The impact of domestic gold price on stock price indices-An empirical study of Indian stock exchanges
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Universal Journal of Marketing and Business Research (ISSN: 2315-5000) Vol. 2(2) pp. 035-043, May, 2013
Available online http://www.universalresearchjournals.org/ujmbr
Copyright © 2013 Transnational Research Journals
Full Length Research Paper
The impact of domestic gold price on stock price
indices-An empirical study of Indian stock exchanges
Amalendu Bhunia1 and Somnath Mukhuti2
1
Associate Professor, Department of Commerce, University of Kalyani, West Bengal, India
2
Research Scholar, Department. of Commerce, CMJ University Meghalaya
Accepted 29 April, 2013
The present research paper examines the impact of domestic gold price on stock price indices in India
for the period for the period from 2nd January, 1991 to 10th August, 2012 using appropriate statistics,
unit root test and Granger causality test. The domestic gold price in India is eternally escalating in
consequence of its intense domestic demand on account of protection, liquidity along with spreader
portfolio. It give the impression of being at the remarkable data brings to the plane that when the stock
market crumples or when the dollar worsens, gold prolongs to be a safe haven investment because
gold prices increase in such situations. The study is based on secondary data obtained from World
Gold Council database and BSE and NSE database. Unit root test indicates that time series are not
stationary at levels and the selected time series are stationary at 1st difference. Granger causality test
illustrate that no causality exists between nifty and gold price, gold price and sensex and nifty and
sensex and bidirectional causality exists between gold price and nifty, sensex and gold price and
sensex and nifty.
Keywords: Gold Price, Sensex, Nifty, India, Correlation, Multiple regression, ADF and PP unit root test,
Granger causality test
INTRODUCTION
The study of the capital market of a country in terms of a explores the impact of domestic gold price on stock price
wide range of macro-economic and financial variables indices in India. In other words, the plan of this paper is to
has been the area under discussion of many researches observe the causal relationships between the gold price
during the last two decades. Empirical studies make and stock market in India.
known that when financial deregulation comes to pass,
the stock markets of a country become more sensitive to
both domestic and peripheral factors and one of these Problem statement
factors is the price of gold. Historical practices give an
idea about that in countries in period of stock market The global economic disorder is expected to goad
slump, the gold for perpetuity trends higher (Neda improbability in gold prices that has already made it a
Bashiri, 2011). The domestic gold price in India is dodgy asset for investors. Investment demand will return
continually ever-increasing on account of its heavy no more than when there are a few transparencies. Gold
domestic demand as a consequence of security, liquidity prices have been on the mount for the past several
and diversified portfolio. A look at the historic data brings months and the hot-blooded state of affairs in global
to the surface that when the stock market collapses or markets had helped the precious metal to gain
when the dollar deteriorates, gold continues to be a safe handsomely. Conversely, the coming days will see huge
haven investment because gold prices rise in such funds moving from gold to sensex and nifty. The
circumstances (Gaur and Bansal, 2010). This paper domestic gold prices have crowned in India for the first
time, breaks all time record. In view of that most stockists
are looking to smash their share of the precious metal, in
consequence pushing the prices skywards and no
*Corresponding author Email: bhunia.amalendu@gmail.com036 Univers. J. Mark. Bus. Res.
immediate reinforcement seems to be in sight for the gold H1: There is a significant relationship between gold prices
buyer. Gold prices usually rise when outlooks on the and Indian stock price indices.
economy and the financial markets are bearish or there is
uncertainty over future trends. Gold is a precious, highly
liquid, financial instrument and an important asset class Hypothesis 2
that possesses the characteristics of both commodity and
currency, but its tangibility makes it relatively different H0: The selected variables are not non-stationary
from paper assets such as stocks (Steven W. Sumner et variables (there is unit root);
al, 2012). Many researchers have been done the causal H1: The selected variables are non-stationary variables
relationships among stock price index and gold price in (there is unit root).
developed and developing countries. Empirical results
give an idea about that gold price can deeply concern the
stock market (Mahmood Yahyazadehfar and Ahmad Hypothesis 3
Babaie, 2012, taken from Bhunia, A, 2013).
H0: There is no causal relationship between the selected
variables;
The objective of this study H1: There is a significant causal relationship between the
selected variables.
The plan of the paper was to establish, investigate and
assess the impact of domestic gold price on stock price
indices of BSE (SENSEX) and NSE (NIFTY). In this way, Review of Literatures
this paper would attempt to attain the only objective of:
Assess the causal relationship between domestic gold There are diverse studies, technical papers and articles
price & sensex and gold price & nifty. covenanting in aspects that influence stock market prices
at the global level such as:
Rabi N. Mishra and G. Jagan Mohan, 2012, in their study
Importance of the study entitled “Gold Prices and Financial Stability in India”
proved that domestic and international gold prices are
Stock market is distinguished as an extremely closely interlinked. The paper also concludes that
momentous factor of the financial sector of any economy. implications of correction in gold prices on the Indian
Besides, it plays an imperative role in the mobilization of financial markets are likely to be muted.
capital in India. According to Mahmood Yahyazadehfar and Ahmad
The importance of this paper curtails from the critical Babaie (2012), the relationship between nominal interest
position of the Indian financial market for the following rate and gold price with stock price are negative. Also,
grounds: the results of Impulse-Response Functions shocks show
(i) Indian financial market plays an important role in that stock price reaction to the shocks is very fast.
collecting money and encouraging investments, Thai-Ha Le and Youngho Chang (2011) made a study on
accordingly this paper was devised to search the impact “Dynamic Relationships between the Price of Oil, Gold
of gold price in India on stock market prices in BSE and and Financial Variables in Japan: A Bounds Testing
NSE. Approach” and they confirmed that the price of gold and
(ii) The importance of the paper gives a belief to stock, among others, can help form expectations of
domestic as well as foreign investors. higher inflation over time. In the short run, only gold price
(iii) The results of this paper will provide investors helps impacts the interest rate in Japan. Overall the findings of
to compose their individual proper investment decisions. this study could benefit both the Japanese monetary
authority and investors who hold the Japanese yen in
their portfolios.
Hypotheses of the Study Yen-Hsien Lee, Ya-Ling Huang & Hao-Jang Yang (2012)
examined the asymmetric long-run relationship between
This paper aspires to study the change in daily gold price crude oil and gold futures. This study employs the
and its impact on stock price indices based on the momentum threshold error-correction model with
following hypotheses: generalized autoregressive conditional heteroskedasticity
to investigate asymmetric cointegration and causal
relationships between West Texas Intermediate Crude
Hypothesis 1 Oil and gold prices in the futures market. From the study
it is clear that an asymmetric long-run adjustment exists
H0: There is no relationship between gold prices and between gold and oil. Furthermore, the causality
Indian stock price indices;Bhunia and Mukhuti 037
relationship shows that West Texas Intermediate Crude Perron (PP-1988) test methods have been used in the
Oil plays a dominant role. study. The series is not stationary if the calculated value
Graham Smith (2001) empirically investigated the is bigger than the absolute critical value, then null
relationship between gold prices and stock price indices hypothesis is rejected and series is decided to be
on US market using Unit Root Test, Johansen’s Co stationary [Claire G. Gilmore et al, (2009)].
Integration Test, Vector auto regression and VECM. He H0: Series is stationary
confirmed that The short-run correlation between returns H1: Series is non-stationary
on gold and returns on US stock price indices is small If both sets of data are found I (1) (non-stationary), and
and negative and for some series and time periods if the regression produces a I (0) error term, the equation
insignificantly different from zero. All of the gold prices is said to be co-integrated. On the other, if there are two
and US stock price indices are I(1). Over the period variables, xt and yt, which are both non-stationary in
examined, gold prices and US stock price indices are not levels but stationary in first differences, then xt and yt
cointegrated. Granger causality tests find evidence of would become integrated of order one, I(1), and their
unidirectional causality from US stock returns to returns linear combination should have the form:
on the gold price set in the London morning fixing and the zt = xt - ayt
closing price. However, if there is a I (0) such that zt is also integrated
of order zero, I (0), the linear combination of xt and yt
is said to be stationary and the two variables are
MATERIALS AND METHODS also to be co-integrated (Engle & Granger, 1987 and
Claire G. Gilmore, Brian Lucey Ginette M. McManus,
2005). If two variables are co-integrated, there will be
Sources of data an underlying long-run relationship between them.
The first step in our analysis is to test each series for
The study is based on secondary data obtained from determining the presence of unit roots. This can be done
various appropriate data sources including BSE and NSE by means of the Augmented Dickey Fuller (ADF) test, an
database, World gold council database etc. Besides, the extension of the Dickey and Fuller (1981) method. The
facts, figures and findings advanced in similar earlier ADF test uses a regression of the first differences of the
studies and the government publications are also used to series against the series lagged once, and lagged
supplement the secondary data. difference terms, with optional constant and time trend
terms:
Research design ∆yt = a0 + a1t + γyt-1 + Σbiyt-1 + et
(2)
We have measured daily data encompassing the closing In the equation ∆ is the first-difference operator, a0 is an
indexes of both Bombay Stock Exchange (SENSEX) and intercept, a1t is a linear time trend, et is an error term, and i
National Stock Exchange (NIFTY) and the closing is the number of lagged first-differenced terms such that
domestic gold price index using the sample period et is the white noise. The test for a unit root has the
extents from January 2, 1991 to August 10, 2012; null hypothesis that signifies γ = 0. If the coefficient
however, there are 5199 observations for Sensex & Nifty is significantly different from zero, the hypothesis that yt
and 5639 for gold price. Eviews 7.0 package program contains a unit root is considered as rejected. If the test
have been utilized for coordinating the data and carrying on the level series fails to reject, the ADF
out of econometric analyses. procedure is then applied to the first-differences of the
series. Rejection leads to the conclusion that the series is
Tools used integrated of order one, I (1).
A limitation of the Dickey-Fuller test is its
In the course of analysis in the present study, descriptive assumption that the errors are statistically independent
statistics, correlation statistics, multiple regression and have constant variances. In 1988, Phillips and Perron
14
statistics, ADF and PP unit root test and Granger (PP) generalized the ADF test:
causality test have been used. The uses of all these tools ∆yt = b0 + b1(t - T/2) + b1yt-1Σ ∆yt-1 +µt
at different places have been made in the light of (3)
requirement of analysis. Where, among the variables in the equations ∆Yt=Yt-Y
(t-1); T is the coefficient of total number of observations, t is
Model specification the trend variable, stochastic error terms and the
disturbance term µt is such that E(µt) = 0, but there is no
Unit root test requirement that the disturbance term is serially
uncorrelated or homogeneous. The equation is
A time series is stationary or not or include unit root for estimated by OLS and the t-statistic of the b1 coefficient
which Augmented Dickey-Fuller (ADF-1979) and Phillips- is corrected for serial correlation in µt using the Newey-038 Univers. J. Mark. Bus. Res.
Table 1. Descriptive Statistics
GOLD_PRICE NIFTY SENSEX
Mean 8.806313 7.441530 8.648325
Median 8.492613 7.171926 8.365752
Maximum 10.37824 8.750279 9.952514
Minimum 7.768380 5.724304 6.862873
Std. Dev. 0.646449 0.728326 0.735241
Skewness 0.929154 0.333418 0.330504
Kurtosis 2.733134 1.988496 1.984920
Jarque-Bera 828.1164 317.9648 317.8578
Probability 0.000000 0.000000 0.000000
Observations 5639 5199 5199
1 ,6 00
Series: GOLD_PRICE
1 ,4 00 Sample 1 5639
Observations 5639
1 ,2 00
Mean 8.806313
1 ,0 00 Median 8.492613
Maximum 10.37824
8 00 Minimum 7.768380
Std. Dev. 0.646459
6 00 Skewness 0.929154
Kurtosis 2.733134
4 00
Jarque-Bera 828.1164
2 00
Probability 0.000000
0
8.0 8 .5 9 .0 9.5 1 0.0
800
Series: NIFTY
700 Sample 1 5639
Observations 5199
600
Mean 7.441530
500 Median 7.171926
Maximum 8.750279
400
Minimum 5.724304
Std. Dev. 0.728326
300
Skewness 0.333418
200
Kurtosis 1.988496
100 Jarque-Bera 317.9648
Probability 0.000000
0
5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2 8.4 8.6 8.8
West (1987) procedure for adjusting the standard errors. between the two variables, null hypothesis is rejected if
alpha is more than the probability value (0.05).
Pairwise Granger causality Tests Empirical Results and Analysis
We test for the deficiency of Granger causality by
estimating the following VAR model (Olushina Olawale Descriptive Statistics Result
Awe, 2012):
Yt = a0 + a1Yt-1+…+ apYt-p+ b1Xt-1+…+ bpXt-p+Ut Descriptive statistics contain the portrait of mean,
(4) median, standard deviation; kurtosis, skewness and J-B
Xt = c0 + c1Xt-1+…+ cpXt-p+ d1Yt-1+…+ dpYt-p+Vt statistics with probability for the daily stock price (sensex
(5) and nifty) indices of two stock exchanges and daily gold
Testing H0:b1=b2=…=bp=0 against H1: Not H0 is a test price are exposed in Table 1. It is viewed that mean and
that Xt does not Granger-cause Yt. Similarly, testing H0: standard deviation of the particular series have highest
d1= d2=…= dp=0 against H1: Not H0 is a test that Yt does mean. Positive skewness and kurtosis designates that all
not Granger cause Xt. In case of Granger causality the selected series are less peaked than normal
distribution. The Jarque-Bera statistic with probabilityBhunia and Mukhuti 039
validates that none of the series are normally distributed. substantiates that there is an existence of serial
Graphical representations of descriptive statistics are correlation or multi-collinearity between the independent
given below: variables. At the same time, Durbin-watson statistics
authenticates that the residuals are independent.
Correlation Statistics Result
Unit Root Test Results
Correlation statistics in table-2 point out that sensex and
nifty are positively correlated with gold prices in the However, Granger causal test is indispensable where
period under study. Correlation test result is incredibly there is any underlying impact of gold price on stock price
sturdy however it does not talk about the grounds and indices of BSE and NSE. Granger causal test is
shock. In order to make out an unequivocal delineation of achievable if the series are stationary. In order to
the shock, it is obligatory to execute multiple regression stationarity analysis, unit root tests of Augmented Dickey-
test between the selected variables. Fuller (ADF) and the Phillips-Perron (PP) tests are
conducted with the levels and first differences of each
Multiple Regession Test Results series on the condition that the null hypothesis is non-
stationary, subsequently rejection of the unit root
Table-3 gives an idea about multiple regression test hypothesis prop up stationarity.
results. Multiple regression test has been assessed with Table-4 illustrates the results of unit root test. It
non-stationary data and residuals, at that moment the divulges that time series are not stationary at levels.
regression result turns into forged. Since VIF value Nevertheless, table illustrates that the gold price and BSE040 Univers. J. Mark. Bus. Res.
Table 2. Correlation Statistics
GOLD_PRICE NIFTY SENSEX
GOLD_PRICE 1.000000
NIFTY 0.932312 1.000000
SENSEX 0.928865 0.992889 1.000000
Table 3. Multiple Regression Test
Dependent Variable: GOLD_PRICE
Sample (adjusted): 1 5199 Method: Least Squares
Variable Coefficient Std. Error t-Statistic Prob. VIF
NIFTY 0.506820 0.030034 16.87511 0.0000 17.851
SENSEX 0.159020 0.029751 5.344999 0.0000 17.851
C 3.540772 0.044353 79.83175 0.0000
R-squared 0.869920 Mean dependent var 0.869920
Adjusted R-squared 0.869870 S.D. dependent var 0.869870
S.E. of regression 0.187743 Akaike info criterion 0.187743
Sum squared resid 183.1451 Schwarz criterion 183.1451
Log likelihood 1320.717 Hannan-Quinn criter. 1320.717
F-statistic 17374.35 Durbin-Watson stat 17374.35
Prob(F-statistic) 0.000000 R 0.876287
*Included observations: 5199 after adjustments
Table 4. Unit Root Test Result
ADF
at level at 1st difference
Gold price 0.784469 -77.16061
Nifty -1.6699151 -50.62846
Sensex -1.8443263 -65.98076
Critical values
1% -3.431425 -3.431330
5% -2.861900 -2.861858
10% -2.567004 -2.566982
PP
at level at 1st difference
Gold price 0.830414 -77.14896
Nifty -1.702241 -65.42885
Sensex -1.810382 -65.95544
Graphical representations of unit root test are given below:
and NSE stock price indices are stationary at 1st variance to be heterogeneously distributed and less
difference [1(1)]. Augmented Dickey Fuller unit root dependent. It proves that the selected series are
analysis test discloses that errors have constant variance stationary at 1st difference [1(1)].
and are statistically independent. At the same time Therefore, Granger causal test can be applied on these
Phillip-Perron unit root test is used to ensure the variables, as supported in (Hina Shahzadi and M.N.
stationarity of the data series. This test tolerates the error Chohan, 2012) and Kaliyamoorthy, S and Parithi, SBhunia and Mukhuti 041
Table-5. Pairwise Granger Causality Test Results
Type of
Null Hypothesis Obs F-Statistic Prob. Decision
Causality
No causality
NIFTY ↑ GOLD_PRICE 5197 0.67598 0.5087 DNR H0
Bi-directional
GOLD_PRICE ↑ NIFTY 3.87787 0.0208 Reject H0 causality
Bi-directional
SENSEX ↑ GOLD_PRICE 5197 4.14253 0.0159 Reject H0 causality
No causality
GOLD_PRICE ↑ SENSEX 2.30010 0.1004 DNR H0
Bi-directional
SENSEX ↑ NIFTY 5197 123.853 3.E-53 Reject H0 causality
DNR H0 No causality
NIFTY ↑ SENSEX 1.61115 0.1998
Note: Decision rule: reject H0 if P-value < 0.05, DNR = Do not reject; ↑ = does not Granger cause.
(2012). has been prepared in the present chapter in hunt for the
trend of causation between gold prices and stock price
indices.
Pairwise Granger causality Tests Results Table-5 exposes that no causality and bi-directional
causality subsists between gold price and stock price
The Granger causality test (Awe, O. O, 2012 and Hakan indices under the study. No causality exists between (i)
Güneş, 2005) is a statistical proposition test for Nifty and Gold price, (ii) Gold price and Sensex and (iii)
determining whether one time series is helpful in Nifty and Sensex. Bidirectional causality exists between
forecasting another. The pairwise Granger causality test (i) Gold_Price and Nifty, (ii) Sensex and Gold Price and042 Univers. J. Mark. Bus. Res.
(iii) Sensex and Nifty. It is crucial that the outcome of Pp. 1-17.
causality between the particular indicators does not mean Bashiri N(2011). The Study of Relationship between Stock
that movement in one indicator essentially causes Exchange Index and Gold Price in Iran and Armenia, working
movements in another indicator21. To a great coverage, paper, Yeravan State University, Department of International
Economics Faculty of Economics. 5(131): 49-50.
causality essentially leads to the movements of the time Bhunia A (2013). Cointegration and Causal Relationship
series (Olushina Olawale Awe, 2012). among Crude Price, Domestic Gold Price and Financial
Variables-An Evidence of BSE and NSE. J. Contemp.
Issues in Bus. Res. 2(1):1-10.
CONCLUSION Bilal AR, Noraini BT , Talib Abu (2013). How Gold Prices
Correspond to Stock Index: A Comparative Analysis of Claire
The present research paper examines the impact of GG, Brian LG , McManus M(2005). The Dynamics of Central
domestic gold price on stock price indices in India. The Europe an Equity Market Integration, IIIS Discussion Paper
No. 69:1-24.
principal finale of the empirical results is that the
Boise I(2003). Statistical Reference for Descriptor Module
preferred time series demonstrate non-stationary and Training, online from dev.projectionscentral.com,14.04.2013
that's why afford signal of Granger causality test. and www.greenwichai.com/index.php/hf-essentials/measure-
Descriptive statistics illustrate that all the particular of-risk. http://www.unesco.org
series are more peaked than normal distribution. Dickey DA, Fuller WA (1981). Likelihood Ratio Statistics for
Correlation statistics indicates that BSE and NSE are Auto-Regressive Time Series with a Unit Root. Econometrica.
positively associated with domestic gold prices in the 49: 1057-1072.
period of study. Multiple regression test results are Enders W(1995). Applied econometric time series. New York:
spurious and there is an existence of serial correlation as John Wiley and Sons, Inc.
Engle RF, Granger CWJ(1987). Co-integration and Error
well as multicollinearity. Unit root test result reveals that
Correction: Representation. Estimation and Testing.
the gold price and BSE and NSE stock price indices are Econometrica. 55: 2511-2576.
stationary at 1st difference [1(1)]. Gaur A , Bansal M (2010). A Comparative Study of Gold
Granger causality test illustrates that no causality and Price Movements in Indian and Global Markets. Indian J.
bi-directional causality subsists between gold price and Financ. 4(2):32-37.
stock price indices under the study. No causality exists Gilmore CG, McManus GM, Sharma R(2009). “The Dynamics
between (i) Nifty and Gold price, (ii) Gold price and of Gold Prices, Gold Mining Stock Prices and Stock Market
Sensex and (iii) Nifty and Sensex. Bidirectional causality Prices Comovements”, Research in Applied Economics, 1(1)
exists between (i) Gold_Price and Nifty, (ii) Sensex and E2:1-19.
Gold Price and (iii) Sensex and Nifty, as supported in, Granger CW(1969). Investigating Causal Relation by
Econometric Models and Cross Spectral Methods.
(Olushina Olawale Awe, 2012). Econometrica. 37:424-438.
Gold price persists to increase in India because they Gupta P, Ravi S (Provide year). Commodity Market
are considered gold the safe haven investment as a Inefficiencies and Inflationary Pressures - India’s Economic
financial asset as well as jewellery. World Gold Council Policy Dilemma, International Conference “Risk in
report says that India stands today as the world’s largest Contemporary Economy, XIIIth Edition, Galati, Romania. Pp.
single market for gold consumption. 31-38.
The assessment of the impact of gold price on Indian Hakan G, Fatma G, Merve AZ, Bolor L(2005). Effects of Oil
stock price indices utilized in this study is based on the Price, Interest Rate and Dollar Price of Euro on Gold Price,
financial market indicators. There is a need to widen this Empirical Studies in Social Sciences, 6th International
Student Conference, Izmir University of Economics, Izmir
definition including macro and other market indicators Turkey, 1-11 taken from iibf.ieu.edu.tr/.
(such as crude price, exchange rate, interest rate, Kaliyamoorthy S , Parithi S (2012). Relationship of Gold
inflation) relevant to the impact to facilitate reach our Market and Stock Market: An Analysis, International Journal
destination at more robust empirical analysis. This could of Business and Management Tomorrow. 2(6):1-6.
be a possible area for future research in India (Mishra Karachi Stock Exchange and Bombay Stock Exchange, World
and Mohan, 2012). Applied Sci. J. 21 (4): 485-491.
Lee Y, Huang Y , Yang, H (2012). The Asymmetric Long-Run
Relationship between Crude Oil and Gold Futures (2012).
REFERENCES Global J. Bus. Res. 6(1):9-15, 2012. Available at SSRN:
http://ssrn.com/abstract=1945967
Agarwalla RK (2006). Share Prices and Macroeconomic Mishra RN , Mohan GJ (2012). Gold Prices and Financial
Variables in India: An Approach to Investigate the Stability in India, RBI working paper series, Department Of
Relationship between Stock Markets and Economic Growth, Economic And Policy Research. 2:1-16.
project report, working paper, Business Systems and Mishra RN, Mohan GJ (2012). Gold Prices and Financial
Cybernetics Centre, Tata Consultancy Services Limited. Pp. Stability in India, RBI working paper series, Department Of
1-20. Economic And Policy Research. 2:1-16.
Awe OO(2012). On Pairwise Granger causality Modelling and Newey WK, West KC (1987). A simple positive definite,
Econometric Analysis of Selected Economic Indicators. heteroskedasticity and autocorrelation consistent covariance
Interstat statjournals.net/YEAR/2012/articles/1208002.pdf. matrix. Econometrica. 55:703-708.Bhunia and Mukhuti 043 Phillips PCB, Perron P(1988). Testing for Unit Root in Time Japan: A Bounds Testing Approach, Online at Series Regression. Biometrika. 75: 335-86. http://mpra.ub.uni-muenchen.de/33030/ MPRA Paper No. RBI Report (2012). Working Group to Study the Issues Related 33030. The Evidence from Thailand. Int. J. Financ. Res to Gold Imports and Gold Loans by NBFCs in India. Pp. 1- 3(2): 105-114. 224. Virginie C , Hélène RF (2011). Gold and financial assets: Are Shahzadi Hina , Chohan MN (2012). Impact of Gold Prices on there any safe havens in bear markets?', Economics Bulletin, Stock Exchange: A Case Study of Pakistan, Working paper 31(2):1613-1622. series, Karachi Stock Exchange, 10 (2):1-12. www.rbi.org.in Sumner SW, Johnson R , Soenen L (2012). Spillover effects Yahyazadehfar M, Babaie A (2012). Macroeconomic among gold, stocks, and bonds, (JCC) J. of Centrum Variables and Stock Price: New Evidence from Iran, Middle- Cathedra. Pp. 106-120. East Journal of Scientific Research, 11 (4): 408-415. Smith G(2001). The Price of Gold and Stock Price Indices for Yahyazadehfar M , Babaie A (2012). Macroeconomic the United States, the World Gold Council. Pp. 1-35. Variables and Stock Price: New Evidence from Iran, Middle- Tangjitprom N (2012). Macroeconomic Factors of Emerging East J. Scientific Res. 11 (4):408-415. Stock Market: Thai-Ha Le , Youngho C(2011). Dynamic Relationships between the Price of Oil, Gold and Financial Variables in
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