to complete this study.
1.6 SIGNIFICANT OF STUDY
By conducting this research, it will help the researcher to better understanding on the reality movement of share price and currency fluctuation in Malaysia. Furthermore, it will help researcher to gain knowledge or expended their knowledge in order to complete this research especially in finding the data and literature review (LR). It also help researcher to relate the reality and the theory that has been learned in class.
Person who is benefits from this research is economist. This is because economist's task is to do research about economy and predict the future economy. Economist is an important person to a country especially as information from them can help government to plan where and when to invest and be more prepared. So, these studies help a lot and can release an economist burden as they need to do a lot of research.
In addition, this thesis also gives an advantage to the investor. This is because by using this study as a guide; they can know what the impact of currency movement to their share price or their market value. As they know, they can see whether it is a good time to invest or not. On the other hand, they can also predict and plan for the future perfectly because they have knowledge on how the economy progress. This result would help the policy makers as well as domestic and foreign investors in Malaysia stock market in their decision making.
Lastly, this research also could be used by manager to determine whether it is necessary to implement hedging strategies against exchange rate exposure or not based on the impact of exchange rate fluctuation on the value of country's stock.
1.7 DEFINITION OF TERM
1.7.1 SHARE PRICE
A stock market or equity market is a public entity for the trading of company stock and derivative at an agreed price which these are securities listed on a stock exchange as well as those only traded privately. The stocks are listed and traded on stock exchanges which are entities of a corporation or mutual organization specialized in the business of bringing buyers and sellers of the organizations to a listing of stocks and securities together. The stock can be trade using primary and secondary market like IPO and Bursa Malaysia.
1.7.2 CURRENCY
In general, currency can be defined as a form of note that legally designed by government as a medium of exchange or for a transaction in order to get goods and services. The money comes into two types, first paper money and the second one is coin. The value of the money against others is called currency and it is different from one country to another country. So the value can be measure by the usage of currency as the indicator and it is standardizing all over the world.
1.7.3 CURRENCY FLUCTUATION
Currency fluctuation refers to the movement of the currency against the home currency. The currency movement can be available in daily basis as well as monthly and yearly basis. The currency will fluctuate every day depend on the supply and demand and also depended on the economic variable such as interest rate and inflation rate. Furthermore many author agreed that the currency fluctuation also depend on the import and export of the particular countries.
1.7.3 EXCHANGE RATE
Exchange rate can be defined as current market price of one country that can be traded or exchange to another country. Exchange rate also is a mechanism for a country to convert their currency to another foreign currency for example Malaysia Ringgit to USD. It also can be known as foreign exchange rate or rate of exchange. USD is a main currency that other country is often using. The top largest currency in the world is Euro and USD. The exchange process can be made in direct or indirect quotation depends on that countries and transaction made. The exchange rate is very important to everybody to make a transaction abroad and they also can predict the next future rate using forward rate. The exchange rate risk can be controlled using swap and hedging strategies.
1.7.4 SHARE MARKET @ SHARE INDEX
Share Market is a place where the share (stock) of listed companies can be traded. The larger stock market in the world is New York Stock Exchange (NYSE). For Malaysia the stock can be trade at FTSE Bursa Malaysia KLCI (FBMKLCI). The information available in share market included top listed companies and the value (market capitalization), chart, profile and other market data.
1.8 ORGANIZATION OF CHAPTER
This chapter will cover on the essential element needed to define and fill the gap regarding the issues highlighted throughout the study. The chapter will briefly elaborate on introduction of study, background of study, problem statements, and the significance of the study, research scope as well as the limitations of this study.
Chapter 2 will cover on the Literature Reviews on the past research done by many author all over the world. It is about the empirical research that was similar with this research. This chapter containing the Literature Reviews on the both independent variables and dependent variable which are Share Price, Exchange Rate and also Past Share Price.
Chapter 3 will cover on the Research Methodologies. This chapter will briefly elaborate on the data collection, research design, theoretical framework, hypothesis, data retrieve, and data analysis and administration.
The most important part in this research is in Chapter 4. In this chapter, researcher will highlight and discuss the result obtained from the Stata program that processes the multiple data. Researcher then will try to imitate the result own by the previous literature. In order to compare the previous literature result with the study conducted, researcher must possess reliable source of data that is sufficient to cover the census and reflect the previous study. The comparison for the latest and previous objective will led to a new dimension of result. To analyse the relationship between a dependent variable and two or more independent variables, research will be use Multiple Regression in order to determining whether there is positive or negative relationship.
Lastly in chapter 5 containing summary and a view on the result of the data obtained from the regression table in chapter 3. Author also may include some useful recommendation for future researcher whom wish to conduct similar study regarding this topic.
CHAPTER 2
LITERATURE REVIEW
2.1 EMPIRICAL STUDIES ON SHARE PRICE AND EXCHANGE RATE
The major role of the stock market nowadays is to provide a medium of exchange of ownership of companies' shares and act as a mechanism for companies to raise their capital. This role gives a market place an opportunity where the transaction of purchases and sales can be made and where share prices can be determining by supply and demand relationships. The need for and the success of the stock market for a company and country can be prove by the fact that the majority of major companies all over the world have their own equity capital quoted. (Firth, 1977).
The fluctuation of currency may give a big impact to the firm value. Arnold, Nell and Ryan (2011) investigated the impact of different currencies under the two accounting rules and found that it did make a difference in investors' ability to discern the impact on firm value. The research was conducted using three different time frames which are 2011 second quarter percentage change in share price, monthly dollar change for the first two calendar quarters for 2011, and the monthly percentage change in share prices for the same period as dependent variables. They concluded that there was a significant relationship between currency risk (using the U.S. dollar as the benchmark currency) and stock market performance. The result also indicates that a correlation between exchange rate effects on the cash flow statements and changes in share prices.
According to Dimitrova (2005), in her research of the relationship between share price and the exchange rate, she assume that in period of one month to three month trade flows also play a role in determining the demand for share. But the result of her study is contrary with what her expect because of different in time frame assumption.
Foreign currency exchange rates are among the most important prices in a country's economy. Changes in exchange rates should therefore have a significant effect on the performance of firms involved in international activities. Firms engaged in international transactions are subject to transaction risk arising from payable and receivables in foreign currencies. In addition, multinational firms will have translation risks from having assets and liabilities denominated in foreign currencies. Gary and Peter examine the relationship between the exchange rate and the UK share price of individual firms and the sample was taken from importers and exporters firm. The result indicates that there is a weak relationship between firm value and exchange rate by using data from questionnaires of 298 listed companies in UK. The result also shows that importers and exporters are affected differently.
Golaka and Samanta (2000) believe that the depreciation and appreciation of domestic currency may be able to influence the share price and also affect the value of the firms or countries itself. Granger causality test have been done using the data of daily stock market index and exchange rate (expressed in Indian Rupee per U.S. dollar) for India. The data is in daily basis for the period March 1993 to December 2002. The result shows that the return in stock market had causal influence on return in exchange rate with possibility to influence in reverse direction, meaning that in negative relation. Contrast with Mahmudul and Gazi (2009) in his studies, he illustrate that stock market returns and exchange rates movements are positively related.
Empirical studies suggest that change in exchange rate will affect the competitiveness of a firm value because the fluctuation of exchange rate causes them to borrow money abroad in a foreign currency in order to fund their business. These will cause the movement of the share price too. Timothy and David (2003) investigate the impacts of exchange rate movement on the stock market valuation of a firm. They using weekly data from Standard & Poor (S&P) Emerging Database for 15 companies from various countries and the result show that the impacts of depreciation on stock return is negatively related and also found that firm's foreign currency debt outstanding are important determinants of exchange rate exposure.
In contrast, Abdullah, Sarkar, and Omar (2012) studies about the relationship between exchange rate and stock prices is increasingly getting momentum in global financial markets especially in the wake of the Asian financial crisis of 1997-1998. This study using Granger causality approach using monthly data to test whether change in exchange rates lead to changes in the stock market in Bangladesh. Overall, the empirical result obtained in this study reveals that foreign exchange rates and stock prices movements do not Granger cause each other in Bangladesh. In other words, the two major financial markets in Bangladesh do not seem to have influence on each other.
John, Dilip and Yang (2009) had completed a study to examine the return of stock market using daily data of 27 countries around announcement of devaluations. The result also indicate negative relationship but he argued that the negative figure indicated the positive co-movement between the two variable because he using the direct quotation as an indicator of currency. In their research, they also mention that they used the data of Australia currency per unit of USD, that why the negative result assume to indicate a positive co-movement.
Meanwhile, according to John Evan (2009), in his research, he investigate the relationship between stock prices and exchange rates in Australia and then expanded the analysis to investigate the changes in these key economic variables and the relationships between those changes through the process of the Granger causality test. The database was collected from 1979-2004 for all announcements of currency devaluations by countries for which we have stock market data. The result indicates that there is a strong positive relationship existed between the two variables during the period. He also found that the Australian stock market has the depth and liquidity to adequately compete for domestic and foreign capital against other larger markets in Asia, Europe and North America.
Contrary with Lyna (2008), she investigates if currency exchange rate movements impact the stock return of European based car companies with market interests in the US. By selecting a various car companies which, French Renault and Peugeot, German Audi and BMW and Swedish Saab and Volvo, with three different currencies exchange rates which are SEK/USD, SEK/Euro and Euro/USD. In her research, she included three major macroeconomic factors such GDP, stock market index and Oil price to perform a multiple regression analysis. The result indicates that five over six companies in three exchange rate not significant influence in share price. The only companies that showing significant effect to share price is BMW because the companies not applying hedging strategies in it business and taransaction abroad.
Komain (2012) had conducted a study of the linkages between Thai Stock and Foreign Exchange Markets under the Floating Regime and the data used in this study is in monthly data of stock market index from the Stock Exchange of Thailand from period covers July 1997 to June 2010 with 156 observations, and the nominal bilateral exchange rate was collected in same time period in terms of baht per U.S. dollar from the Bank of Thailand. The result indicates that there are bidirectional causal relations between stock market risk and exchange rate risk in negative directions.
According to Investopedia of US, the share price is difficult to predict but by drawing a chart and looking the past price movement, investor is able to know and predict the next share price. So those, investor can easily make a decision whether to buy or sell their share in short or long term. This also has been supported by a book which is Fundamental of Investment written by Gitman, Joehnk and Smart (2011). The market price forces an ability to change the share price every day. This means, the share price change because supply and demand. If more people want to buy because of the favorable price, then the price will move up. Conversely, if more people wanted to sell a stock because the price is not favorable enough, then there would be greater supply then demand. It can lean to the fall in price. Logically, when yesterday price is not favorable, people tend to sell it and it may affect the next share price. So that, assumed that past share price may affect the demand and supply of today share price and automatically able to influenced today share price.
Dimitrova (2005) study on the exchange rate and found that effect of exchange rate depreciation will be different from each counties depending whether it is a import base or export base, whether it own foreign unit and whether it hedged against exchange rate fluctuation. He also mentions that there are three importance of the currency prediction to economic. The first one is the currency fluctuation is able to affect decision about monetary and fiscal policy because booming stock price has a positive effect on aggregate demand. The second one is research on currency movement can benefit MNC's in managing their exposure to foreign contract and exchange rate risk. The third is, he argued that the research on currency is very beneficial since the currency often being included as an asset in investment portfolio.
Stuart (2007) mentions in his research that the changes of exchange rates and interest rates should affect the value of the firm. In his research, he investigates the sensitivity of stock returns to the exchange rate and interest rate shocks in the four major European economies. The result indicates that most of industries in selected countries have significant impact to the exchange rate risks.
Alok (2005) had examined whether stock market in India and foreign exchange markets are related to each other or not. The data used is monthly stock return, exchange rate, interest rate and demand for money from April 1992 to March 2002 and run using Granger's Causality test and Vector Auto Regression technique. By using Vector Auto Regression the result showa that stock return, exchange rate return, the demand for money and interest rate are related to each other there are no relationship exists between them.
Conversely, changes in stock prices may also affect exchange rates.Hsing (2008) was studied on the impacts of the stock price and country risk on the exchange rate in Singapore. He found that the real exchange rate in Singapore is positively affected by the real stock index. Mean that if the stock index was increase then the currency is expected to appreciate against the foreign currency.
A study on the relationship between stock prices and exchange rates in Korea by Hwang indicates that the domestic currency devaluation has a negative short-run effect on stock prices. The data collected in monthly stock market indices and exchange rates for the period of 1980 to 1997. Monthly data on the stock market index are obtained from Korean Stock Exchange Market and monthly bilateral exchange rates of the won-dollar are obtained from International Financial Statistics. They also found that the two variables are cointegrated between two variables for the case of Korea
Ajayi and Mougoue (1996) examined the relation between stock prices and exchange rates for the developed countries. The daily data was collected from April 1985 to July 1991. They found that an increase in aggregate stock price has a negative short-run effect on domestic currency value because of inflation expectations, but increases in domestic stock prices induces domestic currency appreciation in long-run. However, in their research they also found that currency depreciation has a negative short-run and long-run effect on the stock market.
Muhammad and Rasheed (2002) examines whether stock prices and exchange rates are related to each other or not. The study uses monthly data on four South Asian countries, including Pakistan, India, Bangladesh and Sri- Lanka. The monthly data was collected from period of January 1994 to December 2000. They employed 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. The results of this study show no short-run association between the variables for all four countries and there is no long-run relationship between stock prices and exchange rates for Pakistan and India as well. They argued that it maybe due to the policy, political uncertainty and investment factors.
CHAPTER 3
RESEARCH METHODOLOGY
3.1 MODEL SPECIFICATION
This research studies the several determinant of stock price movement, It uses macroeconomics panel data set (2004-2011) consisting of 1 dependent variable and 2 quantitative independent variables. It is derived into log-log form as the result can be used to determine the elasticity of each variable. Then the data is regressed using Stata10 as all data is represented in numbers.
3.2 DATA COLLECTION METHOD
There are two kind of data which, primary data and secondary data. Primary data is collected by the researcher himself/herself for example, Questionnaire, interview, observation and also experiment. Secondary data refer to the data that already been collected by others researchers for the others purposes. The example of secondary data is from DataStream, Bursa Malaysia website, UNdata, World Bank data and also from companies' annual report. For this research I'm decided to use secondary data. The data, firstly collected from DataStream of University Technologies Mara and was transferred into Microsoft excel format. The data collected included the daily currency of four (4) ASEAN countries which USD as the home country. USD currency was selected as home currency because to standardize the data. A part of that, I'm also searching for the stock price. Because of this research are included 4 difference countries, so that I use stock market index for each countries which FBMKLCI for Malaysia, DXI for Indonesia, SET for Thailand and STCI for Singapore. All the data were collected in daily basis and it is from same time period which from 01/01/2004-30/12/2011.
3.3 RESEARCH METHOD
3.3.1 THE MODEL
lnSPi,t= α+ lnβ1(ER) + β1SP t-1 (SPi,t) + ui,t
Equation 3.1
Where:
SP i,t = the share index of a country i at time t
ER i,t = the exchange rate of a country i at time t
SP t-1(SP i,t) = the share index of country i at time t-1
SIGN
TYPE
DESCRIPTION
EXPECTED SIGN
ln(SP i,t)
Dependent variable
log of Stock Index of Country
-
a
Constant value
Constant term for each countries
-
ln(ER i,t)
Independent variable 1
log of currency @ exchange rate
Positive (+)
Ln(SP i,t-1)
Independent variable 2
log of Stock Index of Country at
t-1 (late one day)
Positive (+)
Ui,t
Random error term
-
Table 3.1: Variable (Sign, Type, Description and Expected Sign)
With respect to the theoretical model, we can predict that stock price movement of a country is depended on current exchange rate, and late one day share price (SP-1). Researcher introduce a few additional variable in equation which late one day share price. This inclusion has the following theoretical support. So, researcher use the share price expectation, assuming that the next period (day) share price adjust to be observed by share price this period. Thus many author expected that higher share price in last day will have positive impact on the stock price in the next day. Dilip, John and Yangru, 2009 in their research of the local stock market reaction to currency devaluation by a country central bank. They found that stock market drop more if the currency had greater past real depreciation. They strongly believe that the currency drop/ fall, the capital account (share price) will decrease more.
3.3.2 DATA RETRIEVE
3.3.2.1 Share index
Share price index is a dependent variable in this study. Data of share price index is collected from Data Stream consist of 4 ASEAN countries in the period of 2004 to 2011. The data value is described in index number.
3.3.2.2 Exchange Rate
An exchange rate is an independent variable in this research and it seems to have a close relation with share market. This data is also collected from Data Stream consist of 4 ASEAN countries for 8 years (2004-2011). The data is described in the currency of US against other currency. The currency is quoted in American Term as indirect quotation outside of United State. When the exchange rate increase, it means that the currency have a lower value and depreciates against US dollar.
3.4 THEORETICAL FRAMEWORK
The relationship between these variables has been schematically illustrated in figure above. The relationship among the dependent and independent variables will be explained in logical statement.
INDEPENDENT VARIABLES DEPENDENT VARIABLE
EXCHANGE RATE
SHARE PRICE
(STOCK INDEX)
SHARE PRICE (t-1)
Based on the figure above, it shows the theoretical framework diagram share price in Malaysia. The elements for this study are exchange rate and share price -1. It is necessary to distinguish clearly between the terms of dependent variable and independent variables in order to fulfill this research. Dependent variable is a characteristic that change when researcher implement the independent variables. While, independent variables is a concept that hypotheses or believed to cause, influence or lead to variation in the dependent variables.
The Dependent variable is Stock Price. The major role of the stock market nowadays is to provide a medium of exchange of ownership of companies' shares and act as a mechanism for companies to raise their capital. Stock market and economy is said to have strong relationship. In theory, many people and economist agreed that the movement (rise and fall) of economy will affect the performance of stock market. This can be proved, when the economy is booming, it will lead to a higher performance of a company, it will result to an increase in share price. Investors will only interest to invest into a highly performed company. The demand for share price will increase when companies was performed well. Therefore, as applied by basic economic, when demand increase, price of goods also will increase.
The first independent variable is currency fluctuation or exchange rate. Currency is varies day by day. Many authors believe that the currency fluctuation has a positive relationship with share price. That mean, when a currency is expected to be appreciated and thus the share price also is expected to increase in price. Empirical studies suggest that change in exchange rate will affect the competitiveness of a firm value because the fluctuation of exchange rate causes them to borrow money abroad in a foreign currency in order to fund their business. These will cause the movement of the share price too.
The second independent variable is past share price. Past share price also can influence the movement of current share price. This inclusion has few theoretical supports. But it is relevance, since the increasing in last share price may reduce the demand of that particular share and able to affect the share price in the next day. The market force is an ability to change the share price every day. This means, the share price change because of supply and demand. If more people want to buy because of the favorable price, then the price will move up and vise-versa. If price is unfavorable, people will make a decision not to buy that particular share. So that past share price and current share price is positively related each other.
3.5 HYPOTHESIS
In general knowledge, hypothesis can be defined as a statement that we predict through the data. According to Sekaran (2010) she defined hypothesis as logically conjectured relationship between two or more variables expressed in the form of testable statements.
In this research, the researcher will use two types of hypothesis which is called null hypothesis and alternate hypothesis. . Null hypothesis is a rejected statement where there is no significant between the independent and dependent variable. It is different with alternate hypothesis; it is statements in support the independent and dependent variable are significant.
H0= will represent the null hypothesis
H1= will present the alternate hypothesis
Exchange Rate and Share Price
H0= There is no relationship between exchange rate and share price
H1= There is a relationship between exchange rate share price
Past Share Price and Share Price
H0= There is no relationship between past share price and current share price
H1= There is a relationship between past share price current share price
3.6 DATA ANALYSIS AND ADMINISTRATION
Firstly, the raw data taken from database was paste into the Microsoft Excel software to be modified due to the model restrictions. The data should be modified in an appropriated column before preserve in STATA Software. Then, the data need to be sort by Year, Code, DV and IV to make sure the command in STATA can easily run by researcher. Then, all data has been converted into a natural log value (ln10) before being analyzed using STATA software and the command is log value (ln). Descriptive statistics has been prepared to give a brief interpretation of the data, for example mean, max, min, standard deviation and lastly Coefficient of Variation (CV). The model is tested using Pooled Ordinary Least Square (POLS). In order to know the data can be test using pool or panel data, the Breusch and Pagan Lagrangian Multiplier Test should be run.
3.6.1 Pooled Ordinary Least Square (POLS)
According to Podestà (2002), pooled analysis combines time series for several cross-sections and it is characterized by having repeated observations on fixed units. It means that pooled analysis combine cross section data and time series data in one model. The generic pooled linear regression model is estimable by Ordinary Least Squares (OLS) procedure:
(equation 3.2)
While Philippe Polomé (2010) indicates that the most restrictive model is a pooled model that specifies constant coefficients, the usual assumption for cross-section analysis.
(equation 3.3)
This is so that if this model is correctly specified and regressors are uncorrelated with the error then it can be consistently estimated using pooled OLS. The error term is likely to be correlated over time for a given individual the usual reported standard errors should not be used as they can be greatly downward biased. Furthermore, the pooled OLS estimator is inconsistent if the fixed effects model is appropriate (i.e. if the error term is correlated with a regressor). (Philippe Polomé, 2010)
3.6.2 Test for Multicollinearity
According to Gujarati (2003), the term multicollinearity originally meant the existence of a "perfect" or exact linear relationship among some or all explanatory variables of a regression model. This means that two or more independent variables give the same exact relation towards dependant variable causing the relationship to be redundant. For the k-variable regression involving explanatory variable X1, X2,…., Xk (where X1 = 1 for all observations to allow for the intercept term), an exact linear relationship is said to exist if the following condition is satisfied:
λ1X1 + λ2X2 + … + λkXk = 0
(equation 3.4)
Where λ1, λ2,…, λk are constants such that not all of them are zero simultaneously. However, for the case where the variables are not perfectly intercorrelated the equation is as follows:
λ1X1 + λ2X2 + … + λ2Xk + vi = 0
(equation 3.5)
Cameron (2005) state that the total absence of multicollinearity occurs when there is no correlation between any combinations of the independent variables which is also called as orthogonality. It means that a set of bivariate regressions of y on each of the X's in isolation will give the same set of results for the parameters as will be found in the full multiple regression. However, the R-squared and standard errors of the coefficient estimates will certainly change.
Multicollinearity problem is tested using the test of variance inflation factor (VIF) in the STATA. The data is determined to have multicollinearity problem when the mean VIF appears to be over that 5. However, if the mean VIF is less than 5, the data is considered free from multicollinearity problem. Another way to estimate multicollinearity is based on R-squared. If the R-squared appears to be high, it is possible that the data have multicollinearity problem.
3.6.3 Test for Heteroscedasticity
Based on Cameron (2005) heteroscedasticity is a violation of the assumption of constant variances of the error term (homoscedasticity). He also state that when an equation has heteroscedasticity in its error term, the OLS estimator would still be unbiased, however it will not be in minimum variance. Also, the hypothesis tests on regression coefficient would be inaccurate due to the existing heteroscedasticity problem. The presence of heteroscedasticity in the data will influence the result to be more inclined to reject the null hypothesis than it supposed to be.
The test of heteroscedasticity is conducted using Breusch-Pagan / Cook-Weisberg Test by using STATA software. The problem is determined using the following hypothesis:
H0: No heteroskedasticity problem exists
H1: Heteroskedasticity problem exists
Therefore, based on this hypothesis when the chi2 p-value is significant, it denotes the rejection of null hypothesis that no heteroscedasticity problem exist. This means that the data have heteroscedasticity problems. Meanwhile, the contrast will happen when Breusch-Pagan / Cook-Weisberg test shows insignificant chi2 p-value.
3.4.4 Test for Serial Correlation
Serial correlation (also called "autocorrelation") is said to exist when the error terms of any pair of observations are correlated with one another. In other words, the error terms are not independent of one another and thus the covariance is not equal to zero. According to Wooldridge (2001), the serial correlation needs to be tested because the data and model that is supposed to be dynamically complete in the conditional mean should not have any correlation in their error term. Also, serial correlation needs to be tested to to see whether we should compute a robust variance matrix estimator for the pooled OLS estimator
Serial correlation problem will be tested by using Wooldridge Test for serial correlation. The determination in this test is similar with heteroscedasticity test whereby when the result shown a significant f-value, thus it indicates the rejection of null hypothesis and the acceptation of alternate hypothesis. This denotes that there is a significant serial correlation with the dataset used by the model. The contradict will happen when the f-value produce by the Wooldridge test is not significant. The hypothesis for this test is as follows:
H0: No serial correlation problem exists
H1: Serial correlation problem exists
CHAPTER 4
DATA ANALYSIS, RESULT AND DISCUSSION
4.0 INTRODUCTION
In this chapter, researcher aimed to discuss and highlight the result obtained from STATA software by using multiple data of 3 variables which included dependent variable. The researcher try to compare the result obtained with previous study done by the other researcher all over the world. The result obtained may be able to answer the entire research objective made in earlier stage of this research. This chapter also is aimed to know which hypothesis can be rejecting or accept. In order to analyse and reveal the relationship between a dependent variable and two or more independent variables, research will be use Multiple Regression in order to determining whether there are positive or negative relationship between variable. In this chapter, researcher will explain on the descriptive statistics, the correlation between variable, and the coefficient of variable, in order to make sure the result and finding is easy to understand by others. Additionally, researcher also explains a several test to ensure the data used in this study is problem-free such as Multicollinearity test, Heteroskedasticity test, and Serial correlation test. To test all the problem, researcher use Variance inflation Factor (VIF) test to check on multicollinearity problem, Breusch-Pagan / Cook-Weisberg Test for Heteroskedasticity and Wooldridge Test for Serial Correlation.
4.1 DESCRIPTIVE STATISTICS
The table below shows the statistical result of the data. These statistics are; maximum, minimum, mean, variance, standard deviation and coefficient of variations. The descriptive statistics related to the stock index and macroeconomic variables are presented in the following table.
Table 4.1: Descriptive statistics
The table above shows the summary of variables and it explained the details about all the variables included in this research. The symbol max is stand for maximum, thus, the figure indicate the maximum amount of each variable. In this case, the maximum value for currency is USD 0.8328 and for the stock indexes are 4193.438. The minimum value for currency is USD0.000026 and for stock indexes are 384.15. In this research, researcher was using American Terms, so it is an indirect quotation in respect of Malaysia. Therefore it gives a US Dollar price unit of foreign currency. The higher max amount of currency is USD 0.8328 and it is due to the Singapore Dollar currency. Therefore higher value indicates that the SGD has lower value against US Dollar but has higher value against others currency. The minimum amount of USD0.000026 is represent by Indonesia (Rupiah) and its show that the Rupiah has a very low value against USD compare to the others. The mean statistics above shows the average value for each of the variables amongst the selected countries. In additional, the higher value of mean can contribute to the higher value of Coefficient of Variation (CV). This is because CV is calculated by dividing the standard deviation with the mean of each variable.
The higher value in mean show the data is less similarities. Thus, less similarity of data are more preferable because it will give an accurate result. The stock index data is more accurate and precise because its shows a lowers result of CV which 0.5682.
4.2 CORRELATION
Table 4.2: Correlation table
Based on the table above, we can see that all figure shows positive value. The positive figure reflects a positive relationship between the stock market and the other independent variables. For the currency variable, it shows that currency and share price have a strong relationship with the stock market.
4.3 POOLED ORDINARY LEAST SQUARES (POLS) REGRESSION
Table 4.3: Pooled Ordinary Least Squares (POLS) Regression
The analysis starts with the Pooled Ordinary Least Squares (POLS) Regression. This analysis is carried out in order to determine the relationship and the coefficient of each variable involved. From Table 4.3, the value of adjusted R-squared is equal 0.9995. This value indicates that 99% of the total variation in share price is explained by exchange rate and past share price. The other 1% is explained by error term (ui) and others variable that are not included. Pooled Ordinary Least Square Model (POLS) is employed in this research to examine the simultaneous effects of several independent variables on a dependent variable charted on an interval scale. It is the basic approach employed in estimating the panel data. From the table, it shows that the both variable is significant. The exchange rates (currency) were only significant at 10% significance level, while the past stock index is significant at 1% significance level. It means that the model is significant and thus, supports the rejection of the null hypothesis and the alternate hypotheses are accepted. The hypothesis also can be written as:
H0 : β1 = β2 = β3 = β4 = β5 = 0
H1 : at least one of the β 0
INDEPENDENT VARIABLE
COEFFICIENT
PROBABILITY (p-value)
α
0.0015
0.394
Currency (Exchange Rate)
-0.0000664
0.099
Stock Index
0.999804
0.000
Table 4.4: The Relationship among Variable.
ln(SIi,t) = 0.0015 - 0.0000664 ln(ERi,t) + 0.999804 ln(SIi,t-1)
Equation 4.1
4.3.1 RELATIONSHIP BETWEEN EXCHANGE RATE AND SHARE PRICE
The result shows that the exchange rates have a negative relationship with the stock market. In earlier stage, we expect that the currency variable have a positive relationship between the stock market. Meaning that, the appreciation in local currency will lead to the increasing in share price. But in this research, researcher found that there was a negative relationship which -0.0000664 between currency and share index. Means, when 1% increases in Exchange Rate, Share price will reduce by only 0.006%. This result also has been supported by a few previous researcher such as Golaka and Samanta (2000) and Arnold, Nell and Ryan(2011). In their research, they found that share price and domestic exchange rate have a negative relationship. Ma and Koa(1990) suggest that, currency appreciation negatively effect the domestic stock market for an export-dominant countries. In theory, when investors buy shares from foreign companies in foreign country, the transaction is made in foreign currency.
The local companies need exchange the local currency to foreign currency. Therefore, the fluctuation in exchange rate will affect the demand for buying foreign shares and also local share. When USD (foreign) depreciates against local currency (MYR), it will increase the demand of foreign share. The appreciation of local currency cause higher buying power of Malaysian and lead decreasing in Malaysia share price. It shows, there was a negative relationship between this two variable. In addition, the currency and share price will change (fluctuate) everyday, that why these two variable is very close impact each other. This result is parallel with what the researcher expected in earlier stage of this study.
4.3.2 RELATIONSHIP BETWEEN PAST SHARE PRICE AND CURRENTSHARE PRICE
The tables 4.4 above also explain the relationship between last share price and current share price. In respect of last share price, researcher using late one day price (t-1). The result shows that the past stock price has a positive relationship with the current share price. The p-value of last share price is 0.9998. The OLS regression result reports shows that 1% increase in last share price, the current share price will increase by 99%. Researcher predicts that the today stock price of particular countries is dependent on last share price. This inclusion has few theoretical supports. It is relevance, since the increasing in last share price may reduce the demand of that particular share and last will also affect the next day share price. . Based on the result, last share price is the most elastic variable compared to the other one variable. This elasticity means that the variable have a higher considerate amount of responsiveness towards the share price index. This result is parallel with what the researcher expected in earlier stage of this study.
Y (share price)
Ui (error term) *
* β = 0.999804
* *
* *
* *
α = 0.0015
X (last day share price)
Figure 4.1: Slope of OLS Line
Figure 4.1 shows a slope of OLS line and it shows how much y is predicted to change when x change by one unit or 1%. The line shows the last share price has strong positive relation. The line can summaries the general trend of the data. To make the result more precise and to answer the third research objective, researcher tries to run the data one more times. As mention the first data was running in general, which the data are consist of 4 countries and 8 year length of times. So to make sure the result more precise, the data was run specifically by each country and the result of POLS Regression are reported as below.
4.4 POOLED ORDINARY LEAST SQUARES (POLS) REGRESSION FOR EACH COUNTRY
4.4.1 MALAYSIA
Table 4.5: Pooled Ordinary Least Squares (POLS) Regression for (Malaysia)
4.4.2 SINGAPORE
Table 4.6: Pooled Ordinary Least Squares (POLS) Regression for (Singapore)
4.4.3 THAILAND
Table 4.7: Pooled Ordinary Least Squares (POLS) Regression for (Thailand)
4.4.4 INDONESIA
Table 4.8: Pooled Ordinary Least Squares (POLS) Regression for (Indonesia)
Table 4.5 show the POLS Regression for Malaysia by representing by Malaysia Ringgit and FBMKLCI as an indicator of exchange rate and stock market. It shows the p-value or the probability for currency is not significant at 1%, 5% and 10% significance level but have a positive relationship. The Malaysia Ringgit has slightly positive relation with the Malaysia stock market. All result for each countries result shows that the exchange rate is not significant at 1%, 5% and 10% significance level. But all currency has positive relationship with the stock index except for Rupiah (Indonesia). It might due to the very small value of Rupiah against US Dollar. It might affect the accuracy of the result. The adjusted R-squared for all countries shows up of 90% variation of dependent is explained by all independent variable.
4.5 TESTS FOR MULTICOLLINEARITY
Table 4.9: Variance Inflation Factors (VIF)
Table 9 above shows the VIF table to explain multicollinearity exist in this research. According to Gujarati (2003), the term multicollinearity originally meant the existence of a "perfect" or exact linear relationship among some or all explanatory variables of a regression model. This means that two or more independent variables give the same exact relation towards dependant variable causing the relationship to be redundant. When the value of VIF is above then 5 (VIF > 5), then the regression is said to have multicollinearity problem. When multicollinearity existed, it could influence the regression result to be bias and therefore unreliable as it will lead in misinterpreting the result. Multicollinearity also can be detected by look at the adjusted R-square. When adjusted R-squared is too high, the multicollinearity has a high chance to exist. So, in this case, VIF equal to 1.00 thus no multicollinearity problem exist in this data. if multicollinearity exist in our data, we need to drop 1 or more independent variable or add another variable. That how the problem of multicollinearity can be cure.
4.6 TESTS FOR HETEROSKEDASTICITY
Table 4.10: Breusch-Pagan / Cook-Weisberg Test for Heteroskedasticity
The other test need to conduct is test the problem of heteroscedasticity. Heteroscedasticity existed when the variance of dependant variable or standard errors rambled across the data. This problem could make the result to be misleading. In this study, Breusch-Pagan / Cook-Weisberg test is applied in estimation heteroscedasticity problem. Based on the test result in table 4.10, the chi2 value is 0.0004 which significant at 5% and thus it means that there is heteroscedasticity problem with the data being used. The problem is determined using the following hypothesis:
H0: No heteroskedasticity problem exists
H1: Heteroskedasticity problem exists
4.7 BREUSCH AND PAGAN LAGRANGIAN MULTIPLIER TEST FOR RANDOM EFFECTS
Table 4.11: Breuschand Pagan Lagrangian Multiplier Test for Random Effects
The test is conducted to examine either the POLS or Panel Data Analysis (PDA) can be used for further analysis. Based on Table 4.11, the p-value of chi is more than 0.05. It means that the model is not significant at 5%, and thus, sup
