# 4 (130) ³åñÇÉ 2011 45
Table 4: 5. Conclusion
Result of Granger Causality Test According to the result of empirical study, we conclude that
Null Hypothesis F-Statistic Probability
Iran GDP dos e not Granger causing TEDP IX 3.03050 0.19461
GDP of our sample country don’t have Granger Causality relation-
United K ingdom GDP dos e not Granger causing FTSE 100 7.88946 0.06061 ship with their Stock Exchanges.
Turkey GDP dose not Granger caus ing ISE 100 Index 0.96533 0.53317
Japan GDP dose not Granger causing TOPIX 2.53924 0.23496
P hilippine GDP dose not Granger caus ing PSE Index (PSEi) 10.6205 0.08790
Malaysia GDP dose not Granger causing FBM Emas Index 0.25047 2.38566
Indonesia GDP dose not Granger caus ing JSX Composite Index 3.63634 0.15862 1. Filer Randall, Henhouse Jan, and Canpos Naeuro,
Aus tralia GDP dos e not Granger causing Australian Stock Exchange 3.09045 0.19047 Do Stock Market Promote Economic Growth, Working Paper from
Canada GDP dose not Granger causing S&P/TSX Composite 1.00527 0.51924
the Center for Economic Research and
USA GDP dos e not Granger causing NYSE Euronext 1.34628 0.42016
Graduate Education- Economic Institute, 2000.
on them. The test result is shown in table3. 2. Geo Liang Ping, Liu Si-Feng Mi, and Chuan Min,
As table 3 shows the Dickey Fuller augmented statistic values of Empirical study on relationship between GDP and stock index:
Based on the degree of gray incidences, International conferences on
series with lag 0 are smaller than test critical values of series at 1%
information and automation, December 15-18, 2005 Colombo, Srilanka.
level, 5% level and 10% level. From the previous tests, it can be 3. Leigh Lamin, Stock market equilibrium and macroeconomic
concluded that series are integrated of order one, I(1). fundamentals, Working Paper from IMF, 1997.
II. Granger Causality Test 4. Levin Ross and Zervos Sara, Stock market development and long-run
In this paper we carry out Granger Causality Test with lag length growth, World Bank Economic Review, Vol. 10, #2, 323-339, 1996.
3.the result are shown in table 4. 5. Modis Theodore, Sunspots, GDP and the stock market, Technological
According to table 4, to reject the null hypothesis that GDP dose forecasting and social change, 74 (2007) 1508-1514.
not granger cause stock exchange indexes. 6. Poon Ser-huang and Tylor Stephen, Stock returns and volatility:
an empirical study of the UK stock market,
They indicate that the probability that GDP dose not granger
Journal of banking and finance, Vol. 107, #5, 402-437, 1992.
causing indexes are too great to reject the null hypothesis. 7. World Bank reports fir GDP, www.worldbank.org
Therefore there are no granger causality relationship between 8. World Federation of Exchanges,
GDP growth and index growth. Annual reports, available at: www.world-exchanges.org
his paper examines whether stock index and exchange rates as one of the main determinants of business profitability
rates are related to each other or not. The variables are and equity prices (Kim, 2003).
Tehran stock index of Iran, market capitalization of Armenia The relationship between stock prices and exchange rates has
NASDAQ OMX and exchange rate of both countries. preoccupied the minds of economists since they both play important
The study uses monthly data on two Asian countries, including roles in influencing the development of a country’s economy.
Iran and Armenia, for the period January 2006 to Mars 2011 for Also this issue, have received considerable attention after the
Armenia and April 2002 to Mars2011 for Iran. We employed stan- East Asian crises. During the crisis countries affected in both
dard Granger causality tests to examine association between stock currency and stock markets. If stock prices and exchange rates are
indices and exchange rates. The results of this study show no related and the causation runs from exchange rates to stock prices,
Granger Casualty between the said variables for every country. then crises in the stock markets can be prevented by controlling the
Keywords: Stock exchange, Exchange rate stock index, market exchange rates. Moreover, developing countries can exploit such a
capitalization, Granger Causality link to attract or stimulate foreign portfolio investment in their own
countries. Similarly, if the causation runs from stock prices to
exchange rates, then authorities can focus on domestic economic
Knowledge of the factors that influence the behavior of stock
policies to stabilize the stock market. If the two markets are related,
indices and exchange rates has attracted the attention of econo-
mists, policy makers, and the investment community for a long then investors can use this information to predict the behavior of
time. This is especially noteworthy since 1973 when the many one market, using the information on other market. It means that
countries in the world adopted freely floating (or managed floating) Investors can use this information for speculation and to hedge their
rate systems. return on foreign investment.
Many factors, such as enterprise performance, dividends, The main purpose of the present study is to complement the
stock prices of other countries, gross domestic product, existing literature on the stock market – macroeconomic nexus in
exchange rates, interest rates, current account, money supply, two respects. First, is to determine whether stock indices are a lead-
employment, their information etc, have an impact on daily stock ing indicator for future Exchange Rate or vice versa and second to
prices (Kurihara, 2006). Especially, the continuing increases in exam the informational market efficiency about exchange rate in
the world trade and capital movements have made the exchange Iran and Armenia.
THE RELATIONSHIP BETWEEN
STOCK PRICES AND EXCHANGE RATES:
EVIDENCE FROM IRAN AND ARMENIA
Revealing co-movements of financial
markets in iran and armenia in a BASHIRI
consequence of processes occurring in
the world financial markets Student of PHD
Course in Yeravan state university
Miqayel HOVSEPYAN department of International
Doctor of economical sciences, economics faculty of economics
Ð³Û³ëï³Ý üÆÜ²ÜêÜºð & ¾ÎàÜàØÆÎ²
Table 1: rate. On the other hand, negative causal relationship
Unit Root Test
Tes t Critical Values
from exchange rate to all stock market indices is deter-
Series ADF 10% mined (Aydemir and Demirhan, 2009).
1% level 5% level
level Adjasi determined whether movements in
Exchange exchange rates have an effect on stock market in
Rate(USD:AMD) -6.190179 -4.198503 -3.523623 -3 .192902
Ghana. The Exponential Generalised Autoregressive
-3 .192902 Conditional Heteroskedascity (EGARCH) model was
NASDAQ OMX mark et
-5.909714 -4.198503 -3.523623
used in establishing the relationship between
Rate(USD:IRR) -17.07368 -4.049586 -3.454032 -3 .152652 exchange rate volatility and stock market volatility. It
was found that there is negative relationship between
Tehran Stock Exchange
-9.815927 -4.049586 -3.454032 -3 .152652 exchange rate volatility and stock market returns
depreciation in the local currency leads to an increase
Table 2: in stock market returns in the long run; where as in the
Unit Root Test - order one, I(1)
short run it reduces stock market returns. Additionally,
Test Critical Values
Series ADF there is volatility persistence in most of the macroeco-
1% level 5% level 10% level
-1.803939 -3.565430 -2.919952 -2.597905
nomic variables; current period’s rate has an effect on
forecast variance of future rate (Adjasi, 2008).
NASDAQ OMX market
-0.871605 -3.565430 -2.919952 -2.597905 In a paper, Desislava Dimitrova studied if there is a
Exchange Rate(USD:IRR) link between the stock market and exchange rates that
-2.235214 -3.494378 -2.889474 -2.581741
might explain fluctuations in either market. He make
Tehran Stock Exchange
-2.279046 -3.494378 -2.889474 -2.581741 the case that, in the short run, an upward trend in the
stock market may cause currency depreciation,
Results of long run Causality Table 3: whereas weak currency may cause decline in the
stock market. To test these assertions, he used a mul-
Null Hypothesis F-Statistic Probability
tivariate, open-economy, short-run model that allows
Iran Stock Index dose not Granger causing Exchange rate of Iran 0.78281 0.55996 for simultaneous equilibrium in the goods, money, for-
Exchan ge rate of Iran dose not Granger causing Iran Stock Index 0.55543 0.57562 eign exchange and stock markets in two countries.
Armenia market capitalization dose not Granger causing Exchan ge 1.85813 0.17061 Specifically, this paper focused on the United States
rate of Armenia and the United Kingdom over the period January 1990
Exchange rate of Armenia d ose not Granger causing Armenia market 0.11320 0.89329
through August 2004. It found support for the hypoth-
esis -that a depreciation of the currency may depress
II. Literature review the stock market—the stock market will react with a less than one
Over the past few decades, determining the effects of macroeco- percent decline to a one percent depreciation of the exchange rate.
nomic variables on stock prices and investment decisions has pre- This also implies that an appreciating exchange rate boosts the
occupied the minds of economists, therefore in the literature; there stock market (Dimitrova, 2005).
are many empirical studies to disclose the relationship between Another paper investigates the nature of the causal relationship
macroeconomic variables such as interest rate, inflation, exchange between stock prices and macroeconomic aggregates in the for-
rates, money supply, oil price, gold price etc and stock indices. eign sector in India. It tests the causal relationships between the
However, the direction of causality still remains unresolved in both BSE Sensitive Index(stock exchange) and the three macroeconom-
theory and empirics. In this part we will explain some Previous ic variables, exchange rate, foreign exchange reserves and value of
Empirical Studies about this subject. trade balance using monthly data for the period 1990-91to 2000-01.
The first study has done by Gopalan Kutty and has examined the The results suggest that there is no causal linkage between stock
relationship between stock prices and exchange rates in Mexico. prices and the three variables under consideration (Bhattacharya
The stock index data for this study is obtained from Dow Jones and Mukherjee, 2001).
News/Retrieval provided by Dow Jones. It consists of weekly clos- Naeem Muhammad and Abdul Rasheed, study four South Asian
ing of Bolsa, Mexico’s equity index, a market capitalization weight- countries, including Pakistan, India, Bangladesh and Sri- Lanka, for
ed index of the leading 35-40 stocks. Mexican Peso per US dollar the period January 1994 to December 2000. The results of this
starting from the first week of January 1989 to the last week of study show no short-run association between the variables for all
December 2006 was obtained from the International Monetary four countries. There is no long-run relationship between stock
Market. After eliminating some of the incompatible data, a total of prices and exchange rates for Pakistan and India as well. However,
849 data points were generated. The Granger causality test shows for Bangladesh and Sri-Lanka there appear to be a bi-directional
that stock prices lead exchange rates in the short run, and there is causality between these two financial (Muhammad and Rasheed,
no long run relationship between these two variables. This finding 2000).
corroborates the results of Bahmani-Oskooee and Sohrabian’s con-
clusion, but contradicts the findings of other studies which reported III. Methodology and Data:
a long term relationship between exchange rates and stock prices In this study we use monthly data of Exchange rate and Stock
(Kutty, 2010) and (Bahmani et.al 1992). Exchange performance for the period Jun 2006- Mar2011for
In other study Aydemir and Demirhan investigate the causal rela- Armenia and Apr2002-Mar2011 for Iran. In this study we consider
tionship between stock prices and exchange rates, using data from the US Dollar monthly average price as exchange rate and Tehran
23 February 2001 to 11 January 2008 about Turkey. The reason of stock index as Iran Stock Exchange indicator. We also employ
selecting this period is that exchange rate regime is determined as NASDAQ OMX market capitalization as the indicator of Armenia
floating in this period. In this study, national 100, services, financials, capital market.
industrials, and technology indices was taken as stock price indices. Traditionally to test for the causal relationship between two vari-
The results of empirical study indicate that there was bidirectional ables, the standard Granger (1969) test has been employed in the
causal relationship between exchange rate and all stock market relevant literature. This test states that, if past values of a variable Y
indices. While the negative causality exists from national 100, serv- significantly contribute to forecast the value of another variable Xt+1
ices, financials and industrials indices to exchange rate, there is a then Y is said to Granger cause X and vice versa. The main step for
positive causal relationship from technology indices to exchange starting is to check for the stationarity of the original variables and
# 4 (130) ³åñÇÉ 2011 47
then test co-integration between them. According to Granger, the ation and the Exchange rate in both countries.
test is valid if the variables are not co-integrated (Granger, 1986).At Stock market in Iran and Armenia are still in a transitory phase. If
first we started with unit root test. these results are also arrived at for more subsequent periods, then
1/ Unit Root Test it may be concluded that Iranian and Armenian stock market are
Empirical studies (for example, Engle and Granger, 1987) have approaching towards informational efficiency at least with respect to
shown that many time series variables are non-stationary or inte- one macroeconomic variable, which is exchange rate.
grated of order 1 (i.e., their changes are stationary). The time series
variables considered in this paper are the stock Index of Tehran
Stock Exchange and Armenia capital market(NAZDAQ OMX) and
two macroeconomic variables namely, exchange rates(for Iran and
Armenia). In order to avoid a spurious regression situation the vari-
ables in a regression model must be stationary or co-integrated.
Therefore, in the first step, we perform unit root tests on these four
time series to investigate whether they are stationary or not. The
Augmented Dickey-Fuller (ADF) unit root test is used for this pur-
If the calculated ADF statistics are less than their critical values
from Fuller’s table, then the null hypothesis (H0) is accepted and the
series are non-stationary or not integrated of order zero.
Usually stock exchange indices are non stationary. In the second
step we estimate co-integration regression using variables having
the same order of integration.
The null hypothesis of non-stationary is rejected if the calculated
ADF statistics is less than the critical value from Fuller’s table. That
means there is a long run stable relationship between the two vari-
ables and causality between them is tested by the error correlation
model. On the other hand, if the null hypothesis of non-stationary is
rejected and the variables are not co-integrated then the standard
Granger causality test is appropriate.
IV. Empirical Results:
As our first step, we have determined the order of integration for
each of the four variables used in the analysis. Using the standard
Augmented Dickey Fuller unit root test analyzed in the earlier sec-
tion, we have tested on levels, zero and first differences of the
series. The results are tabulated in Table 1 and Table2.
As table 2 shows the Dickey Fuller augmented statistic values of
series are smaller than test critical values of series at 1% level, 5% References:
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