Abstract The economy of a nationis driven by a robust securities market. The growth of a nation is indubitablybased on the strength and stability of its secondary market systems andintermediaries. The mobilization of funds and its flow into diverse sectors of theeconomy in a regulated manner signifies dynamism and progress. Egypt as aneconomy has been in a trajectory of progress right since the establishment ofits Secondary Market and its Index EGX 30 in 2009. The Egyptian Pound (EGP) hasbeen at the centre of attention of Egyptian monetary policy due to undue stresson it for quite some time. The Central Bank of Egypt (CBE) has been in theforefront to stabilize the Pound from time to time. The changing economicenvironment of a country has an indelible impact on its growth and development.Any change in the foreign exchange market is sure to leave its footprint in thesecondary market.

An intrigue that is plaguing all researchers in the field ofForeign Exchange Management, is the query about the relationship betweenSecondary Market and Forex Market. Many an investigation has been done to seeif there is a significant relation between Stock Prices and Exchange Rates. Therecent transition in Egyptian Economy to float its currency and its efforts tostabilize the Pound has attracted researchers to find out the effects of such amove. The relationship between securities market and forex market has to begiven a serious thought before any decision in the forex market policy andregulation. Hence this study analyses the dynamic relationship between stockmarket and exchange rate in Egypt using Engle-Granger cointegration method. Keywords: ChangingEconomic Environment; Egyptian Economy; Exchange Rate; Stock Prices;Cointegration; Granger Causality; Econometrics 1.

IntroductionEgyptian Economy standstall in the African Continent. However the Exchange rate instability in thelast year is a matter of Economic concern. The economy went in through adynamic change in its policies and processes. There were sudden strategies anddecisions by the government that took the Egyptians through a vortex of change.The role of CapitalMarket in the development of a nation cannot undermined. Exchange ratemovements have a significant role in determining the direction of growth of anycountry. These two important economic variables have been at the forefront ofeconomic observation by researchers in all countries. This dynamic relationshiphas been utilized by policy makers, due to their predictive efficacy.

The recent ExchangeRate crisis in a few nations, have reiterated that the relationship betweenstock prices and exchange rates is a matter of contention even today. Empiricalinvestigation into their relationship might lead to meaningful discoveries.This paper seeks to study the dynamic relationship between stock prices andexchange rate in Egypt. The context of the study is the instability of the EgyptianPound (EGP). Egyptian Stock Index (EGX) has seen its own share of ups anddowns. Firstly unit root tests were employed to test stationarity of the givenseries.

Secondly Cointegration was tested using and Engle – Granger’s (1987)two – step methodology. A long-run relationship between stock market and forexmarket in Egypt was observed in this study. A unidirectional causality fromforex market to stock market was also witnessed.

2. Literature ReviewAcademic research hasbeen intrigued by the relation between exchange rates and stock prices. Thisinterest spiked ever since nations have moved towards flexible exchange ratesystem. The researches have evolved around two theoretical models:flow-oriented and stock-oriented.

The flow oriented models, reiterate that thestock prices and exchange rates are positively related since, exchange rate isdetermined by a country’s current account and trade balance (Dornbush andFisher, 1980). While the stock-oriented models, hold that the stock prices pushup interest rates and subsequently have a downward pressure on exchange ratesince, capital account determines exchange rates (Branson, 1983, Gavin, 1989). Few researches haveindicated a relation between exchange rates and stock prices. Bahmani – Oskooe &Sohrabian (1992) found a bi-directional causality, even though there was nolong-run relation using Granger Concept of Causality, Akaike’s final predictionerror conjecture and Chow Test.

Granger and others (2000) applied unit root andcointegration models to determine the appropriate Granger causality relationbetween stock prices and exchange rates during Asian crisis. The authors foundpositive correlations between exchange rates and stock prices from the data ofJapan and Thailand. Whereas the data of Taiwan indicated negative correlation.Ramaswamy and Yeung (2005) considered the causality between stock markets andexchange rates in nine east Asian economies and found that the direction ofcausality demonstrated a hit-and-run behaviour and switched according to thelength of the period. Alagidede and others (2010) conducted three variations ofGranger causality test and found out causality from exchange rates to stockprices for Canada, Switzerland and UK.

A weak causality in the other directionwas found only for Switzerland. Causality was observed from stock prices toexchange rates in Japan. Nieh and Lee (2001) found lack of long-runrelationship between the stock prices and exchange rates.There is not muchempirical observation of the changing dynamics of the financial markets inEgypt. Thus this study explores the dynamic relationship between stock pricesand exchange rate in Eygpt. 3. Data and MethodsStock prices datacomprise of EGX 30 and Exchange rate data comprises of USD/EGP.

The data havebeen collected from www.investing.com. The period of data collection is from2009 January to 2017 December. The year 2009 was chosen since EGX 30 wasstarted that year. All analysis was carried outusing GRETL software.3.1.

Unit Root TestThe Unit Root Test ofDickey and Fuller (1981) has been employed. It is used to ensure that the dataof a time series variable is non-stationary using an auto-regressive model.This test has been deployed to ensure that data is stationary and ensuring thatall variables are I (1) as variables that are I (0) indicate an automaticlong-run equilibrium correlation. The Augmented DickeyFuller (ADF) Unit Root Test consists of estimating the following regression: ?Yt= ?1 + ?2t + ? Yt-1 + ?i t-1 +?tThe null of non-stationarity hypothesis is statedthus:H0: A unitroot ‘or’ non-stationarity ‘or’ ? = 0H1: No unitroot ‘or’ stationarity ‘or’ ? < 0, since ? = ? – 1The unit root testswere carried out on the stock index (EGX) and exchange rate (EGP). Then theseries were tested for unit roots at the level series. First difference oflevel series were obtained using the following equation: x = x – x (1)3.

2. Engle – Granger Two-step CointegrationTestEngle-GrangerCointegration Technique (1987) has been used to estimate the long-runequilibrium between Stock Prices and Exchange Rate.The cointegrationbetween EGX (Stock Price) as dependent variable with EGP (Exchange rate) forEygpt was done after ADF unit root tests of the two series. The Cointegrationregression is given as:Yt= ?1 + ?2 Z t + utEGXt= ?1 + ?2 EGP t + ut Following this theresiduals, ut, are saved from the cointegrating equation andtested using ADF to see if they are I(0) under the following hypotheses:H0:A unit root in the cointegrating regression residuals, ?t ~ I(0)H1:No unit root in the cointegrating regression residuals, ?t ~ I(0)When the residuals ofcointegrating regression are I(0), it indicates stationarity and the null wouldbe rejected. Thus we can conclude that there is a cointegration in theregression, where the residuals of both EGX and EGP are stationary.The next step involvesthe estimation of the Error Correction Model (ECM) the short-term model usingthe residuals, ?t.?t = EGXt ? ?1? ?2EGP ? ?3tEGXt = ?0 +?1EGPt + ?2ut?1 + ?t 3.3 GrangerCausalityGranger Causality testwas conducted to see if there is any predictive causality between the twovariables EGX and EGP.

The test involves estimating the following pair ofregressions: EGXt = iEGPt-1 + i EGXt-1+ u1t EGPt = IEGPt-1 + i EGXt-1+ u2t 3. ResultsThe Engle-GrangerCointegration methodology stipulates that to examine the long run relationshipbetween two variables, they both have to be integrated of the same order. Hencewe need to find out if the variables in the study – EGX and EGP are integratedof the same order. An Augmented DickeyFuller (ADF) test was employed to test for unit root in the level series of EGPand EGX. It was found that the level series, i.

e. EGX I(0) and EGP I(0) arenon-stationary. Next the ADF test was run on the two series after differencingthem. It was found that the two series – EGX and EGP are integrated of theorder 1, i.e. EGX I(1) and EGP I(1). Therefore, the basic condition forcointegration is satisfied. The results are presented in Table 1.

Table1. Test for Unit Root using Augmented Dickey Fuller Test Series With Constant With Constant & Trend Stationary/ Non-stationary t statistic p-value t statistic p-value EGX (level) 0.208605 0.972 -0.932747 0.9477 Non-stationary EGX (Differenced) -10.1695 <0.001** -10.

2296 <0.001** Stationary EGP (level) -0.0919912 0.946 -1.

55178 0.8052 Non-stationary EGP (Differenced) -10.8838 <0.001** -11.0217 <0.

001** Stationary **Significant at 1% levelAs seen from the aboveresults, the ADF test revealed that both EGX and EGP level series were non-stationarysince the p-value was not significant at 1% level. The Null Hypothesis was accepted.After differencing theEGX and EGP, it was observed through the ADF test that the integrated seriesI(1) were stationary, since p-value was significant at 1% level and the NullHypothesis was rejected.

The criteria for aCo-integration relationship as laid down by Engle and Granger has beenfulfilled. Next it was examined whether there was a co-integrating relationbetween EGX and EGP. The estimates of thelong run relationship – (Cointegrating regression):EGX = 2324.38 + 629.912 EGP + utt =7.740 18.

59pvalue = <0.0001 <0.0001 Where ut is theresidual from the long run Cointegrating regression as depicted in Fig 1. Fig.1.

Residual Plot of the Cointegrating RegressionIn order to find out if the variables EGX and EGP have long runrelationship, the residuals obtained from the above relationship was tested forstationarity using ADF test shown in Table 2. Table2. Testing for stationarity of residuals using Augmented Dickey Fuller Test Series With Constant With Constant & Trend Stationary/Non-stationary t statistic p-value t statistic p-value ut -3.5575 0.008275** -3.58477 0.

03592* Stationary ** Significantat 1% level* Significant at 5% level It was observed throughthe ADF test that the residuals were stationary, since p-value was significantat 5% level. Therefore, the Null Hypothesis was rejected. It could be concludedthat there EGX and EGP have a cointegrating relationship. It has been observedthat EGX and EGP are cointegrated. There is a long-term relationship orequilibrium between Egyptian Stock Prices and Egyptian Pound exchange rate. Itimplies that there may be disequilibrium in the short run. The error term inthe above equation may be considered as “equilibrium error.

” This error termcan be used to tie the short-term behaviour of EGX with its long-term value.The Error Correction Mechanism (ECM ) was first used by Sargan (1984) and laterpopularised by Engle and Granger. The Granger Representation Theorem statesthat if two variables Y and X are cointegrated then the relationship betweenthe two can be expressed as ECM. The ECM equation forthe study is given below:d_EGX = 98.25 + 49.64 d_ EGP – 0.

083 ut-1t =1.64 0.75 – 1.73pvalue = 0.104 0.

45 0.087 The test for causalitywas done using Granger Causality test. The null hypothesis tested was thatStock Prices do not (Granger) cause Exchange Rate and vice-versa.

The resultsare shown in Table 3Table3. Causality between EGX and EGP Direction of causality Number of lags F value Decsion EGX EGP 2 2.064 (0.

1323) Accepted EGP EGX 2 23.878 (< 0.0001) Rejected From the above it isevident that Stock Prices (EGX) does not (Granger) cause Exchange rate (EGP).However it is proved that Exchange Rate (EGP) does (Granger) cause Stock Prices(EGX) in the context of Egypt. 4. ConclusionA change in onemacroeconomic variable is bound to impact the other variables as well.

Anychange in the foreign exchange market is sure to affect the secondary market. Ananalysis was undertaken to find out the dynamic relationship between stockprices and exchange rates with reference to Egypt. Utilising the data ofEgyptian Stock Index (EGX) and the Exchange rate of the EGP/USD, from January2009 to December 2017, it has been observed that there is a long-termequilibrium between stock prices and exchange rate in Egypt, since theconditions of Cointegration are fulfilled.

The short-term equilibrium betweenthe two variables is however is not significant. There is unidirectionalGranger causality. It is found that Exchange rate (EGP) has a causal effect onthe Stock Prices (EGX). The policy implicationis that the government of a country should seriously consider the impact theforeign exchange market has on the secondary market before any decision toalter fundamentals in the foreign exchange market. Any adjustment of theexchange rate has an altercating effect on the entire economy. ReferencesAlagidedeP.

, Panagiotidis, T. & Zhang, X. (2010). Causal relationship between stockprices and exchange rates. StirlingEconomic Discussion Paper, 2010-05. Retrieved from https://www.stir.

ac.uk/research/hub/publication/233.Bahmani-Oskooe,M. & Sohrabian, A. (1992). Stock prices and the effective exchange rate ofthe dollar. Applied Economics, 24(4),459-465.

Branson,W.H. (1983) Macroeconomic determinants of real exchange rate risk. In Herring,R.

J. (Ed.), Managing Foreign ExchangeRate Risk. Cambridge: Cambridge University Press.Dickey,D.A. & Fuller, W.A.

(1981). Likelihood ratio statistics for autoregressivetime series with a unit root. Econometrica,49(4), 1057-1073. Dornbusch,R. & Fisher, S. (1980).

Exchange rates and the current account. American Economic Review, 70, 960-97. Retrievedfrom http://www.

mit.edu/~14.54/handouts/dornbusch80.

pdfEngle,R. & Granger, C. (1987). Co-integration and error correctionrepresentation, estimation and testing. Econometrica,55, 251-267. Retrieved from Stable URL:http://www.jstor.

org/stable/1913236.Gavin,M. (1989). The stock market and exchange rate dynamics. Journal of International Money and Finance, 8, 181-200. Retrievedfrom https://www.sciencedirect.com/science/article/pii/0261560689900223Granger,C.

W. J., Huang, B-N., & Yang, C.

W. (2000). “A bivariate causality betweenstock prices and exchange rates: Evidence from recent Asian flu.” The Quarterly Review of Economics andFinance 40 (3) : 337-354. Retrieved from https://www.sciencedirect.

com/ science/article/pii/S1062976900000429.Gujarati, D. N.,& Porter, D.

C. (2009). Basic econometrics (5th ed.

). Boston: McGraw-Hill.Nieh,C-C. & Lee, C-F. (2001). Dynamic relationship between stock prices andexchange rates for G-7 countries. TheQuarterly Review of Economics and Finance 41, 477–490.Ramasamy,B.

& Yeung, M.C.H. (2005). The causality between stock returns and exchangerates: revisited.

Australian EconomicPapers, 44, 162-169. doi:10.1111/j.1467-8454.2005.00257.x.