• No results found

Causality between stock prices and exchange rates: evidence from india

N/A
N/A
Protected

Academic year: 2020

Share "Causality between stock prices and exchange rates: evidence from india"

Copied!
9
0
0

Loading.... (view fulltext now)

Full text

(1)

CAUSALITY BETWEEN STOCK PRICES AND

EXCHANGE RATES: EVIDENCE FROM INDIA

Dr. Neeru Gupta Assistant professor Department of Management Maharaja Agrasen Institute of Technology

Abstract:This paper studies the long term end short term interaction between stock prices and exchange rates in India. The daily exchange rate of US dollar in terms of Indian Rupee and daily closing price of S& P BSE Sensex for the year 2011 to 2017 has been taken. It is found that both the series are non-stationary and integrated of order one. Engel-Granger co-integration test is performed to find the long term association between exchange rate and stock index. The study shows that there is no long term association between two time series. Granger causality test depicts that only short term interaction has been found but that is only unidirectional i.e. Exchange rate cause movement in stock market but stock market doesn’t cause any movement in exchange rate.

Key words: Engel-Granger co-integration test, exchange rate, Granger causality test, stock price, unit-root test.

1. INTRODUCTION

Financial market plays a very important role in the development of a country. It helps in determining the quantum of total capital inflow and outflow, total accumulated fund, stock of capital etc. which further helps to economist in formulating various economic policies. Various components of financial market such as stock market, foreign exchange market, foreign institutional investors, mutual funds, commodity market are seems to be linked with one or other. Generally, it is assumed that movement in one market cause movement in another market. One market can have a predictive power to forecast another market.

(2)

S & P BSE Sensex is the oldest stock exchange in Asia is considered as a benchmark of stock prices movement in India. It is a market capitalization-weighted' index of 30 large and financially sound companies. Various economist and investors use Sensex data to form their economic policies and investment decision respectively. Economist believe that recent surge in Sensex (Sensex has been scaled 30,000 mark in April) have been occurred because of either currency overvalued or large of fund flowing in Indian equity market.

The interaction between stock prices and exchange rate has been defined through a channel. The impact of exchange rate on stock price is defined as, if there is any fluctuation in exchange rate, it will effect firm’s value that will lead to change in competitiveness of firm and therefore, the value of firm’s assets and liability denominated in foreign currency will change , results in effect on profitability and value of equity.

Similarly, change in value of stock price will lead to change in exchange rate. via portfolio adjustment. If stock price goes upward, inflow of foreign capital will increase, leading to domestic currency appreciation and if stock price goes down, the domestic investor’s wealth will decrease, leading to demand for money and low interest rate, causing capital outflow. And the capital outflow will result in domestic currency depreciation.

Many empirical studies have been conducted by researchers to identify this relationship between stock price and exchange rate but the results are diverse. The Linkage between stock price and exchange rate varies across economies because of various economic factors such as exchange rate regime, trade size, degree of capital control and size of equity market (Shiunpan and fok, 2007).

(3)

2. LITERATURE REVIEW

The linkage between stock price and exchange rate varies across economies. Developed and developing countries shows diverse results on inter-linkage between stock market and exchange rates. This is because of various economic factors such as trade size, capital flow, size of equity market etc.(Shiun-Pan and Chi-Wing Fok,2007). Some studies say that there is a strong linkage between two markets while few other studies say there is no linkage between two markets. In the earliest study of seven advanced markets and eight emerging markets Ajayi et al(1998) report that stock and currency markets are well integrated in advanced countries where exchange rate responding to innovations in stock markets, while in emerging markets the result of causal relationship is mixed. Granger et al(2000) says that in most of the Asian countries like Hongkong, Singapor, Thailand and Taiwan, there is a strong feedback relation, whereas, in few countries like Indonasia and Japan, there is no recognizable pattern of relationship between stock price and exchange rate. In South Koria, exchange rate leads stock prices while in Phillipins stock prices lead exchange rate with negative correlation. They also found that there is no long term association between two markets. Symth and Nanda (2003) studied four south Asian Markets i.e. India, Sri Lanka, Bangladesh and Pakistan and confirmed that there is no long term relationship between two markets in any of four countries. There is a unidirectional causality from exchange rate to stock price in India and Sri Lanka only. In Bangladesh and Pakistan both markets work independently. In Brazil market also the unidirectional causality is found but from stock price to exchange rate (Benjamin and Tabak,2006). Rahman and Uddin(2009)studied three south Asian markets i.e. Bangladesh, India and Pakistan and reported that there is no long term and short term association between stock price and exchange rate while Abdalla and Murinde (2010) studied the emerging financial market such as India, Koria, Pakistan and Phillipins and found that except Phillipins all markets have unidirectional causality from exchange rate to stock prices. Tsai (2012) come up with a very interesting point in his study of Asian financial market. He found that relationship is more obvious when exchange rate is extremely high & low. He used a quantile regression model to observe this phenomenon.

(4)

often cause currency depreciation in Itly and Japan. In US both markets move independently. Oguzhan and Demirhan (2009) examine this relationship in Turkey market by taking various sectorial indices and conclude that there is a bidirectional causal relationship between exchange rates and stock prices.

Indian experience

Smith and Nanda (2003) find the unidirectional causality from exchange rate to stock price in India. Rahman and Uddin (2009) reported in his study of data for the year 2003-2008 that there is no long term and short term association between stock price and exchange rate. Sundram (2009) examined the data from 1994 to 2008 and found that there is no long run equilibrium relationship between stock return and exchange rate in India. Moreover there is no short causal relationship between two. National stock exchange index is used to find relationship. Abdalla and Murinde (2010) analysed the data from 1985-2001 and, than from 1994-2007 and found that Indian market has unidirectional causality from exchange rate to stock prices. From this review it is evident that in most of the studies Indian financial market shows unidirectional causality from exchange rate to stock prices.

3. METHODOLOGY

Daily closing price of BSE Sensex index and exchange rate of dollar with Indian rupee for the time period 1 April 2011 to 31st march 2017 are obtained from the BSE website and exchange rate database

available at www.investing.com. Since, stock market in India is closed on some gazetted holidays (Diwali, Holi, 2ndOctober, 15th August, 26thJanuary etc.) and exchange rate are continue to fluctuate as it

is an international phenomenon, therefore, both time series are refined to form symmetry by eliminating data of these days. Finally, total 1480 observations are recorded for analysis.

Firstly, the correlation analysis is done to determine the degree of correlation between exchange rates and stock prices. As we know that existence of correlation means not necessarily causation so, to determine the causality between exchange rate and stock prices, causality test is conducted, The methodology used in the study is based on Granger(1969) because granger’s test are superior than other test of causality (Geweke, Meese, & Dext,1983). The two essential steps for granger causality test i.e. stationarity and co-integration between variables has been carried out. Augmented-Dickey-Fuller (ADF) unit root test is used to test the stationary of time series and their order of integration using both trend and intercept. The ADF model is given as follow:

q

X

t

X

X

(5)

Where Xt is the variable tested for unit root; Δ is the first difference operator; α is the constant term; t is a time trend; and q is the lag number, ɛ is the error term. SIC(Schwarth Information Criteria) is used to decide the number of lags selected.

In unit root test null hypothesis is (H0): β=0; implying that Xt has unit root and alternate hypothesis (H1): Xt is stationary (not unit root). Null hypothesis is rejected if calculated test statistics are greater than critical values. If the series has unit root at level than first difference of the series can be used to perform unit root test. In this case, the variables are said to be integrated of order 1. When the series are co-integrated of order 1 than Johansen’s co integration test is used to find if any co-co-integrated vector or long term association among variables exists or not.

This test is based on two statistics i.e. Trace test and Maximum Eigen Value test. The null hypothesis in Trace test is that the number of distinct integrated vectors is less than or equal to number of co-integration relations( r) as against r+1 co-co-integration vectors.. The maximum eigen value test has the null hypothesis that there are exactly r co-integrating vectors against the alternative of r+1 co-integrating vectors.

The null hypothesis for co-integration test is H0: There is no Co-integration between two variable. If the p-value is less than 5% than null hypothesis is rejected, otherwise accepted.

At the end, Granger causality test has been used to find direction of short term causation between variables. This test is used basically to determine whether one time series is useful in forecasting another series or not. Granger causality test is based on Lag augmented -Vector autoregression (LA-VAR) approach. The Akaike Information Criteria is used to decide optimum lag length for applying granger causality test. The following equations are used :

           q i q

i i t i t

i t i

t SP ER e

SP

1 1 1 2 1

0

………(2)

   

p i p

i i t i t t

i

t

ER

SP

e

ER

1 1 1 1 2 2

0

………(3)

(6)

H01:B2i=0, means that exchange rate doesn’t granger cause stock price.

H02: γ2i=0, means that stock price doesn’t granger cause exchange rate.

In order to test null hypothesis F-statistics is used. If the p-value is less than 0.05, than null hypothesis is rejected and otherwise accepted.

4.

EMPIRICAL ANALYSIS

There is a high degree of positive and significant correlation(0.787) between exchange rate and stock market price. Since, we know that existence of correlation doesn’t means causation necessarily, so, granger causality test is performed. Granger causality test requires that time series should be stationary. ADF Unit root test is performed to check stationarity of stock price and exchange rate data. A time series is said to be stationary if its probability distribution remain unchanged over the time period. Here, in table-1 the null hypothesis is accepted for BSE and Exchange rate as ADF test statistic is lower than critical value at level. It means both the series has unit root. Then, ADF unit root is performed at first difference. It is shown in table-1 that test statistics is much higher than critical value. Hence, hypothesis is rejected. The two series has no unit root now and integrated of order one. The results of unit root are compiled and presented in table-1

Table-1: Results of Unit Root Test

BSE Exchange Rate

At Level DifferenceAt First At Level DifferenceAt First

t-Statistic Prob. Statistict- Prob* Statistict- Prob. Statistict- Prob ADF -2.8308 0.1863 -35.579 0.0000 -35.579 0.0000 -29.986 0.0000

1% level -3.9643 -3.9643 -3.9643 -3.9643 5% level -3.4129 -3.4129 -3.4129 -3.4129 10% level -3.1284 -3.1284 -3.1284 -3.1284

Source: Author’s Compilation

So here, we can say that stock price and exchange rate are stationary at first difference and integrated of order 1 i.e. I(1).

(7)

as p value is greater than 0.05. Thus, there is no integration in both the cases.there is no long term co-movement between stock price and exchange rate and none of the variable can be predicted on the basis of past value of another variable

.

Table-2: Results of Co-integration Test

Hypothesied

no of CE TraceStatistic Criticalvalue Prob.value Max.value eigen Criticalvalue Prob.

None 11.8196 15.49 0.1658 10.1669 14.26 0.2012 At most 1 1.65291 3.84 0.1984 1.6529 3.84 0.1986

Source: Complied by Author

In the absence of any co-integration between series the author moves to Granger Causality test to find any causal relationship between stock prices and exchange rates. After applying Granger Causality test in Eviews, the results are compiled in table-3

The optimum lag length used is 3 as determined by Akaike information criteria (AIC).

Table-3: Causal Relationship Between Stock Price and Exchange Rate.

Null hypothesis F-Value P-value Causal

relationship

Exchange rate doesn’t granger cause stock price (H0)

7.07837 0.0001 Yes

Stock price doesn’t Granger cause Exchange Rate(H0)

0.75598 0.5189 No

Source: Author’s compilation

The first null hypothesis i.e. Exchange rate doesn’t granger cause stock price is rejected here as p value is less than 0.05 and the second null hypothesis i.e. Stock price doesn’t Granger cause Exchange Rate is accepted as the p value is more than 0.05. It means in India exchange rate cause movement is stock price but stock price doesn’t cause any movement in exchange rate during the period 2011-2017.

5.

CONCLUSION

(8)

exchange rate cause movement in stock price but stock prices does not cause any movement in exchange rate. The two necessary conditions of granger causality test i.e. stationarity and co-integration among variables, are tested using unit root test and Johansen’s co-integration test. It is found that both the series are stationary at first difference and there is no long term association between stock price and exchange rate in India as aligned with previous research in India and in foreign country. The two financial markets share no common trend in long run. Hence, it is concluded that both the markets are related and exchange rate has the predictive power to forecast stock price in short run only.

One of the implications of this research is that investors can use this relationship between stock price and exchange rate to hedge risk in equity market against fluctuation in currency movements. Moreover, the government should be cautious in their implementation of exchange rate policies, given that such policies have ramification on their stock market.

REFERENCE

[1] Rahman, L. and Uddin, J., “Dynamic Relationship between Stock Prices and Exchange Rates: Evidence from Three South Asian Countries,International Business Research, 2(2),2009, pp. 167-174.

[2] Nieha, C.C. and Leeb, C.F., “Dynamic relationship between stock prices and exchange rates for G-7 countries”, The Quarterly Review of Economics and Finance ,41, 2001, pp. 477–490.

[3] Phylaktis, K. and Ravazzolo, F., “Stock prices and exchange rate dynamics”,Journal of International Money and Finance, 24, 2005, pp. 1031-1053.

[4] Aydemir, O. and Demirhan, E., “The Relationship between Stock Prices and Exchange RatesEvidence from Turkey”,International Research Journal of Finance and Economics,

23, 2009, pp.207-215

[5] Foresti , P., “Testing for Granger causality between stock prices and economic growth”,

Online athttp://mpra.ub.uni-muenchen.de/2962/, MPRA Paper No. 2962, posted 26. April 2007, pp1-10

[6] Kumar Sundaram, “Investigating causal relationship between stock return with respect to exchange rate and FII: evidence from India”, Online athttp://mpra.ub.uni-muenchen.de/15793/,

(9)

[7] Ajayi, A.R. and Mougoue, M., “on the dynamic relation between stock prices and exchange rates,The Journal of Financial Research, 19(2),1996, pp.193-207

[8] Ajayi, A. R. at el, “on the relationship between stock returns and exchange rates: tests of grangercausality”.Global Finance Journal. 9(2), pp 241-251.

[9] Tabak, B., “The Dynamic Relationship between Stock Prices and Exchange Rates:Evidence from Brazil”,Banco Central Do Brasil, working paper, 2009, pp.1-35

[10] Tsai, “The relationship between stock price index and exchange rate in Asian markets: A quantile regression approach”, Journal of International Financial Markets, Institutions and Money, 22(3), July 2012, pp. 609-621

[11] ShiunPan, WingFok, AngelaLiu, “Dynamic linkages between exchange rates and stock prices: Evidence from East Asian markets”,International Review of Economics & Finance,16(4),2007, pp 503-520

[12] Christopher and Wenchi Kao, G., “On exchange rate changes and stock price reactions,” Journal of Business Finance and accounting, 17(3),1990.

References

Related documents

I thank the following museum staff for providing information on specimens in their collections: Sylke Frahnert of the Museum für Naturkunde (Berlin), Hein van Grouw of the

Using the full-wave solvers based on the MoM (TET, 2016; Altair, 2016) the input impedances of the loop antenna and its electric dipole ver- sion, enclosed by a resonator as seen

By identifying best practice 1 elements of workforce planning across three components—

Gains in mean species richness within the River Wey produced by the barrier optimization model are

In the augmented data sets (with a larger proportion of spike-in regions), HGMM did not fail for any array. using the top 1% of the data to estimate alternative distri- bution and

The US government has agreed to forgive six debt claims (all foreign assistance loans from 1974-76) owed by Indonesia to the US Agency for International

This fig- ure is significantly lower than the average cost of such programs and, as a result, participants may need a high level of financial support to supplement the investment

• Long service intervals and low operating costs due to a fuel-efficient design optimized for specific operating condition.. • More comfortable vibration characteristics due