stock prices and exchange rates a review article

On the relation between stockprices and exchange rates: a review article Mohsen Bahmani-Oskooee and Sujata Saha The Center for Research on International Economics and Department of Econo

Journal of Economic Studies

On the relation between stock prices and exchange rates: a review article

Mohsen Bahmani-Oskooee, Sujata Saha,

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On the relation between stock

prices and exchange rates:

a review article

Mohsen Bahmani-Oskooee and Sujata Saha

The Center for Research on International Economics and Department of Economics, The University of Wisconsin-Milwaukee,

Milwaukee, Wisconsin, USA

Abstract

Purpose – While changes in stock prices are said to affect exchange rates, exchange rate changes are

also said to affect stock prices The purpose of this paper is threefold First, the authors review all

empirical literature by dividing them into two groups of univariate and multivariate studies Second,

a table which summarizes the main features of each study is provided to help future researchers to

have easy access to summary of each study Finally, a new direction for future research is proposed.

This new direction relies upon non-linear ARDL approach and shows how to investigate symmetric vs

asymmetric effects of exchange rate changes on stock prices.

Design/methodology/approach – The paper reviews existing published work and provides

suggestions for future research.

Findings – The paper reviews existing published work and provides suggestions for future research.

An application reveals that exchange rate changes have asymmetric effect on stock prices.

Originality/value – This is the first review paper on the relation between exchange rates and

stock prices.

Keywords Stock prices, Exchange rates, Review article, Asymmetry

Paper type Research paper

I Introduction

One of the areas in financial economics that has received the largest attention is the link

between foreign exchange market and the stock market The easiest way to infer the

link is by a reference to portfolio approach to exchange rate determination Under this

approach wealth is one of the main determinants of the exchange rate An increase in

stock prices usually increases public wealth This in turn increases the demand for

money and therefore, interest rates By attracting international investment, domestic

currency appreciates On the other hand, depreciation of domestic currency can boost

exports and eventually profit of exporting firms High profits once announced, can

cause share prices to rise Furthermore, depreciation raises cost of imported inputs

This can increase production cost even to firms that are not export oriented If higher

costs result in lower profits or expectation of lower profits, share prices could be

affected For this reason stock prices could move in either direction

Clearly if one needs to test the link between stock prices and exchange rates, one has

to concentrate on the current floating exchange rate system that began in 1973 For this

reason, almost all studies have engaged in empirical analysis using data from post-1973

period While some have concentrated on the link between stock prices and exchange

rates at bilateral level, some have included additional determinants of stock prices For

this reason, we review the empirical literature between the two variables at bilateral

Journal of Economic Studies Vol 42 No 4, 2015

pp 707-732

© Emerald Group Publishing Limited

0144-3585

Received 10 March 2015 Revised 10 March 2015 Accepted 11 March 2015

The current issue and full text archive of this journal is available on Emerald Insight at:

www.emeraldinsight.com/0144-3585.htm

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level in Section 2 In Section 3 we review studies that have included other variables

in their models In Section 4 we propose a direction for future research and finally,

we concluded in Section 5 A table is provided in which all features of the reviewedstudies are summarized[1]

II Review of bivariate studiesPerhaps the first study that concentrated on the relation between stock prices andexchange rates is that of Aggarwal (1981) who used monthly data during the period1974-1978 from the USA By using an aggregate index of stock prices and effectiveexchange rate of the dollar he showed that there is a positive relation between the twovariables, i.e., dollar depreciation or a decline in the effective exchange rate of the dollarcaused stock price to decline The implication is that more firms were hurt bydepreciation than helped Exactly opposite was concluded when Soenen and Hennigar(1988) looked into the response of stock prices of seven industrial sectors in the USA tochanges in the value of the dollar The seven sectors were selected on the belief thatthey were affected heavily by international trade The seven sectors were automobile,computer, machinery, paper, textile, steel and chemical The finding that the relationbetween stock price of each sector and the value of the dollar was negative implied that

as dollar depreciates, every sector exports more and rips profit from trade

None of the studies mentioned above accounted for integrating properties of the twovariables nor for cointegration between them Thus, their findings could suffer fromspurious regression problem To resolve the issue, Bahmani-Oskooee and Sohrabian(1992) used monthly data from the period of 1973-1988 to show that index of S & P 500and the effective exchange rate of the dollar are non-stationary variables Application

of Engle and Granger (1987) cointegration analysis revealed that there is no long-runrelationship between the two variables However, application of the Granger causalitytest revealed that the two variables Granger cause each other in the short run.The Asian financial crisis of 1997 triggered a renewed interest in studying theinteraction between exchange rates and stock prices, mostly in developing countries.Granger et al (2000) concentrated on East-Asian countries of Hong Kong, Indonesia,Japan, South Korea, Malaysia, the Philippines, Singapore, Thailand and Taiwan and usedGranger causality test and Gregory-Hansen cointegration test to analyze the relationshipbetween stock prices and exchange rates They used daily data for the period 1986-1997and showed that exchange rate changes affect stock prices in Japan and Thailand ForTaiwan, the relationship was reversed, that is, stock prices affected exchange rates Theyfound bi-directional relationship between the two variables in Indonesia, South Korea,Malaysia and the Philippines, a finding similar to that of Bahmani-Oskooee andSohrabian (1992) for the USA However, Singapore failed to show any pattern ofrelationship Through Granger causality test it was inferred that exchange rates affectedstock prices in eight of the nine countries Following the same path, Nieh and Lee (2001)used daily data from the period 1993-1996 and explored the dynamic relationshipbetween stock prices and exchange rates in the G-7 countries (Canada, France,Germany, Italy, Japan, UK and USA) Engle-Granger and Johansen maximum likelihoodmethods of cointegration were applied Their results, again, supported the findings ofBahmani-Oskooee and Sohrabian (1992) and reported that there was no long-runrelationship between stock prices and exchange rates in all of the G-7 countries Theresults of VECM estimation suggests that the two financial variables do not havepredictive capabilities for more than two consecutive days and thus there is a short-runsignificant relationship which lasts only for one day for certain G-7 countries

Continuing the same line of research, Smyth and Nandha (2003) examined the

relationship between stock prices and exchange rates in four South-Asian countries of

Bangladesh, India, Pakistan and Sri Lanka using daily data from 1995 to 2001 Like

previous studies, using Engle-Granger as well as Johansen’s cointegration techniques,

they were unable to find any long-run equilibrium relationship between the two

variables in any of the four countries Using Granger causality test they also concluded

that exchange rates Granger cause stock prices in India and Sri Lanka but for

Bangladesh and Pakistan they found no evidence of causality running in either

direction During a crisis period the fluctuations in stock prices and exchange rates are

high The Asian financial crisis of 1997 led to series of financial downfall To consider

experiences of other countries in the crisis region, Lean et al (2005) used weekly data

from 1991 to 2002 for Hong Kong, Indonesia, Singapore, Malaysia, South Korea, the

Philippines and Thailand to study the pre- and post-crisis scenario and the effect of

9-11 terrorist attack Japan was used as a control They applied both cointegration and

bivariate causality technique For all of the countries except for the Philippines

and Malaysia, they found no evidence of Granger causality between stock prices and

exchange rates in the period before Asian financial crisis During the crisis period, they

found evidence of causality between the two variables Results show no cointegration

between the variables before or during the Asian crisis of 1997 but after the 9-11

terrorist attack, weaker cointegration relationships between the variables were found

Phylaktis and Ravazzolo (2005) used monthly data from 1980 to 1998 for Hong Kong,

Indonesia, Malaysia, the Philippines, Singapore and Thailand They analyzed the

short- and long-run relationships between exchange rates and stock prices and the

avenues through which exogenous shocks affect these two variables They found that

exchange rates and stock prices are positively related using the method of cointegration

and Granger causality tests US stock price is the causing variable which acts as a

channel that links the exchange rates of the five countries to their stock market indices

Shifting to Europe, Obben and Shakur (2006) analyzed the relationship between

the performance of the stock market and exchange rates in New Zealand using a

cointegrating VAR approach using weekly data from 1999 to 2005 The five exchange

rates were those currencies that are used in the construction of New Zealand’s

trade-weighted index series They concluded that both in the short run and long run there is

bi-directional causality between the five exchange rates and a couple of share price indices

With regards to non-dollar exchange rates, Yau and Nieh (2006) used monthly data of

Japan and Taiwan from 1991 to 2005 to study the relationship among stock prices

of Taiwan and Japan and NTD/Yen exchange rate They applied Granger causality test

and found that there is bi-directional causality between the stock prices of Taiwan and

Japan but there is no significant causal relationship between the NTD/Yen exchange rate

and the stock prices of Japan and Taiwan From the Johansen method of cointegration it

was concluded that there was no long-run relationship among the three variables

However, Yau and Nieh (2009) revisited the issue by testing for cointegration with

threshold effect between the stock prices and the exchange rates in Japan and Taiwan

and the effect of US exchange rate on the financial market of Taiwan Using monthly

data from 1991 to 2008, they found evidence of a long-run equilibrium relationship

between NTD/JPY and the stock prices of Japan and Taiwan There was no short-run

causal relationship between the two countries financial assets which means that

exchange rate and stock price movements do not affect each other significantly in the

short run The results supported the traditional approach that a long-run positive

relationship runs from exchange rates of either Japan or USA to stock prices of Taiwan

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For seven Asian countries (Hong Kong, Japan, Korea, Malaysia, Singapore, Taiwanand Thailand), Pan et al (2007) applied the methods of Granger causality and Johansencointegration test to examine the linkages between stock prices and exchange ratesusing daily data from 1988 to 1998 They concluded that during the Asian financialcrisis period there is no long-run equilibrium relationship between exchange rates andstock prices For Hong Kong, Japan, Malaysia and Thailand there existed a significantcausal relationship from exchange rates to stock prices before the 1997 Asian financialcrisis and during the financial crisis period they found causal relationship fromexchange rates to stock prices for all countries except for Malaysia.

All studies reviewed above have assumed that the relation between a stock priceand an exchange rate is linear Ismail and Isa (2009) uses Markov Switching VARmodel and assume the two variables to be regime dependent They then studied thenon-linear relationship between exchange rates and stock prices in Malaysia usingmonthly data from 1990 to 2005 The Johansen cointegration test suggested evidence of

no cointegration between the variables Their analysis showed that a non-linear model

is more appropriate to model all the series than the linear model They also foundevidence of common regime switching behavior between the variables Whether linear

or non-linear relationship, it appears that no study finds evidence of long-runrelationship This is also true of Rahman and Uddin (2009) who used monthly datafrom 2003 to 2008 for Bangladesh, India and Pakistan and the method of Johansencointegration and Granger causality test Not only they found evidence of no long-runrelationship between stock prices and exchange rates, they also found no causalrelationship in either direction between the variables The implication is that marketparticipants cannot use information of one market to help to forecast the other market.Considering the experience of Australia, using daily data from 2003 to 2006,Richards et al (2009) studied the relationship between the two variables UsingJohansen cointegration test they showed that that both stock prices and exchange ratesare cointegrated in the long run The method of Granger causality test supported theportfolio balance model which says that changes in stock prices affect changes inexchange rates However, using weekly data from 1989 to 2006, Kutty (2010) wasunable to support cointegration in Mexico, though some evidence of short run Grangercausality was reported Considering the Chinese experience, the dynamic relationshipbetween exchange rates and stock prices was studied by Zhao (2010) using monthlydata from 1991 to 2009 Applying Johansen method of cointegration, the results showed

no stable long-run equilibrium relationship between the real effective exchange rateand the stock price The source and the magnitude of the spillovers were identifiedthrough vector auto-regression and multivariate generalized autoregressive conditionalheteroskedasticity models From the foreign exchange market to the stock market therewas no mean spillover effect but there was bi-directional volatility spillover effects.Further attempt was made by some studies to consider the link between the twovariables by using updated data To that end, Alagidebe et al (2011) used monthly datafrom 1992 to 2005 for Australia, Canada, Japan, Switzerland and UK Again, they found nolong-run relationship between the variables Through Granger causality test it was foundthat in Canada, Switzerland and UK, there is causal linkage from exchange rates to stockprices and in Japan there is causality running from stock prices to exchange rates In thesame line, Harjito and McGowan (2011) used weekly data from 1993 to 2002 for Indonesia,the Philippines, Singapore and Thailand and reported evidence of bi-directional causality

in Thailand and Singapore They also found cointegration between exchange rates andstock prices and cointegration among the stock markets of all four countries

By using weekly data from 1999 to 2010 for the countries of Australia, New Zealand,

Japan, Switzerland, USA, UK and Euro Zone, Katechos (2011) examined the

relationship between stock markets and exchange rates in the light of the global equity

market returns The method of maximum likelihood regression with GARCH was

applied and results showed that there is a link between the exchange rates and the

global stock market returns but the characteristics of the currencies determine the sign

of the relationship The value of currencies with higher rates of interest is positively

related to global equity returns and the value of currencies with lower rates of interest

is negatively related to global equity returns Larger is the interest rate differential

more is the explanatory power of the model Sticking to weekly data, Lean et al (2011)

used weekly data from 1990 to 2005 for Hong Kong, Indonesia, Japan, Korea, Malaysia,

the Philippines, Singapore and Thailand and examined the interactions of exchange

rates and stock prices by allowing for structural breaks They applied the methods of

panel Lagrange Multiplier (LM) cointegration, Gregory-Hansen test for cointegration

and Granger causality test to find little evidence of long-run equilibrium relationship

between exchange rates and stock prices Only in Korea, exchange rates and stock

prices were cointegrated The predictive power of the two variables is limited only to

short run, though not for all countries Again, using weekly data during 2000-2008

period, Lee et al (2011) considered the experience of Indonesia, Korea, Malaysia, the

Philippines, Taiwan and Thailand to examine the relationship between the two

variables and the effect on their correlation due to stock market volatility They used

the method of Smooth Transition Conditional Correlation GARCH model to show

that in Indonesia, Korea, Malaysia, Thailand and Taiwan there are significant price

spillovers from stock market to foreign exchange market Stock market volatility does

affect the correlation between the stock and foreign exchange markets For all the

countries except for the Philippines, the correlation becomes higher when the stock

market becomes more volatile

Using rolling regression analysis, Kollias et al (2012) studied the link between the

two variables The advantage of using rolling regression is, with the sample size

remaining same, at a time, the sample period moves forward by one observation

Hence it takes into account of the new information available They used daily data

from 2002 to 2008 for European countries and showed that there is no long-run

relationship between the two variables The direction of causality depends on the

condition of the market There is causality running from exchange rates to stock

prices under normal situation whereas causality might run from stock prices to

exchange rates during crisis situations

Deviating from standard approaches, Tsai (2012) employed quantile regression

approach on monthly data from 1992 to 2009 for Singapore, Thailand, Malaysia, the

Philippines, South Korea and Taiwan The method of quantile regression helps to

study the relationship under different market conditions (“different quantiles of

exchange rates”) Exchange rates and stock prices are negatively related when the

exchange rates are extremely high or low So depending on the conditions of the

market, the relationship can change Considering exchange rates other than against

the US dollar, Wickremasinghe (2012) examined the relationship between stock

prices and the Sri Lankan exchange rates against the Indian rupee, the Japanese yen,

the British pound and the US dollar The results produced no evidence of any

long-run relationship between any of the four exchange rates and stock prices in

Sri Lanka There was only evidence of unidirectional causality running from stock

prices to Sri Lankan exchange rate against US dollar Through variance

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decomposition analysis it was inferred that most of the variance of the stock price isexplained by Indian rupee[2].

Most of the papers reviewed so far concentrated either on developed or ondeveloping countries However, Buberkoku (2013) considered both developed anddeveloping countries and used monthly data from 1998 to 2008 to study therelationship between stock prices and exchange rates for countries like Australia,Canada, England, Germany, Japan, Singapore, South Korea, Switzerland and Turkey.The methods used were Engle-Granger and Johansen cointegration test and Grangercausality test The results showed that in the long run there is no relationship betweenthe variables in the considered countries, except for Singapore In the short run, stockprices affect exchange rates in Canada, Switzerland and Turkey Causality runs fromexchange rates to stock prices for Singapore and South Korea But for Australia,England, Germany and Japan there was no causal relationship in either directions

To test for sensitivity of the results to data frequency, Tsagkanos and Siriopoulos(2013) used both daily and monthly data from 2008 to 2012 for European Union andUSA to study the relationship between the two variables during the financial crisis of

2008 to 2012 They applied methods of structural non-parametric cointegratingregression, Johansen cointegration test and Granger causality test They found thatmovements in stock prices affect movements in exchange rates in EU in the long runand in USA in the short run Paying special attention to the crisis period, Caporale et al.(2014) focussed on the banking crisis period of 2007-2010 to analyze the connectionsbetween stock prices and exchange rates For Canada, Euro area, Japan, Switzerland,

UK and USA, they used weekly data which were sub-divided into time periods: the crisis period (2003-2007) and the crisis period (2007-2011) Using Bivariate UEDCC-GARCH models they found that in the short run there is unidirectional Grangercausality from stock returns to exchange rate changes in the USA and the UK; in theopposite direction in Canada, and for the Euro area and Switzerland there isbi-directional causality Causality-in-variance from stock returns to exchange ratechanges is found in the USA and for the Euro area and Japan it is in opposite direction,while there is evidence of bi-directional feedback in Switzerland and Canada Duringthe recent financial crisis, dependence between the two variables has increased.Finally, in this bivariate models Yang et al (2014) used daily data from 1997 to

pre-2010 for India, Indonesia, Japan, Korea, Malaysia, the Philippines, Singapore, Taiwanand Thailand to study the relationship between stock returns and exchange rates.They applied Granger causality test in quantiles and they found that during theAsian financial crisis, all the countries except for Thailand there are feedbackrelations between exchange rates and stock prices and in Thailand, stock returns leadexchange rates The causal effects are heterogeneous across different quantiles anddifferent periods and most of the stock and foreign exchange markets are negativelycorrelated

The findings by bivariate studies reviewed above could be biased due to otheromitted variables from the models The next group of studies try to address this issue

by including other macro variables in their model

III Multivariate modelsOver the past recent years due to the trend of the globalization, capital flows amongdifferent international markets has increased which has also led to the increase in closerelationship between the stock markets and the foreign exchange markets Empiricalstudies have also focussed on examining the effect of different macroeconomic

variables on stock market The analysis of the effects of different macroeconomic

variables like inflation, GDP, industrial production index, money supply, oil prices,

interest rates, foreign capital, exchange rates, etc are important since they can help

policy makers of an economy to better formulate policies Investors find important and

interesting to see how and which variables cause the stock prices to fluctuate Using an

APM model, Chen et al (1986) examined the effect of different macroeconomic variables

(industrial production, inflation, risk premia, etc.) on the stock returns of the USA and

found that macroeconomic variables have significant effect on expected stock returns

Fama and French (1993) examined four to five factors that affect stock returns and

stock prices

Tian and Ma (2010) studied the relationships among stock prices and macroeconomic

variables like exchange rates, money supply, industrial production and consumer price

index using monthly data from 1995 to 2009 for China They employed the ARDL

method of cointegration Their results show that prior to financial liberalization of 2005,

no cointegration exists between the major foreign exchange rates and the Shanghai

stock price index After the liberalization, cointegration exists Money supply and

exchange rates affect stock prices with positive correlation in China and also previous

month CPI Granger causes stock prices Using Johansen method of cointegration,

Chortareas et al (2011), for countries like Egypt, Kuwait, Oman and Saudi Arabia

examined the role of oil prices as a link between the stock markets and exchange rates

They used monthly data from 1994 to 2006 and their results show that when oil price is

not considered, there is no long run cointegration between exchange rates and stock

prices Inclusion of oil prices show no cointegration between exchange rates and stock

prices when full sample period is considered Before the oil price shock of 1999, no

cointegration among the variables was found After the shock, exchange rates, stock

prices and oil prices are cointegrated in Egypt, Oman and Saudi Arabia But for

Kuwait, there is long-run relationship only between stock prices and oil prices Real

exchange rates are positively related to stock prices in Egypt and Oman and in

Saudi Arabia they are negatively related Oil prices have long-run positive effect on

stock prices The model employed by Liu and Tu (2011) included exchange rate and

foreign capital as determinants of stock prices They used daily data from 2001 to 2007

from Taiwan to study the relationships among the variables and to analyze whether in

these markets the properties of asymmetric volatility switching and mean-reverting

exists or not They found that the movements of the exchange rate and the stock price

index are affected by overbuying and overselling rates of foreign capital All of the

three conditional means exhibit asymmetric mean-reverting behavior (negative returns

reverting quicker than positive returns) The volatility of the three markets exhibited

GARCH effects

The model employed by Parsva and Lean (2011) included like interest rates, inflation

rates and oil prices as main determinants of stock prices in Egypt, Iran, Jordan, Kuwait,

Oman and Saudi Arabia Using monthly data from 2004 to 2010 they estimated their

model using Johansen method of cointegration and Granger causality test They found

that in the long run, all variables are cointegrated Both in short run and long run there is

bi-directional causality between stock prices and exchange rates for Egypt, Iran and

Oman before the crisis In Kuwait causality runs from exchange rates to stock prices in

the short run Comparing the pre- and post-crisis periods, there was not much distinction

in the behavior of exchange rates and stock returns Oil price was also included in a

model by Basher et al (2012) who used monthly global data from 1988 to 2008 to examine

the relationship among stock prices in emerging markets Additionally, they included

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global real economic activity as one of the variable which affects oil prices Using astructural VAR model and through the analysis of impulse response function they foundthat positive shock to oil prices decreases emerging markets stock prices and US dollarexchange rates in the short run Exchange rates respond to changes in oil prices in theshort run, a positive shock to oil prices leads to decrease in trade-weighted exchangerates Oil price decreases with increase in oil production but a positive shock to realeconomic activity increases the price of oil Along similar lines, Eita (2012) employedJohansen’s method and quarterly data from 1998 to 2009 for Namibia to examine thedeterminants of stock prices The results showed that stock prices are affected byeconomic activity, exchange rates, inflation, interest rates and money supply Stockprices increase with increase in economic activity and money supply and stock pricesdecrease with increase in inflation and interest rates Exchange rates, GDP, moneysupply and inflation move stock market away from equilibrium Similarly, Inegbedion(2012) considers the experience of Nigeria by using data from 2001 to 2009 By applyingCochran-Orcutt Autoregressive Model, the results show that exchange rates and stockprices are negatively related The relationship of stock prices with interest rates andinflation, respectively are not significant But the joint effect of all the variables on stockprices is significant[3].

Foreign reserves and interest rates were added as additional variables into therelation between stock price and exchange rate to explore the effects of portfolioadjustment by Lin (2012) Using monthly data during 1986-2010 and the ARDLapproach, the model was estimated for Asian emerging countries of India, Indonesia,Korea, Philippines, Taiwan and Thailand During crises periods, in terms of long runcointegration and short-run causality, the co-movement between exchange rates andstock prices became stronger Spillover effect was mostly from stock price shocks toexchange rates Further analysis showed that the co-movement is generally driven bycapital account balance than the trade balance Separately, Pakistan was the country ofconcern by Aslam and Ramzan (2013) who studies the effects of the real effectiveexchange rate index, CPI, per capita income and discount rate on the stock prices.Applying NLS and ARMA techniques revealed that while discount rates and inflationnegatively affected Karachi stock price index, per capita income and real effectiveexchange rate index affected positively Discount rate impacted stock index the most.This study helps to understand how effectively a country can control itsmacroeconomic variables for better performance of the stock market In the samevein, commodity prices are introduced into the relation between the exchange rate andstock market by Groenewold and Paterson (2013) who employed monthly data during1979-2010 from Australia Their results showed that when commodity prices are notconsidered, there is no cointegration between exchange rates and stock prices With theinclusion of commodity prices, all the three variables are cointegrated in the long run.When only exchange rates and stock prices are considered, there is no causalitybetween them in either direction In the short run, exchange rates affect commodityprices and commodity prices in turn affect stock prices

Different macro variables in Pakistan were also considered by Khan et al (2013) whoused monthly data from 1998 to 2008 The macroeconomic variables considered weremarket returns, CPI, risk-free rate of return, industrial production and M2 The resultsshowed that both stock prices and exchange rates affect each other in the short run butthere is no long run association between the variables In the long run, market returnand risk-free return are not related to stock prices but there is some association ofindustrial production and stock prices There exists both short run and long-run

relationship between stock prices and inflation and money supply Boonyanam (2014)

explored the relationship between different monetary variables with stock prices

The monetary variables included were nominal bilateral exchange rate in terms of Baht

per US dollar, CPI, narrow money and 14 days repurchase rate and the methods used

were multivariate cointegration, VECM and variance decomposition analysis Monthly

data from 1999 to 2012 was used for Thailand and the results show evidence of

long-run relationship between stock prices and monetary variables In the short run,

narrow money and interest rate affect stock prices There is one way causality from

exchange rates to stock prices and from interest rates to stock prices There was also

positive relationship between CPI and stock price

Rather than using stock prices, Moore and Wang (2014) examines the source of the

relationship between stock return differentials and real exchange rates using monthly

data for Australia, Canada, Indonesia, Japan, the Philippines, Malaysia, Singapore,

South Korea, Thailand and the UK At the first stage, the dynamic conditional

correlation (DCC) is derived between the two variables and then the derived DCC is

used to regress on the interest rate differentials and the trade balance With the help of

bivariate GARCH model with DCC they found that there is a negative relationship

between the relative stock prices and real exchange rates There exists time-varying

correlation between stock return differentials and real exchange rate changes The US

stock market influences the foreign exchange market and local stock market Trade

balance is the major determinant of the dynamic correlation for Asian market and

interest rate differential is the key factor for developed countries For the countries

where capital mobility is low, economic integration acts as the cause of the linkage and

thus it supports the flow-orientated model But where capital mobility is more, financial

integration acts as the cause of the linkage which in turn favors the stock-oriented

model Finally, the case of Turkey is considered by Tuncer and Turaboglu (2014) who

used quarterly data from 1990 to 2008 to examine the short run and long-run

relationships between stock prices and GDP, treasury bills rates and exchange rates

They employed the method of Johansen test for cointegration to study the long-run

relationship and found evidence of long-run relationship between stock prices and the

other variables In the short run, stock prices and real effective exchange rate affect

GDP but there is no causality relationship from treasury bills to GDP There is

causality from real effective exchange rates to stock prices All the variables do not

affect exchange rates in the short run hence exchange rate is comparatively an

exogenous variable

In sum, the literature on the relation between stock prices and exchange rate is vast

From the review of more recent studies it is clear that the link between the two

variables is dependent on the data frequency and period chosen, the countries studied,

and other macro variables, etc But in general most of the papers concluded that in the

short run, stock prices and exchange rates are related but there is no relationship

between them in the long run Other macroeconomic variables like, CPI (inflation rate),

interest rates, discount rates, oil prices, money supply, industrial production, GDP and

foreign capital also are found to affect stock prices Table I provides the main features

of each study reviewed

IV A new direction for future research

The models reviewed in the previous section and all studies listed in Table I have one

common feature They have all assumed that the effects of exchange rate changes on

stock prices are symmetric, i.e., if depreciation has positive effects on stock prices,

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