stock prices and exchange rates are they related.evidence from karachi stock exchange on tobacco...
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Stock prices and exchange rates
RELATIONSHIP BETWEEN STOCK PRICE AND EXCHANGE RATES
Stock Prices and Exchange Rates: Are they Related?
Evidence from Karachi Stock Exchange on Tobacco Industry.
Ainy Ather
Faisal Pervaiz
Hina Arif
Sabrina Irshad
Syed Zaki Uddin Hussain
BBA-H
Department of Business Administration
IQRA University, Karachi
Stock prices and exchange rates
Stock Prices and Exchange Rates: Are they Related? Evidence from Karachi Stock
Exchange on Tobacco Industry.
Abstract
This paper examines whether stock price and exchange rates are relater to each other or not. The
study uses monthly data of exchange rate of Dollar to PKR and the stock prices of the three listed
companies in tobacco sector of KSE-100 index namely Lakson Tobacco, Khyber Tobacco, and
Pakistan Tobacco for period of January 2003 to December 2007.Bivariate Correlations and
Regression test is employed to examine the association between stock price and exchange rate.
The result of this study shows the association between the said variables Stock Prices of three
listed Tobacco companies are dependent of Exchange Rates.The results have implications for
investors, policy makers and academicians.
Stock prices and exchange rates
Introduction
Over the past few years’ considerable attention has been received by the stock prices and the
exchange rates Beer and Hebein (2008). The Asian Financial Crises which started in July 1997
gave this issue its due attention. The following crises, in the effected countries gave rise to the
chaos in the money and stock markets. This resultantly also effected the exchange rates. Granger
et al. (2000) examined the relationship between exchange rates and stock prices for nine Asian
countries during the Asian financial crisis and found that exchange rates and stock prices were
not co integrated in any of the countries. Hence we can say that if a relationship between the two
markets exists, then the investors could use this information for predicting one market’s behavior
on another.
Due to the increasing trend toward globalization in financial markets, a substantial amount of
research has been devoted to the investigation of the correlation of stock returns across
international markets. According to Eun and Shim (1989), Hamao et al. (1990), and Bekaert and
Harvey (1996), it is extensively believed that varying exchange rates have an effect on the
competitiveness of firms busy in global competition. A declining home currency promotes the
competitiveness of firms in home country by allowing them to undercut prices charged for goods
manufactured overseas (Luehrman, 1991).
According to the traditional models of open economy relationship between the stock market
performance and the exchange rate; behaviour exist (Dornbusch and Fischer, 1980) and suggest
that changes in exchange rates affect the competitiveness of firms as fluctuations in exchange
rate affect the value of the earnings as well as the cost of its funds (as many companies borrow in
Stock prices and exchange rates
foreign currencies to fund their operations and hence its stock price). A depreciation of the local
currency makes exporting goods attractive and leads to an increase in foreign demand and hence
revenue for the firm and its value would appreciate and hence the stock prices. On the other
hand, an appreciation of the local currency decreases/increases the exporting/importing firms’
profits because it leads to a decrease in foreign demand of its products (Gavin, 1989).
The expected returns from the investment in foreign stocks are determined by changes in
local stock price and currency values. If the effect of exchange risk does not vanish in well-
diversified portfolios, exposure to this risk should command a risk premium. Therefore, the
interaction between currency value and stock price is an important determinant of global
investment returns (e.g., Doong et. al., 2005).
This research is carried on the basis of exchange rates and stock prices of KSE listed 3
tobacco companies namely, Pakistan Tobacco Company Limited, Khyber Tobacco Company
Limited, and Lakson Tobacco Company Limited. It began with a 50 share index and was grown
with the requirement. The KSE 100 index was introduced on November 1st, 1991 and today is
one of the most accepted measures of exchange. This index is also used to compare the prices of
the whole stock exchange over a period of time. It is one of the most widely and extensively used
exchange rates in the country.
Pakistan’s tobacco industry is one of the industries in Pakistan which also has a significant role
to play in the country’s economy. It is one of the largest taxes paying industry of Pakistan. This
industry has higher taxes and its product is advised against by the government and many other
people, it is still widely used and an important sector. Despite of the stigma attached to this
Stock prices and exchange rates
sector not only in Pakistan but around the world, it is still a major source of income for both the
government and the people. It is also one of the largest sources of direct and indirect
employment for the people.
If any relation between the two exists then this information could be made to use by the investors
in order to predict the behavior of one market on another. It can tell how one market or in
specific the change in one market would impact the other market or how will the other market be
effected. This information could be utilized to understand the relationship between the two
markets.
The purpose of this report is to find a relationship between stock prices and exchange rates of
Pakistan. It makes use of the stock prices of the exiting three tobacco companies in the stock
exchange and monthly Rates of the dollar value from 2003-2007. This research make of
Correlation and regression. This research tells how one market or in specific the change in one
market would impact the other market.
Literature Review:
This thesis deals with the existence of relationship between stock prices and exchange
rates. Researchers all over the globe have given most of their attention in determining the
existence of relationship between stock prices and dollar rate. Franck and Young (1972) were
among the first authors to analyze the association between stock prices and dollar rates. Using
correlation regression analysis, they reported significant interactions. Aggarwal (1981) finds that
the US stock prices and the trade-weighted dollar value are positively correlated.
Stock prices and exchange rates
Our main focus would be on two portfolio models which explain the interaction between
exchange rate and stock prices. First the ―Flow-Oriented‖ model (Dornbusch and Fischer, 1980
and Gavin, 1989) suggests that fluctuations in exchange rates affect the competitiveness of firms
and also the balance of economy. Secondly is the ―Stock-Oriented‖ model (Branson, 1983 and
Frankel, 1983) where the stock market exchange rate link explained through a country’s capital
accounts.
Flow- Oriented Models states that the exchange rate is determined largely by a
country’s current account or trade balance performance. The changes in exchange rates affects
global competitiveness and trade balance, thereby influencing real economic variables like real
income and output (Dornbusch and Fisher, 1980). Stock prices, are basically defined as a current
value of upcoming cash flows of firms, should adjust to the economic perspectives. Thus, flow
oriented models results in a positive relationship between stock prices and exchanges rates with
direction of causation running from exchange rates to stock prices.
Another classification of Portfolio Balance Method and Monetary Models is Stock
Oriented Model. A portfolio balance model shows a negative relationship between stock prices
and exchange rates and come to the conclusion that stock prices have an impact on exchange
rates. Such models presume an internationally diversified portfolios and the role of exchange
rates to balance the demand for and the supply of domestic as well as foreign assets.
Portfolio Balance models provides an alternative for the association between stock prices
and dollar rates, focusing on the role of capital account transactions. Developing markets can
attract many foreign investors to invest heavy capital flows, ultimately increasing demand for its
currency. But in contrary, if stock prices are decreasing investors would try to sell out their
Stock prices and exchange rates
stocks to avoid losses and would convert their currency into foreign currency in order to move at
foreign location. In such a case, local currency would decline. As a result, rising (declining)
stock prices would lead to depreciation in exchange rates. Furthermore, foreign investment in
local equities increases due to foreign diversifications that investors would gain.
For numerous reasons it is important to observe the association between stock prices and
dollar rates. Firstly, in order to predict the path of the exchange rate we need to find out the links
between the two markets. This can help the multinational corporations to manage their exposure
to foreign contracts and the exchange rate they face. Secondly, currency is more often being
included as an asset in investment funds’ portfolio. Knowledge about the link between
currency rates and other assets in a portfolio is vital for the performance of the fund. The
mean- variance approach to portfolio analysis suggests that the expected return depends on the
variance of the portfolio. Therefore, an accurate estimate of the variability of a given portfolio is
needed. This, in turn, requires estimates of the correlation between stock prices and
exchange rates. Third, the understanding of the stock price- exchange rate relationship may
prove helpful to foresee a crisis.
We will be employing the famous Granger causality test. (Granger, 1969) was developed
as a more efficient approach in comparison to the basic correlation tool, which does not imply
causation between Correlated variables in any significant sense of the word. The Granger test
addresses the issue of whether the current value of a variable y – yt - can be explained by past
values of the same variable – yt-k – and then whether adding lagged values of another variable x
– xtk– improves the explanation of yt. As such, the variable y is said to be Granger-caused by x if
the coefficients on the lagged values of x are discovered statistically significant.
Stock prices and exchange rates
Jorion (1990) found a weak link between stock returns of US multinational companies
and the effective US dollar exchange rate for the period 1971-1987. Roll (1992) finds a positive
relationship between market indices and exchange rates. Smith (1992) uses Portfolio Balance
Model to examine the determinants of exchange rates. The results show that equity values have a
significant influence on exchange rates but the stock of money and bond has little impact on
exchange rates.
Solnik (1987) observe a weak but positive relationship between the two variables. Soenen
and Aggarwal (1989) re-access the Solnik model using 1980 – 1987 data for the same eight
industrial countries. They report a positive correlation between stock return and exchange rates
for three countries and negative correlation for five. Soenen and Hennigar (1988) conclude that
the value of the U.S. dollar is negatively correlated, that is depreciation of the U.S. dollar
increases the U.S. stock price indexes. Giovannini and Jorion (1987) discovered empirical
regularities between exchange rates and stock markets in USA.
Early empirical studies, however, omit to recognize the fact that most financial variables
are non-stationary. To account for this problem, Bahmani-Oskooee and Sohrabian (1992) used
co-integration to investigate the relationship between monthly data on S&P 500 index and US
dollar effective exchange rates for the period 1973-1988. In early studies, many researchers
have discussed this issue in various timeframes. Franck and Young (1972) were among the first
authors to analyze the association between stock prices and dollar rates. Using correlation
regression analysis, they reported no significant interactions. Aggarwal (1981) finds that the US
stock prices and the trade-weighted dollar value are positively correlated.
Stock prices and exchange rates
In recent times, researchers have pointed out that such a system can be incomplete if you
omit some important variables. In such a situation the long run relationship of variables and
causality structure are invalid. Lutkepohl (1982) and more recently Caporale and Pittis (1997)
explains that the omitted variables in a system can be the only determining factor for sensitivity
of causality inferences between the variables of incomplete system.
Early empirical studies have not considered the fact that most financial variables are non-
stationary. To account for this problem, Bahmani-Oskooee and Sohrabian (1992) used co-
integration to investigate the relationship between monthly data on S&P 500 index and US dollar
effective exchange rates for the period 1973-1988.
Officer (1973) explained that during the period of Great Depression, aggregate stock
volatility, volatility of money growth and industrial production increased. But stock volatility
remained at same levels before and after Depression period. Black (1976) and Christie (1982)
discovered that in contrary to Officer (1973) financial leverage can partially explain the stock
market volatility. French et al. (1987) and Schwert (1989) found Market volatility as variance of
monthly returns of market index. It changes over time. Any uncertain situation in economy
would cause a proportionate change in stock return volatility. But French et al. found a negative
relationship between return and volatility.
Schwert (1989) and Hamilton and Lin (1996) found out that stock market volatility is
increases during the recession and Glosten et al. (1993) find out interest rates are to be an
important factor in explaining stock market volatility. Mao and Kao (1990) exporting firms’
stock values were comparatively more sensitive to changes in foreign exchange rates. Their
Stock prices and exchange rates
study also found out another topical issue of the relationship between stock prices at the macro
and micro levels. The existing available evidence indicates a fragile association involving them
at a micro level. According to the macro level, Ma & Kao (1990) originate that a currency
appreciation pessimistically affect the domestic stock market for an export-dominant country and
optimistically for an import-dominant country.
Yu (1997) investigated Hong Kong market, Tokyo market, and Singapore market for the
period 1983-1994. Using daily data, he detected bi-directional relationship in Tokyo and a
causality running from exchange rates to stock prices for Singapore. Abdalla and Murinde (1997)
applied co-integration approach to examine stock prices-exchange rates relationship in four
Asian countries using data from 1985 to 1994. Their results reject an occurrence of causality in
Pakistan and Korea but support its existence in India and Philippines. In India the relationship
occurs from exchange rates to stock prices, the opposite is found for Philippines.
Libly Rittenberg (1993) employed the Granger causality tests to examine the association
linking dollar rate changes and price level changes in Turkey. Since causality tests are sensitive
to lag selection, therefore he employed three different specific methods for optimal lag selection
[i.e., an arbitrarily selected, Hsiao method (1979), and the SMAR or subset model auto
regression method of Kunst and Marin (1989)]. In all cases, he found that causality runs from
price level change to exchange rate changes but there is no feedback causality from exchange
rate to price level changes.
Eli Bartov and Gordon M. Bodnor (1994) concluded that contemporaneous changes in the
dollar have problems in explaining abnormal stock returns properly. According to their findings
Stock prices and exchange rates
a lagged change in the dollar is negatively associated with abnormal stock returns. The
regression results showed that a lagged change in the dollar has explanatory power with respect
to errors in analyst’s forecasts of quarterly earnings.
Some of the researchers have focused on some specific industries rather than on whole
economy. Chamberlain et al. (1997) focusing on the banking industry reported that US banking
stock returns were responsive to exchange rates changes. But in contrary, Japanese banking stock
returns were not sensitive to changes in exchange rates. Ajayi et al. (1998) provided evidence to
indicate unidirectional causality from the stock to the foreign exchange markets for the advanced
economies (USA, Korea) and no consistent causal relations in the emerging markets (Malaysia).
Hamao et al. (1990) investigate the price and volatility spill over in three major stock
markets (New York, Tokyo, and London). Koutmos and Booth (1995) find asymmetric volatility
spillovers across the New York, Tokyo, and London stock markets. So (2001) studies the
dynamic spill over effect between interest rate and exchange value of US dollar.
Khoo (1994) estimated the mining companies’ economic exposure by using exchange
rates, interest rates and price of oil. He discovered that the sensitivity of stock returns to
exchange rate movement and proportion of stock are minor. Domely and Sheehy (1996) found a
contemporary relation involving the dollar rate and the market value of large exporters.
Several researchers consider the involvement of other macroeconomic factors they might
include in the exposure regression. Different macroeconomics factors including interest rates,
money reserve, inflation, different monetary policies, etc., have been applied to the exchange rate
exposure model by various researchers. Ibrahim (2000) has extended the exiting studies on the
Stock prices and exchange rates
stock prices – dollar rates causal association by investigating the concern for Malaysia. He used
three exchange rates, namely, nominal effective exchange rate, real effective exchange rate and
bilateral exchange rate. Using monthly data from January 1979 to June 1996, applying co
integration and Granger Causality tests he found that, in the bivariate models, no extended
relationship involving the stock market index and a few of the exchange rates.
Vygodina (2006) examines the exchange rates and stock prices for large and small stocks
for the period 1987-2005 in the USA and used Granger causality methodology. The study results
that there is Granger causality from large stocks to the exchange rate but there is no causality for
small stocks. Stock prices and exchange rates are affected by the same macroeconomic variables,
whereas the changes in monetary policy have an important effect on the nature of this
relationship. In other words, the nature of the correlation involving stock prices and dollar rate is
variable with time.
In economic analysis it is stated that firm value is related to exchange rate movements.
Shapiro (1975) stated that increase in value of home currency firm with depreciation of local
currency. Adler and Dumas (1984) stated that even firms operating local domestic markets,
might get effected by exchange rates movements. Luetherman (1991) found from testing his
hypothesis, that if the local currency depreciates it will give rise to competitiveness of local
manufacturers in comparison to foreign competitors. But in contrary, no firm can get benefit
when local currency depreciates, although significant decline is witnessed in market share of
industry with the depreciation of local currency.
Stock prices and exchange rates
Bodner and Gentry (1993) considered the three countries namely Canada, Japan, and USA.
According to the research some industries in these countries have significant exposure. Choi and
Prasad (1995) developed a model examining the exchange rates sensitivity of 409 US
multinationals. They came up with a conclusion that firm’s value is affected by change in
exchange rates. Around 60% of firms had significant exchange rate exposure.
Domely and Sheehy (1996) found contemporary relation involving the foreign exchange
rate and market value of exporters. Miller and Reuer (1998) conducted a study on differences in
strategy and industry structure of firm’s economic exposure in accordance to foreign exchange
rates fluctuations. Around 13 to 17% of US manufacturing firms affected by foreign exchange
movements. Foreign direct investment reduces economic exposure to foreign exchange rate
fluctuations. Glaum, Barunner and Himmet (2000) examined the German company’s exposure to
change in US dollar exchange rates. They found that German firms are significantly exposed to
changes in dollar rate.
Pan et al. (2000) noted that exchange rates had significant effects on stock prices in seven
Asian countries during 1988 – 1998. Similarly to Granger et al. (2000), they reported much
stronger interaction during and after the financial crisis of 1997. Wu (2000) explores the
existence of a balance correlation between stock prices and dollar rates in Singapore asset market
and it’s sensitive to different currencies. He concludes that Granger causality runs merely one
way from dollar rates to stock prices; the co integration investigation suggests that Indonesia
Rupiah has an optimistic long run effect on stock prices.
Stock prices and exchange rates
Erbaykal and Okuyan (2007) examined 13 developing countries to figure out the exchange
rates-stock price relations using different time period for each country. They came up with a
conclusion that indicated causality relations for eight countries. While there is a one directional
causality from stock price to dollar rates in the five of them, bidirectional causality exist for
remaining three economies. They also found no causality for these financial variables in Turkey,
but these findings are not found consistent with the results. This is due to the different time slots
used in the research. On the other hand, Sevuktekin and Nargelecekenler (2007) found positive
and bidirectional causality between these two financial variables in Turkey using monthly data
from 1986 to 2006.
Morley and Pentecost (2000) examine the nature of the correlation linking stock prices
and exchange rates for Canada, France, Germany, Italy, Japan, UK, and USA. They find that the
lack of correlation between the level of stock prices index and the level of the exchange rates is
due to the fact that dollar rates and stock prices do not display general trends, but rather exhibit
common cycles. Thus the statistical relationship is a short run rather than long run or trend
relationship.
Amare and Mohsin (2000) examine the long-run association between stock prices and
exchange rates for nine Asian countries (Japan, Hong Kong, Taiwan, Singapore, Thailand,
Malaysia, Korea, Indonesia, and Philippines). They use monthly data from January 1980 to June
1998 and employed co integration technique. The long-run correlation linking stock prices and
dollar rates was found only for Singapore and Philippines. They attributed this lack of co
integration between the said variables to the bias created by the ―omission of important
Stock prices and exchange rates
variables.‖ When interest rate variable was included in their co integrating equation they found
co integration between stock prices, exchange rates and interest rate for six of the nine countries.
Ramasamy and Yeung (2001) focused their research on two markets in nine East Asian
economies and they found that causality can differ according to the period of study. For the
period of the entire four years of the crisis (1997 – 2000) all countries, apart from Hong Kong,
showed that stock prices cause movements in the exchange rates.
Fama (1981) states that stock prices are reflected by the variables like, inflation, exchange
rate, interest rate, and industrial production.Maysami and Koh (2000) and Choi et.al (1992)
examine the impacts of the interest rate and exchange rate on the stock returns and showed that
the exchange rate and interest rate are the determinants in the stock prices. Likewise, Ehrhard
(1991) documents a powerful result of the interest rates on stock returns. Similar results are
achieved in various studies using different countries such as Campbell (1987), Shanken (1990),
Apergis andEleftheriou (2002).
Lee and Nieh (2001) examine both short-run co movements and long-run balance
interaction involving stock prices and exchange rates for each G-7 country: Canada, France,
Germany, Italy, Japan, the United Kingdom (U.K.) and the U.S. They found no long run
equilibrium relationship exists between the two variables. However, in the short-run causality
runs from exchange rates to stock prices in Germany, Canada, and the U.K, and runs from the
later to the former in Italy and Japan.
Griffin and Stulz (2001) also examined particular industries rather than on whole
economy. They noted that changes of weekly exchange rates had negligible impacts on industry
Stock prices and exchange rates
stock indices in developed countries. Nagayasu (2001) analysis empirically the recent Asian
financial crisis using the time series data of exchange rates and stock indices for Philippines and
Thailand which were the first two countries confronted by massive movements in financial asset
prices. He found unidirectional causality runs from the financial sector index to the exchange
rate, contagion effects running from Thailand to the Philippines.
Rim and Mohidin (2002) examined relations between industry indices and exchange rates
using monthly data before and during the Asian financial crisis. Their findings show that
industry indices had long run positive effects on exchange rates, and exchange rate also had long
– run positive effects on most indices. Short-run effects proved to be generally negative in both
directions. Hatemi and Irandoust (2002) also find that Granger causality is unidirectional running
from stock prices to exchange rates in Sweden.
Bhattacharya and Mukherjee (2003) investigated the nature of the causal relationship
between stock prices and macro economic aggregates for in India and found no significant
linkage. Muhammad and Rasheed (2003) used monthly data on four South Asian countries for
the period (1994 to 2000). They came up with no correlation involving stock prices and
exchange rates in Pakistan and India neither in short run or in long run. Whereas, in Bangladesh
and Srilanka markets are bi directionally linked.
Phylaktis and Ravazzolo (2005) considered the long run and short run correlation between
stock prices and dollar rates and the channels in the course of which exogenous shocks impact
these markets. Findings using co-integration methodology and multivariate Granger causality
Stock prices and exchange rates
tests on a sample of Pacific Basin countries propose that stock and overseas exchange markets
are positively correlated and that the US stock market acts as a medium for these associations.
Hatemi and Roca (2005) examines the link between exchange rates and stock prices before
and during the 1997 Asian crisis, for Indonesia, Malaysia, Philippines, and Thailand. They find
that with the exception of the Philippines, during the period before the Asian crisis, there was a
significant causal link between dollar rates and stock prices in each of the four Asian countries.
Causality ran from the former to the latter in the case of Indonesia and Thailand, while direction
of causality is reversed in the case of Malaysia. During the Asian crisis period that took place,
the relationship between those two variables ceased across the all countries.
Doong, Yang, and Wang (2005) examine he dynamic relationship and pricing of stock
and exchange rate, using Weekly data for Indonesia, Korea, Malaysia, Philippines, Thailand and
Taiwan. They find that stock prices and exchange rates are not co integrated, using Granger
causality test, bidirectional causality can be detected in all countries except Thailand.
Mansor (2000) examined the Malaysian markets and found no long-run correlation
involving stock prices and dollar rates; although in bivariate cases he found a short-run causal
correlation from stock prices to dollar rates. He also found a bi-directional causality in some
multivariate models.
Chong and Koh’s (2003) showed that stock prices, economic activities, real interest rates
and real money balances in Malaysia was linked in the long run both in the pre- and post capital
control sub periods. Islam and Watanapalachaikul (2003) showed a strong, significant long-run
relationship between stock prices and macroeconomic factors (interest rate, bonds price, foreign
Stock prices and exchange rates
exchange rate, price-earning ratio, market capitalization, and consumer price index) during 1992-
2001 in Thailand.
Dong (2006) argued that the market prices are not only important in determining the
conditional mean of exchange rate changes, but also directly affect the conditional volatility of
exchange rate changes. He also argued that the exchange rate exposure to macro innovations is
amplified by the market prices of risk which varies over time. The existing structural models of
exchange rates have a static and linear relationship between macro variables and exchange rates.
If the time-varying from macro shocks to exchange rate movements is correct, a static and linear
relationship, therefore, will not be specified. Dong (2006), however, using the recursive
identification of monetary policy shocks, which is said to be inappropriate, couldn’t get rid of the
delayed overshooting puzzle or the forward premium puzzle.
Hau and Rey (2006) developed an equilibrium model in which exchange rates, stock prices,
and capital flows are jointly determined. They show that net equity flows into the foreign market
are positively correlated with a foreign currency appreciation. According to Adler and Dumas
(1984) those firms whose entire operations are domestic are also has a possibility of being
effected by exchange rates, especially if their input and output prices are influenced by currency
movements.
When there is a falling home currency, it promotes competitiveness of home country firms
as it allows them to undercut the prices charged for goods manufactured abroad (Luehrman,
1991). Simple partial equilibrium models like Shapiro predict an increase in the value of the
home country firm in answer to a decrease in the value of the home currency. Benita and
Stock prices and exchange rates
Lauterbach (2004) in their research showed that exchange rate volatility have real economic
costs. It affects a country’s price stability, firm profitability and a country’s stability.
Developments that are done in the foreign exchange market have cost implications for the
households, firms and the state. There are three events, namely the Asian Currency Crises, the
advent of floating exchange rate in the early 1970s and financial market reforms in the early
1990s have over all prompted financial economist into determining the link between these two
markets (Mishra, 2004).
Adjasi and Biekpe (2005) studied the relationship between stock market returns and
exchange rates effects in 7 African countries. Co integration tests explained that in long run
decrease in exchange rates results in increase in stock market prices in some of the countries,
while in the short run decrease in exchange rates decreases stock market returns. Mishra (2004)
showed that stock return, exchange rate return, interest rates and money demand are interrelated
although no consistent relationship exists. Moreover, there is no Granger Causality between
stock returns and exchange rates are found.
Engle and Rangel (2005) also study the link between number of macro economic variables
and stock market volatility. This study concludes that volatility stock return forecast can be
easily being incorporated with macroeconomic variables forecast.
The effect of a stock price increase on expenditure is explained by Mishkin (2001) as
follows. First, it leads to increased investment by firms. The value of a firm’s equity increases as
its stock price rises while the prices of new equipment remain unchanged in the short run. As a
result, investment is now relatively cheaper and companies will tend to invest more.
Stock prices and exchange rates
Among some of the major researchers that are carried out on emerging markets namely;
Mishra (2004), Chortareas et al. (2000), Koutmoa et al. (1993). Early researchers like Smith
(1992), Franck and Young (1972), Solnik (1987), Granger et al. (2000), Abdalla and Murinde
(1997), and Apte (2001) have found a positive relationship between stock prices and exchange
rates. Where as researchers like, Soenen and Henniger (1998), Mao and Kao (1990), Ajayi and
Mougoue (1996), have reported negative relationship between the two variables. On the other
hand, Bartov and Bodnar (1994), Franck and Young (1972) have found weak or no relationship
between stock prices and exchange rates.
Frenkel (1976), Bilson (1978), Dornbusch (1976), Frankal (1979), Dornbusch and Fisher
(1980), Hooper and Morton (1982), Branson,et al.’s (1977) portfolio-balance model also
suggests that asset of portfolios has been described by the ―Stock Oriented Model‖ exchange rate
movement. Empirical studies of Meese and Rogoff (1983), Wolff (1988), Bailie and Selover
(1987), and Ghartey (1998) found some relationship between exchange rates and macro-
fundamentals, whereas another empirical studies shows the evidence for the relationship between
stock prices and macro-fundamentals which are found in Bailey (1990), Sadeghi (1992), and
Kwon and Shin (1999).
Libly Rittenberg (1993) employed the Granger causality tests to examine the relationship
involving exchange rate changes and price level variations in Turkey. Since causality tests are
sensitive to lag selection, therefore he employed three different specific methods for optimal lag
selection [i.e., an arbitrarily selected, Hsiao method (1979), and the SMAR or subset model auto
regression method of Kunst and Marin (1989)]. In all cases, he found that causality runs from
Stock prices and exchange rates
price level change to exchange rate changes but there is no feedback causality from exchange
rate to price level changes.
Eli Bartov and Gordon M. Bodnor (1994) concluded that contemporaneous changes in the
dollar have little power in explaining abnormal stock returns. They also, found a lagged change
in the dollar is negatively associated with abnormal stock returns. The regression results showed
that a lagged change in the dollar has explanatory power with respect to errors in analyst’s
forecasts of quarterly earnings.
Adrangi and Ghazanfari (1996) test for causality relationship between the dollar exchange
rate and the stock return in Germany and US. They found that stock returns cause the changes in
the exchange rate of the dollar.
Moradoglu, Taskin and Bigen (2001) examines the relation between stocks
returns and some macroeconomic variables and concluded that there is a one way causal
relationship from exchange rates to stock returns in Nigeria, Mexico, Korea, Greece, Colombia
and Brazil where as a both way causal relationship between the variables in case of Mexico.
Yu (1997) investigated Hong Kong market, Tokyo market, and Singapore market for the
period 1983-1994. Using daily data, he detected bi-directional relationship in Tokyo and a
causality running from exchange rates to stock prices for Singapore. Abdalla and Murinde (1997)
applied co-integration approach to examine stock prices-exchange rates relationship in four
Asian countries using data from 1985 to 1994. Their results reject an occurrence of causality in
Pakistan and Korea but support its existence in India and Philippines. In India the relationship
occurs from exchange rates to stock prices, the opposite is found for Philippines.
Stock prices and exchange rates
Stock prices are expected to react ambiguously to exchange rates. The change in currency
effects on the balance sheets of multinational companies. Depreciation could either raise or lower
the value of a company, depending on the imports and exports of that respective company. When
the stock market index is considered, the net effect cannot be predicted.
In contrary to this concept, another way of looking at the picture is that the currency will
depreciate if the stock market declines. In other words, in markets with high capital mobility, it is
the capital flows, that determine the daily demand for currency. A decline in stock prices makes
foreign investors sell the financial assets they hold in the respective currency. This leads to
currency depreciation.
The study done on the correlation linking the stock prices and dollar rate on USA show a
weak relationship that is the exchange rates are significantly related to either the firm or portfolio
stock. (Jorion1990; Bahmani-Oskooee and Sohrabian, 1992; Amihud, 1993; Bartor and Badnar,
1994). Tests were also run on Japan and Canada by Bondnar and Gentry (1993). The result that
has been gathered by Abdalla and Murinde (1997) says that it is in the favor of the traditional
approach that is the exchange rates supports the stock prices. Their study consisted of the
countries India, South Korea, Pakistan and Philippines.
The research done by Ding, Harris, Lau, and McInish (1999) examined the links between
Malaysia and Singapore trading for a Malaysian firm and another study done by Sabherwal
(2003) examined the US and Canada by a sample of Canadian firms. Kim, Szakmary, and
Mathur (2000) had made use of the daily data on 21 Japanese, 21 British, 5 Dutch, 5 Swedish,
and 4 Australian firms. From this data they estimated the VAR models of the contact of the
Stock prices and exchange rates
underlying shares, the New York afternoon exchange rate, and the U.S. market index on ADR
prices. From their research they found out that the underlying shares appeared to be most
important. But then there is a major independent role for the exchange rate and the U.S. market
index in pricing ADRs.
Kato, Linn, and Schallheim (1990) carried out a study in order to examine 7 U.K., 8
Japanese, and 8 Australian stocks which were traded in New York. From their study they found
the evidence that the price in the home country leads the price in New York. Lau and Diltz
(1994) conducted a study of the 7 Japanese stocks which were traded in New York and found out
a bi-directional causality but with a stronger impact of NYSE returns on Tokyo returns rather
than the reverse of this. Lieberman, Ben-Zion, and Hauser (1999) had examined 6 Israeli stocks
that are listed in New York. From their study they found that the price discovery appeared to
occur in Israel for five of the firms with Teva having a dominant role for the U.S. Wang, Rui,
Firth (2002) had carried out an examination on a group of Hong Kong stocks that were traded in
London. They concluded from their examination that they found bi-directional causality for local
market returns between the two markets. They also found out that in their examination. Hong
Kong was the dominant market.
Karolyi and Stulz (1996) conducted an examination on the determinants of correlations
amongst the open to close daily returns on 8 Japanese stocks that were traded in the United
States and had a matched sample of U.S. stocks. Their research found out that shocks to the
currency futures returns had no influence that could be measured on the Japanese and U.S. stock
price correlations. Bailey, Chan, and Chung (2000) had carried out a research and studied the
impact of the Mexican peso/U.S. dollar exchange rate on prices of Mexican firms that were
Stock prices and exchange rates
being traded on the NYSE. They took a certain sample of the stock prices and exchange rates at
30-minute intervals. They had concluded their findings that that peso depreciation was associated
with decreases in the stock 5 prices.
The Stock market and Exchange rates relations in developed and developing economies
have been discussed and researched to bring a broadly- based insight into the issue. However,
very few researchers have talked about China’s market in this aspect. Chien-Chung Nieth &
Cheng-Few Lee (2001) considered the G-7 countries, and discovered the dynamic relationship
between stock prices and exchange rates. Both the Engle-Granger (EG) two steps and the
Johansen maximum likelihood co integration tests are used. Their empirical work rejects most of
the previous studies that suggest a significant relationship between stock returns and exchange
rates. It supports the findings of Bahmani-Oskooee and Sohrabian’s (1992) that there is no
possible existence of long run equilibrium relationship between the two variables. Moreover, by
applying Granger Causality test, it results in short run unidirectional causality relationships
between stock returns and exchange rate.
Tsoukalas (2003) examines the relationship between stock prices and macroeconomic
factors in Cyprus. Cypriot economy mainly depends on services (import sector); therefore this
study reveals strong relationship between stock prices and exchange rates.
Kurihara (2006) selected to examine the relationship between macroeconomic variables
and daily stock prices in Japan, he chose the period from (March 2001-September 2005). He
takes Japanese stock prices, U.S. stock prices, exchange rate (yen/U.S. dollar), the Japanese
interest rate etc. As a result, domestic interest rate does not influence Japanese stock prices.
However, the exchange rate and U.S. stock prices affect Japanese stock prices. Whereas,
Stock prices and exchange rates
Japanese stock prices has been influenced by the implementation of quantitative easy policy in
2001.
Alexandra and Lava (2007) used Granger causality and bivariate cointegration tests on
daily and monthly exchange rates and stock prices data collected over the 1999 to 2007 period.
They used three types of exchange rates; the nominal effective exchange rates of the Romanian
leu, the bilateral nominal exchange rates of the leu against the US dollar and the euro, and the
real effective exchange rates of the leu. They resulted in no cointegration involving the dollar
exchange rates and the stock prices, however, suggests the presence of cointegration between
stock market indices used and the exchange rates - nominal bilateral, nominal effective or real
effective rates. The authors finally concluded that the lack of co integration indicated by the
Engle and Granger procedure may be due to the lower power of the test, as recognized in the
literature. Granger causality tests, on the other hand revealed unilateral causality relations from
the stock prices to exchange rates for the entire period and the second sub-period, and one
bilateral causality relation linking the stock prices and the mutual dollar exchange rate against
the US dollar and the euro for the first sub-period.
In order to figure out the nature of relationship, we are here to debate on the causal
relations between exchange rates and stock prices in Malaysia. To this end, it employs a new
causality methodology which allows causal inferences to be conducted in a system including
time series processes that may be integrated as well as co integrated. Toda and Yamamoto (1995)
applied a simplistic approach for assessing causal relations regardless of order of integration
and/or the cointegration rank in a vector autoregressive (VAR) system. It considers both
bivariate and multivariate frameworks. It should be emphasized that the use of incomplete
Stock prices and exchange rates
system which fails to account for other important variables may end up with spurious result. The
lack of causal relationship in the past studies could be because of the omission of important
variables, which serves as a conduit through which the exchange rates and stock prices are
linked.
From an emerging markets perspectives analysis on the correlation involving stock prices
and dollar exchange rates turned out to be interesting debate. In Romania, Horobet & Ilie (2007)
discussed about the fluctuations in exchange rates. They focused that such fluctuations can
significantly have an effect on firm value, as they influence the terms of competition, the input
and output prices, and the value of firm’s assets and liabilities denominated in foreign currencies.
Although firms with foreign operations, from exporting to international production, are more
affected as compared to proper domestic firms, in the real sense no company can be considered
as fully isolated from the effects of exchange rates changes. Consequently, all firms’ prices as a
result of influence may react sooner or later to changes in the exchange rates. When there is a
change in exchange rates, a company might face: Firstly, transaction exposure, which arises
when the firm is contractually bounded to make or receive a payment at a future date
denominated in a foreign currency; Secondly, translation exposure, arising from the need of
consolidating the financial reports of a multinational company from affiliates’ reports
denominated in various currencies; and Thirdly, economic exposure, is witnessed as the change
in the firm’s present value as result of changes in the significance of the firm’s projected future
cash flows and cost of capital, induced by unexpected exchange rate changes.
Horobet & Ilie (2007) examined the interactions between the stock prices and the dollar
exchange rates for the Romanian market during 1999-2007, focusing on developments dynamics
Stock prices and exchange rates
on the foreign exchange markets after the end of 2004. In this research the authors have used the
rates calculated according to the European Central Bank methodology. The NEER is calculated
as a weighted geometric average of the bilateral exchange rates against the currencies of trade
partner countries and reported as an index; a rise in the index indicates a strengthening of the
currency. The REER corresponds to the NEER deflated by nominal unit labor costs for the total
economy and consumer prices (CPI); a rise in the index signifies a loss of competitiveness.
As per the macroeconomic perspective, Horobet & Ilie (2007) explains that due to the
increase in real money and the value of domestic currency, stock prices reflecting the real
economic activity may affect exchange rates. The correlation linking dollar exchange rates and
stock prices at the macroeconomic level may be sensitive to the exchange rate regime in force.
The currency appreciation under a floating exchange rate reduces the competitiveness of
countries’ exports and, is expected to have a negative outcome on the local stock market. On the
contrary, country relying on imports, will appreciate lowering input costs of local currency,
creating a positive impact on the stock market.
Hsing (2004) studies the Brazilian monetary markets, and because of economic
fluctuations it affects output. The study uses consideration of stock prices in a Mundell-Fleming
model. It also uses monthly data, providing short-run insight, but captures more macroeconomic
relationships than daily data. The author builds upon the open economy Mundell-Fleming
framework where net exports depend on the real exchange rate. The model is slightly extended
by including variables which research claims as relevant—oil prices, domestic and external debt.
Stock prices are also included and they are expected to affect output through wealth and
investment.
Stock prices and exchange rates
Hsing (2004) adopts a structural VAR model originally proposed by Sims (1986), using this
method allows for the simultaneous determination of several endogenous variables. Among the
seven endogenous variables are output (Y), real interest rate (RR), exchange rate (EX) and the
stock market index (ST), which are also the four endogenous variables in my model. The model
consists of seven equations where each endogenous variable is expressed as a function of its own
lag, the lags of the other six endogenous variables, the two exogenous variables (which are the
same for all seven equations), and a white noise term.
The conclusions about the correlation linking stock prices and dollar exchange rates are
drawn quite indirectly. To determine the sign of the relationship, Hsing (2004) introduces an
artificial shock to each variable. The author finds a negative relationship between stock prices
and output in the initial three to four months, which turns into an unambiguous positive
relationship after the fourth month. Hence, the short-run effect is not consistent with any
expectations.
Çifter and Ozun (2007) analyzed the impact of interest rates by using wavelet study with
Granger Causality test. In this study we are taking daily closing values of the Istanbul Stock
Exchange 100 index and compounded interest rates are used. In the study it is verified that
preliminary with 9 days time-scale consequence interest rate is granger cause of ISE 100 index
and effects of interest rates on stock return increases with privileged time scales. In this point of
view bond market has considerable long-term effect on stock market.
The sector index returns is used in many studies to measure impact of exchange rates and
interest rates. For this purpose, Malik and Hassan (2004) studies how do unanticipated shocks
determine the persistence of volatility overtime, altering the volatility patterns of financial
Stock prices and exchange rates
assets? They identify time periods of rapid changes in instability by using the iterated cumulated
sums of squares (ICSS) algorithm. Examining five major sectors they discover that accounting
for instability shifts in the standard GARCH model considerably reduces the projected volatility
persistence.
Jayasinghe and Tsui (2007) examine exchange rate exposure of sector returns and
volatilities. In the paper a bivariate GJR-GARCH model is used to examine aspects of exchange
rate exposure of segment indexes in Japanese industries. Based on a trial data of fourteen sectors,
considerable verification is found exposed returns and its asymmetric conditional instability of
exchange rate exposure. In addition, returns in many sectors are interrelated with those of
exchange rate changes.
Usually most of the research is carried out to find out the nature of correlation involving
stock prices and dollar exchange rates in the developed side of the world. But no specific
research has been carried out about the UAE financial markets. There can be several ways to
describe the factors affecting stock prices. One of the Arabic researcher namely, Al-Qenae et at.
(2002) made an important contribution by investigating the effect of earning and other
macroeconomic variables on the stock prices of Kuwait Stock Exchange during the period 1981-
1997. The macroeconomic variables examined are gross national product (GNP), interest rate,
and inflation.
The study found a significant higher sensitivity of the estimated earning response
coefficient (ERC) with the leading period returns. The researchers have witnessed that inflation
rate and interest rate have statistically significant but negative coefficients in most cases, where
as GNP has positive effect but it is only significant in a certain (high) return measure interval.
Stock prices and exchange rates
This study also indicates that investors from Karachi Stock exchange (KSE) are able to anticipate
earnings and suggests that the KSE market exhibits some features of semi-strong efficiency (i.e.,
a scenario in which stock prices incorporate all publicly available information).
Mukherjee and Naka (1995) investigate the relation between Tokyo stock prices and six
macroeconomic variables using a vector error correction model (VECM). Their study covered
240 monthly observations for each variable in the period from January
1971 to December 1990. The results of the study show that the relationship between
Tokyo stock prices, the exchange rate, money supply, and industrial production is positive,
whereas the relationship between Tokyo stock prices and inflation and interest
rates are mixed.
Chaudhuri and Smiles (2004) considered Australian Stock Market in the period ranging
from 1960 to 1998, in order to find out the correlation between stock prices and dollar exchange
rates. Main economic variables sin the research includes real GDP, real oil prices, real money,
and real private consumption. The finding of the research shows long run relationships between
stock prices and real macroeconomic activity. Moreover, Australian stock markets returns are
affected by the American and New Zealand market
significantly.
Hammoudeh and Aleisa (2004) have studied the relationships among Gulf
Cooperation Council (GCC) stock markets and NYMEX oil future prices for a period from 1994
to 2001. The export of Oil is a large determinates of foreign exchange earnings and
Stock prices and exchange rates
governments’ budget revenues and expenditure. Moreover, it is the primary determinants of
aggregate demand which influences corporate output and domestic price level, which eventually
impact corporate earning and stock prices. The result of the study shows that UAE stock market
is another important and higher link next to Bahrain after the Saudi Arabia market.
Most of the studies carried out in this part of the under developed or developing world
results in strong stock prices-earning relations exist while no robust long-term stock prices-
dividend relation is found. It has been reported that a negative relation between prices and long-
term interest rates exist, whereas positive relations exist with the short-term interest rates. GDP,
GNP, and industrial production are those variables which are more likely to have positive
relationship with stock prices. In the same aspect money supply appears to have a positive
relation as well. Stock prices appear to move inversely with inflation through a negative relation.
However, the relation between oil prices and stock prices is not significant. Overall, stock prices
are affected by economic and financial fundamentals and macroeconomic variables in most
cases.
Omran (2003) studies the impact of key feature in investigating the impact of real interest
rates as a key feature in the performance of the Egyptian stock market, both in conditions of
market activity and liquidity. Significant long-run and short-run relationship is indicated between
the variables through the co integration analysis through error
correction mechanisms (ECM) indicated implying that real interest rates had an
impact upon stock market performance.
Stock prices and exchange rates
Vuyyuri (2005) focused on financial and the actual sectors of the Indian financial system
using monthly observations from 1992 through December 2002, in order to investigate the co
integrating correlation and the causality between the financial. The financial variables used were
interest rates, inflation rate, dollar exchange rate, stock return, and actual sector was proxied by
industrial productivity.
Johansen (1988) found long run balance correlation between the financial sector and the
real sector by applying multivariate co integration test. The Granger test indicated unidirectional
Granger causality involving the financial sector and real sector
of the economy.
Maghyereh (2002) focused Jordanian stock markets investigated the long-run relationship
between the Jordanian stock prices and selected macroeconomic variables.
Johansen’s (1988) co integration analysis and monthly time series data for the period from
January 1987 to December 2000. The study showed that macroeconomic variables were reflected
in stock prices in the Jordanian capital market.
Gunasekarage, Pisedtasalasai and Power (2004) examined the influence of macroeconomic
variables on stock market equity values in Sri Lanka, using the Colombo All Share price index to
represent the stock market and (1) the money supply, (2) the treasury bill rate (as a measure of
interest rates), (3) the consumer price index (as a measure of inflation), and (4) the exchange rate
as macroeconomic variables.
Ta and Teo (1985) had studied high correlation among six Singapore sector indices in the
period 1975 to 1984 and the overall SES market return (e.g. All-S Equities Industrial and
Stock prices and exchange rates
Commercial Index, SES All-Equities Finance Index, SES All-S Equities Property Index, SES
All-S Hotel Index, SES All-S Plantation Index and SES All-S Mining Index).Using daily data in
examining the relationships, they had concluded that sector returns were highly correlated to
each other, although such correlations did not remain stable over time.
Sun and Brannman (1994) found a single long-run relationship among the SES All-S
Equities Industrial & Commercial Index, Finance Index, Hotel Index, and Property Index from
1975 to 1992. With reference to study of Johansen’s (1988) they have used the employment of
VECM to examine the long-run equilibrium relationship between selected macroeconomic
variables and stock market sector indices represented on the Singapore Exchange (SGX) the
Finance Index, the Property Index, and the Hotel Index.
Friedman and Schwartz (1963) has hypothesized that the growth rate of money supply
would affect the aggregate economy and hence the expected stock returns. In this way they had
explained the relationship between money supply and stock returns.
Among the other developing economies, a research is carried out in Pakistan to find that
there are four co integrating vectors in money demand, interest rate, economic activity, inflation,
stock prices and exchange rate. in case of developing economy like Pakistan researchers have
ample effort made in estimating money demand functions . Akhtar (1974), Abe, et al. (1975),
Burney and Akmal (1990), Khan (1980, 1982a) and Raza (1989), Mangla (1979) and Nisar and
Aslam (1983).Bahmani-Oskooee and Malixi (1991) estimate the demand for money (M1) in
Pakistan on the inflation rate, real output and the exchange rate.
Stock prices and exchange rates
Rehman (2005) found that the demand for money (M2) in Pakistan has a positive
relationship with real output and the exchange rate, and a negative relationship with the inflation
rate and the demand for money would increase as the rupee depreciates or that the wealth effect
dominates the substation effect.
Qayyum (2005) used the co-integration and error correction approach to estimate demand
for money function (M2), and concludes that the money demand function (with M2 money
balance) stable for Pakistan.
Zakir Hussain et.al (2006) used OLSQ Method and found that no co integration
and no-unit root in the demand for money function, regression analysis was performing.
The research was carried out in Pakistan to find the association between exchange rate,
stock Prices and demand for money function in Pakistan for the period 1971 – 2006. Important
findings of this research shows that stock prices positively and statistically significant and
exchange rate insignificantly associated to money demand in the long run. But in the short run
the inflation negatively and significantly effect on the money demand. The stock prices
positively wealth on money demand in the long run. Hence an increase in stock prices is
expected to dictate an easier monetary policy to prevent a given nominal income or inflation
target being undershot.
Stock prices and exchange rates
Data
This research makes use of the monthly exchange rate of Dollar to PKR and the stock
prices of the three listed companies in tobacco secoor of KSE-100 index namely Lakson
Tobacco, Khyber Tobacco, Pak Tobacco for the five years (2003-2007). The year 2007 for
Lakson is excluded from the analysis, due to variation in the data. The research comprises of
monthly rates (P1 that is the monthly closing rates) to determine the relationship between the
stock prices and exchange rates. Data gathered is secondary data from the KSE 100-index and
the business recorder.
Methodology
This research uses Bivariate Correlations and Regression. Correlation coefficient
describes the degree of relationship between two variables. The Bivariate Correlations computes
the Pearson's correlation coefficient, Spearman's rho, and Kendall's tau-b with their significance
levels. Pearson's correlation coefficient is a measure of linear association. Both the variables can
be perfectly related, given that the relationship is linear. But incase the relationship is not linear;
Pearson's correlation coefficient is not the correct measure for the association. The Linear
Regression is used to estimate the coefficients of the linear equation. It involves one or more
independent variables, which best predicts the dependent variable.
Stock prices and exchange rates
Empirical Results:
Table 1:
Regression:
Descriptive Statistics
Mean
Std.
Deviation N
Stock Price
P1 90.3706 101.34961 168
Dollar Rate
P1 59.4981 1.27915 168
Company 2.0000 .84768 168
62.0061.0060.0059.0058.0057.00
Dollar Rate P1
400.00
300.00
200.00
100.00
0.00
Sto
ck
Pri
ce
P1
2007
2006
2005
2004
2003
Year
Stock prices and exchange rates
The average of the tobacco industry stock prices was 90.3706. This means that the average stock
price of the 3 tobacco companies between the year 2003-2007 was RS. 90.3706. The standard
deviation is 101.34961. This means that the stock prices of the three companies were deviating
from the industry mean by 101.34961.
The mean of the Dollar rate was 59.4981 from the years 2003-2007 which means that the
average Dollar Rates in PKR was 59.4981during the period of analysis. The standard deviation
was 1.27915. This tells that the dollar values deviated by 1.27915 from its mean between the
years 2003-2007.
Table 2:
The correlation coefficient for the Pearson’s test of association was 0.205 between Dollar rates
and Stock prices and -.247 between company and stock prices, the coefficients’ are significant,
and indicate that a one unit change in dollar exchange rate might cause a 20.5% change in stock
price or one rupee change in Dollar rate will give a 20.5% change in stock price and in company,
one unit change in dollar will cause a decrease of 24.7% in stock prices of companies.
Correlations
1.000 .205 -.247
.205 1.000 .000
-.247 .000 1.000
. .004 .001
.004 . .500
.001 .500 .
168 168 168
168 168 168
168 168 168
Stock Price P1
Dollar Rate P1
Company
Stock Price P1
Dollar Rate P1
Company
Stock Price P1
Dollar Rate P1
Company
Pearson Correlation
Sig. (1-tailed)
N
Stock
Price P1
Dollar
Rate P1 Company
Stock prices and exchange rates
Table 3:
Mod
el R
R
Squar
e
Adjusted
R Square
Std. Error
of the
Estimate Change Statistics
R Square
Change F Change
df
1 df2
Sig. F
Chan
ge
1 .321(a) .103 .092 96.56163 .103 9.486 2
16
5 .000
Table 4:
The model summary show the R value of 0.321 which indicates that this model explain about
9.2% of total variations as dependent variable at significances of 0.000. The R square or the
proportion of variance between the stock prices and exchange rates is 0.092. The F- statistic is
9.486 where as significance level is 0. It is calculated by dividing the Mean Square (Regression)
by Mean Square (Residual), that is 88448.331/9324.149=9.486. It tells that the mean of the two
differ by9.486. The Error degree of freedom is the DF total (167) minus the DF model (2), that
is167 - 2 =165.
ANOVAb
176896.7 2 88448.331 9.486 .000a
1538485 165 9324.149
1715381 167
Regression
Residual
Total
Model
1
Sum of
Squares df Mean Square F Sig.
Predictors: (Constant), Company, Dollar Rate P1a.
Dependent Variable: Stock Price P1b.
Stock prices and exchange rates
Table 5:
The standardized coefficients value of Beta is 0.205 for dollar rate and -0.247 for company
significant at 0.006 and 0.01. By this it can be said that for the dollar rates, every 1 unit change in
the Dollar rate there was a 0.205 increase in the stock prices. For the company it can be said that
the relationship between the company and stock prices was a decrease of 0.247 in the stock
prices.
Table 6:
The collinearity diagnoses show the Eigen values of 2.895, 0.105 and o.000 for the dimensions 1,
2 and 3. This suggests that for the dimension 2 there is little variance and none for dimension 3.
For dimension 1 there is higher variance that is of 2.895. The condition index states that for
dimension 1 and 2 does not indicate a multi condition index. But dimension 3 suggests serious
Coefficientsa
-818.616 348.084 -2.352 .020
16.270 5.841 .205 2.785 .006 .205 .212 .205 1.000 1.000
-29.519 8.815 -.247 -3.349 .001 -.247 -.252 -.247 1.000 1.000
(Constant)
Dollar Rate P1
Company
Model
1
B Std. Error
Unstandardized
Coeff icients
Beta
Standardized
Coeff icients
t Sig. Zero-order Part ial Part
Correlations
Tolerance VIF
Collinearity Statistics
Dependent Variable: Stock Price P1a.
Collineari ty Diagnosticsa
2.895 1.000 .00 .00 .02
.105 5.258 .00 .00 .98
.000 112.314 1.00 1.00 .00
Dimension
1
2
3
Model
1
Eigenvalue
Condit ion
Index (Constant)
Dollar
Rate P1 Company
Variance Proportions
Dependent Variable: Stock Price P1a.
Stock prices and exchange rates
multi collinear index. The variance proportion is 0.98 for and 0.2 for dimension 2 for company.
This reveals that there is complete co linearity.
Conclusion
This research makes use of the monthly exchange rate of Dollar to PKR and the stock
prices of the three listed companies in tobacco sector of KSE-100 index namely Lakson
Tobacco, Khyber Tobacco, Pakistan Tobacco for the five years (2003-2007). The research
comprises of monthly rates (P1 that is the monthly closing rates) to determine the relationship
between the stock prices and exchange rates. Data gathered is secondary data from the KSE 100-
index and the business recorder.
Our research hypothesis states that Stock Prices are independent to Exchange rates,
which actually rejected by applying statistical tools.
This research uses Bivariate Correlations and Regression. Correlation coefficient describes
the degree of relationship between two variables. The Bivariate Correlations computes the
Pearson's correlation coefficient, Spearman's rho, and Kendall's tau-b with their significance
levels.
The correlation coefficient for the Pearson’s test of association was 0.205 between Dollar
rates and Stock prices and -.247 between company and stock prices, the coefficients’ are
significant, and indicate that a one unit change in dollar exchange rate might cause a 20.5%
change in stock price or one rupee change in Dollar rate will give a 20.5% change in stock price
and in company, one unit change in dollar will cause a decrease of 24.7% in stock prices of
companies.
Stock prices and exchange rates
The co linearity diagnoses show the Eigen values of 2.895, 0.105 and 0.000 for the
dimensions 1, 2 and 3. This suggests that for the dimension 2 there is little variance and none for
dimension 3. For dimension 1 there is higher variance that is of 2.895. The condition index states
that for dimension 1 and 2 does not indicate a multi condition index. But dimension 3 suggests
serious multi collinear index. The variance proportion is 0.98 for and 0.2 for dimension 2 for
company. This reveals that there is complete co linearity.
In the end, we conclude that Stock Prices of three listed Tobacco companies namely,
Pakistan Tobacco, Lakson Tobacco, and Khyber Tobacco for the five years (2003-2007) are
dependent of Exchange Rates.
Moreover, we hope that this research proves to be a good source of information for financial
institutions, stock exchanges and financial analysts. If any relation between the two variables
exists then this information could be made to use by the investors in order to predict the behavior
of one market on another. It can tell how one market or in specific the change in one market
would impact the other market or how will the other market be effected. This information could
be utilized to understand the relationship between the two markets.
Stock prices and exchange rates
References:
1. Naeem Muhammad, Abdul Rasheed (2002). ―Stock Prices and Exchange Rates: Are
they related? Evidence from South Asian Countries‖. The Pakistan Development Review,
Volume 41.
2. Bhattacharya & Mukherjee. ―Causal relationship between stock market and exchange
rate, foreign exchange reserves and value of trade balance: a case study for India‖.
3. Charles Adjasi, et.al (2008). “Effect of exchange rate volatility on the Ghana Stock
Exchange‖. African Journal of Accounting, Economics, Finance and Banking Research,
Vol. 3. No. 3.
4. Hooi Hooi Lean, Paresh Saroyan and Russell Smyth (2008). “Exchange rate and stock
price interaction in major Asian markets: evidence for individual countries and panels
allowing for Structural Breaks‖. Asian Business and Economics Research Unit.
5. Dr. Tulay Yucel, Guluzar Kurt (). “Foreign Exchange Rate Sensitivity and Stock Price
Estimating Economic Exposure of Turkish Companies.‖
6. Daniel Stavarek (2004). “Linkages between stock prices and exchange rates in the EU
and the United States.‖ Econ WPA Finance Series number 0406006.
7. Yaqiong Li, Lihong Huang. “On the Relationship between stock return and exchange
rate: evidence on China.‖ The Business School, Loughborough University, UK. College
of Mathematics and Econometrics, Hunan University, Changsha, Hunan, China.
8. Md. Lutfur Rahman, Jashim Uddin (2008). “Relationship between Stock Prices and
Exchange Rates: Evidence from Bangladesh.‖ International Journal of Business and
Management, Vol. 3, No. 9.
Stock prices and exchange rates
9. Mohamed Abdelaziz, et.al (2008). “Stock Prices, Exchange Rates, and Oil: Evidence
from Middle East Oil-Exporting Countries.‖
10. Desislava Dimitrova (2005). “The Relationship between Exchange Rates and
Stock Prices: Studied in a Multivariate Model.‖ Issues in Political Economy,
Vol.14.
11. Clive W.J. Granger, et.al (1998). “A Bivariate Causality between Stock Prices
and Exchange Rates: Evidence from Recent Asia Flu.‖ Department of Economics,
UCSD, UC San Diego
12. Aydemir, Demirhan (2009). “The Relationship between Stock Prices and
Exchange Rates Evidence from Turkey.‖ International Research Journal of
Finance and Economics, Issue 23.
13. Md. Lutfur Rahman, Jashim Uddin (2009). “Dynamic Relationship between
Stock Prices and Exchange Rates: Evidence from Three South Asian Countries.‖
International Business Research, Vol. 2, No. 2.
14. Shehu Usman Rano Aliyu (2009). “Stock Prices and Exchange Rate Interactions
in Nigeria: An Intra-Global Financial Crisis Maiden Investigation.‖
15. W.N.W. Azman-Saini, et.al (2006). “Stock prices, exchange rates and Causality in
Malaysia: a note.‖
16. Horobet , Alexandra and Ilie, Livia (2007). “On the Dynamic Link between Stock
Prices and Exchange Rates: Evidence from Romania.‖
17. Vardar, et.al (2008). “Effects of Interest and Exchange Rate on Volatility and Return of
Sector Price Indices at Istanbul Stock Exchange.‖ European Journal of Economics,
Finance And Administrative Sciences - Issue 11.
Stock prices and exchange rates
18. Maysami, et.al (2004). “Relationship between Macro Economic Variables and Stock
Market Indices: Co integration Evidence from Stock Exchange of Singapore’s All – S
Sectors Indices.‖ Jurnal Pengurusan 24(2004) 47-77.
19. Qazi Muhammad Adnan Hye, et.al (2009). “Relationship between Stock Prices,
Exchange Rates and Demand for Money in Pakistan.‖ Middle Eastern Finance and
Economics - Issue 3 (2009).