STOCK PRICES AND ITS RELATION WITH CRUDE OIL PRICES AND EXCHANGE RATES SESHAIAH, S. Venkata BEHERA, Chinmaya Abstract
This paper analyzes empirically whether the exchange rates and crude oil prices have explanatory power over Indian Stock market prices or not. The data used for this study are daily stock price indexes of BSE Sensex, Crude oil price and exchange rates for the period 2nd January 1991 – 12th ,December 2007. Engel-Granger and cointegration tests, VECM and variance Decomposition tests were used in the study to explain the long run relations among variables questioned. Obtained results illustrate that stock price indexes are cointegrated with crude oil prices and exchange rates by providing direct long run equilibrium relation. Our results also indicate that the stock market prices are influenced by oil and exchange rate at lag -50 where as stock market prices are influenced by exchange rate only at lag-25. The results also indicates that the average real returns in the era of rupee depreciation are lesser than that of appreciation period.
JEL Codes:
Keywords: Oil prices, Exchange Rates, Indian Stock Prices, Cointegration Tests 1. Background of the paper
In the period 2nd January 1991 to 2nd June, 2003 the Indian rupee depreciated and the stock market index (BSE Sensex) moved from 999.66 to 3206.8, where as the Indian rupee started appreciating from 3rd June, 2003 onwards and there was an unambiguous upward trend up to 12th December, 2007 ( Stock Index moved from 3181.7 – 20375.9).
Over the same period it is observed that the crude oil prices were almost constant when rupee was depreciating and the oil price trend also unambiguous when the rupee started appreciating. Some analyst predicted that the stock market Index touches 30000 marks by 2009. Especially during the period 2006 – 2007 analysts kept telling the investors that no need of doing any analysis, just keep the finger on any scrip blindly and invest to make the profit. One set of analysts also kept trying to predict when this upward trend come to an end based on U.S. trade deficit, recession, and rise in crude oil prices and depreciating U.S. Dollar with all other major currencies.
It is observed from figure-1, in the Annex, and figure -2 that Indian currency has depreciated continuously over the same period the crude oil prices trend almost constant with minor fluctuations. The stock index trend increased with major fluctuations during the same period. The peak points during the period January 1992 to July 1992 and July 1999 – July 2000 might be due to the various scams in market. Otherwise the rise in stock market is negligible because over the 12 years period the stock market increased three times.
It is also observed from figure -3 and figure -4 that the Indian currency has been appreciating continuously since 3rd June 2003, over the same period the crude oil prices
Seshaiah, S. Venkata Professor and Associate Dean (Research), IBS, Hyderabad.
svs_kiams@rediffmail.com and Mr. Chinmaya Behera, Faculty Associate, IBS, Hyderabad.
also increasing. The stock index increased by approximately seven times with in a span of four years. It is observed from table -1 that real return in stock market in the era of rupee depreciation is lesser than that of rupee appreciation era. As per the theory the stock market should rise when the currency is depreciating vice versa. However the Indian market is contradicting the theory. Hence, in this paper, we study whether there is any relationship among Indian stock market prices, Crude oil prices and exchange rates.
Much of the work has been done by experts to assess the long run relationship between stock market prices and exchange rates and stock market prices and crude oil prices. To our Knowledge no researcher made an attempt to assess the Stock market prices relationship with exchange rate and crude oil prices, especially for the Indian Stock market.
Oil & Exchange rate trend in the era of Indian currency depreciation- Fig:2
0 10 20 30 40 50 60
1/2/1991 7/2/1991 1/2/1992 7/2/1992 1/2/1993 7/2/1993 1/2/1994 7/2/1994 1/2/1995 7/2/1995 1/2/1996 7/2/1996 1/2/1997 7/2/1997 1/2/1998 7/2/1998 1/2/1999 7/2/1999 1/2/2000 7/2/2000 1/2/2001 7/2/2001 1/2/2002 7/2/2002 1/2/2003
Time
Oil & Exchange
oil exchange
Sensex trend in the era of Indian currency appreciation- Fig: 3
0 5000 10000 15000 20000 25000
6/3/2003 8/3/2003 10/3/2003 12/3/2003 2/3/2004 4/3/2004 6/3/2004 8/3/2004 10/3/2004 12/3/2004 2/3/2005 4/3/2005 6/3/2005 8/3/2005 10/3/2005 12/3/2005 2/3/2006 4/3/2006 6/3/2006 8/3/2006 10/3/2006 12/3/2006 2/3/2007 4/3/2007 6/3/2007 8/3/2007 10/3/2007 12/3/2007
Time
Sensex
Series1
Oil & Exchange trend in the era of Indian currency appreciation- Fig:4
0 10 20 30 40 50 60 70 80
6/3/2003 8/3/2003 10/3/2003 12/3/2003 2/3/2004 4/3/2004 6/3/2004 8/3/2004 10/3/2004 12/3/2004 2/3/2005 4/3/2005 6/3/2005 8/3/2005 10/3/2005 12/3/2005 2/3/2006 4/3/2006 6/3/2006 8/3/2006 10/3/2006 12/3/2006 2/3/2007 4/3/2007 6/3/2007 8/3/2007 10/3/2007 12/3/2007
Time
Exchange rate & Oil
Oil Exchange
Establishing the relationship among stock prices, crude oil prices and exchange rates is important for various reasons. First: Rise in stock market, appreciation of domestic currency and rise in crude oil prices will influence the monitory and fiscal policy especially for the emerging markets like India since Indian market experienced the contrarian’s approach. Second: Understanding linkage and integration of the variables under study will be useful to the policy makers to make appropriate decisions. Third this study also useful for multinational corporations as well as the retail investors that are involved in Index futures market.
The remainder of the paper is organized as follows, section-II deals with Literature Review, Section III data and methodology used, and section-IV presents results and discussion, followed by summary and concluding remarks in the last section.
2. Literature Review
Hetson and Rouwenhorst(1994) investigated the relationship between stock prices and exchange rates between 1978 and 1992, for twelve different markets and concluded that only a part of variations in stock prices are explained by exchange rates. Ajayi and Mougoue (1996) found that stock market prices are cointegrated with eight industrial economies; the authors also explained that a rising stock market is an indicator of an expanding economy, which goes together with higher inflation expectations. Foreign investors perceive higher inflation negatively and their demand for the currency drops and it depreciate. The authors also found that currency depreciation leads to decline in stock prices in the short run. Koutoulas and Kryzanoswski (1996) concluded that for Canadian stock market, stock market variations are significantly explained by the variations in exchange rates and similar observation is made by Kearney, .C (1998) for Ireland’s stock market. Desislava Dimitrova (2005), Found support for the hypothesis that a depreciation of currency may depress the stock market – the stock market will react with a less than once percent decline to a one percent depreciation of the exchange rate.
This also implies that an appreciating exchange rate boosts the stock market; however the author could not found any support for the same.
Jones and Kaul (1996) investigated the reaction of international stock markets oil shocks by current and future changes in real cash flows and /or changes in expected returns.
Authors have analyzed the stock markets of U.S., Canada, U.K and Japan under different institutional and regulatory environment and found that the crude oil prices allow to predict stock returns except for U.K. Authors also observed that in the post war period oil price hikes had a significant and on average detrimental effect on the stock market of each country. Sandorsky(1999) and papapetru (2001), showed that an oil price shocks has a negative and statistically significant initial impact on the stock returns. Ciner (2001) found that stock Index returns also affect crude oil future returns to S &P 500 index returns.
3. Data and Methodology
Data: For the study, we use daily data on stock market prices, exchange rates and Crude oil price from the http://www.econstats.com/index.htm. We use daily data for the period 2nd January, 1991 to 12th, December, 2007.
Methodology: The empirical exercise comprises two parts: (1) testing for a unit root, I (1), in each series and (2) testing for the number of cointegrating vectors in the system, provided that we cannot reject the null hypothesis of unit root in each of the time series being studied; and causality tests.
3.1. Unit Root Test:
To test for a unit root in each series, as a first step in analysis we transformed all time series data into natural logarithm values. Thus, the first differences correspond to growth rates. Consequently we tested for unit roots in all the series. We have used The Kwiatkowski, Philips, Schmidt and Shin (KPSS) test to test the unit root. The KPSS (1992) test differs from the other unit root tests. The KPSS statistic is based on the residuals from the OLS regression of yt on the exogenous variablesxt:
t t
t x u
y ''
The LM statistic is defined as:
Where f0, is an estimator of the residual spectrum at frequency zero and where S(t) is a cumulative residual function:
t
r
U
rt S
1
)
^(
Based on the residuals ' (0).
^
t
t x
y
u we point out that the estimator of used in this calculation differs from the estimator for used by GLS detrending since it is based on a regression involving the original data and not on the quasi differenced data.
) /(
)
(t 2 T2 f0 S
LM
t
3.2. Cointegration Test To investigate the existence of a long-term relationship between savings and investments, we explore existence of any significant long-run relationships among the variables in our model. If the variables are cointegrated, then this will provide statistical evidence for the existence of a long-run relationship. Though, a set of economic series are not stationary, there may exist some linear combination of the variables which exhibit a dynamic equilibrium in the long run (Engle and Granger, 1987). We employ the maximum-likelihood test procedure established by Johansen and Juselius (1990) and Johansen (1991). Specifically, if Yt is a vector of n stochastic variables, then there exists a p-lag vector auto regression with Gaussian errors of the following form:
where Γ1, .. ... Γp-1 and Π are coefficient matrices, zt is a vector of white noise process and k contains all deterministic elements.
The focal point of conducting Johansen’s cointegration tests is to determine the rank (r) of matrix Γ k. In the present application, there are three possible outcomes. First, it can be of full rank, (r = n), which would imply that the variables are stationary processes, which would contradict the earlier finding of non-stationary. Second, the rank of k can be zero (r
= 0), indicating that there is no long-run relationship among the variables. In instances when Γ k is of either full rank or zero rank, it will be appropriate to estimate the model in either levels or first differences, respectively. Finally, in the intermediate case when there are at most r cointegrating vectors 0 ≤ r ≤ n (i.e., reduced rank), it suggests that there are (n -r) common stochastic trends. The number of lags used in the vector auto-regression is chosen based on the evidence provided by Akaike’s Information Criterion (AIC) (see Akaike 1974). The cointegration procedure yields two likelihood ratio test statistics, referred to as the maximum eigenvalue (λ-max) test and the trace test, which will help determine which of the possibilities is supported by the data1. According to Engle and Granger (1987), if two variables are co-integrated, then a more comprehensive test of causality, which has become known as an error-correction model, should be adopted. The VECM specification restricts the long-run behavior of the endogenous variables to converge to their cointegrating relationships while allowing a wide range of short-run dynamics (Granger Causality). The cointegration term is known as the error correction term since the deviation from long-run equilibrium is corrected gradually through a series of partial short-run adjustments. The representation of VECM is
where ’ Yt-k denotes the error correction term.
4. Results and Discussion
We have used KPSS test to find the existence of a Unit root, based on the Unit root test results that are reported in table 2 in the Annex, we performed Johnsen’s cointegration test to see whether any combination of the variables are cointegrated. The results are
1 The trace test statistic is given by Trace = T Σni=r+1 ln (1- λi) where λr+1,... n are the (n- r) smallest squared canonical correlations between Yt-k and ΔYt series. The λ -max statistic is given by λ-max
= T ln (1 - λr+1) Critical values for each test are given by Osterwald-Lenum, 1993.
reported in Table –III and Table-IV in the Annex. It may be observed from the table that Indian Stock market prices exhibits long run relationship with exchange rates and crude oil prices.
After checking the long run relationship among the variables questioned, we proceed further to verify the short run relationship between the chosen variables. We experimented with a lag of 25 and 50 days hoping such a period would be adequate to get effects of one variable on the other. The results are reported in tables 5 and 6 below.
Table 5. Granger Causality. Lags: 25
Null Hypothesis Observations F-Statistic Probability
Oil does not Granger Cause Sensex 2857 1.12154 0.30724
Sensex does not Granger Cause Oil 2857 0.93252 0.55936
Exchange does not Granger Cause Sensex 3318 1.54088 0.04196 Sensex does not Granger Cause Exchange 3318 0.95800 0.52246 Exchange does not Granger Cause Oil 2874 0.52983 0.97304
Oil does not Granger Cause Exchange 2874 0.63803 0.91571
Table 6. Granger Causality. Lags: 50
Null Hypothesis Observations F-Statistic Probability
Oil does not Granger Cause Sensex 2487 1.48581 0.01566
Sensex does not Granger Cause Oil 2487 1.08358 0.32041
Exchange does not Granger Cause Sensex 3252 1.91586 0.00013 Sensex does not Granger Cause Exchange 3252 0.82346 0.80730 Exchange does not Granger Cause Oil 2487 0.61381 0.98509
Oil does not Granger Cause Exchange 2487 0.83190 0.79358
It may observed from the table that there exists a unidirectional casual influence of the Indian Stock prices from the exchange rate, Indicating the influence of the exchange rate on the Indian stock market prices in 25 days, where as when lags of 50 days are taken we see that there is a unidirectional influence on the Indian stock market prices from both exchange rate and crude oil prices. But in lags 25 days only exchange rate causes the stock market prices.
The variance decomposition results are summarized in table -VII and VIII in the Annex.
It is observed from the table that variation in stock market, oil and exchange rate are explained by themselves (99.76% to 99.96%), that is a little of the movement of the stock market prices, crude oil prices and exchange rate series can be explained by movements other than their own movement. The oil and exchange rates have not influenced the Indian market much. A similar pattern may be observed from the impulse response functions that are reported in table- VIII, which show the effect of a unit shock applied separately to the error of each equation of the VAR. The markets appear relatively independent of one another. This might be due the heavy dependence of Indian stock market on U.S. stock market. When the U.S. Currency started depreciating especially 3rd June, 2003 onwards, the FII inflow to Indian stock market has increased and that led to unambiguous upward trend in the Indian Stock market. The results of Granger causality using VECM are reported in Table 9.
Table 9: Vector Error Correction Mechanism
Standard errors in ( ) & t-statistics in [ ]
Error Correction: D(SENSEX) D(OIL) D(EXCHANGE) -0.00417 0.002857 -0.000856 (0.00125) (0.00090) (0.00018) CointEq1
[-3.32354] [ 3.17055] [-4.84225]
-0.138171 -0.010667 0.002864 (0.01717) (0.01233) (0.00242) D(SENSEX(-1))
[-8.04676] [-0.86490] [ 1.18380]
-0.177305 0.001697 0.002283 (0.01755) (0.01260) (0.00247) D(SENSEX(-2))
[-10.1053] [ 0.13464] [ 0.92375]
-0.054963 -0.000124 0.000980 (0.01740) (0.01250) (0.00245) D(SENSEX(-3))
[-3.15848] [-0.00992] [ 0.39956]
-0.162495 -0.002978 0.002507 (0.01748) (0.01255) (0.00246) D(SENSEX(-4))
[-9.29704] [-0.23725] [ 1.01806]
-0.002169 -0.007462 0.000882 (0.02420) (0.01738) (0.00341) D(OIL(-1))
[-0.08962] [-0.42934] [ 0.25861]
0.016484 -0.057283 0.001542 (0.02418) (0.01736) (0.00341) D(OIL(-2))
[ 0.68183] [-3.29897] [ 0.45282]
0.020137 -0.007882 0.004316 (0.02420) (0.01738) (0.00341) D(OIL(-3))
[ 0.83210] [-0.45350] [ 1.26584]
-0.005772 -0.002989 0.002993 (0.02418) (0.01737) (0.00341) D(OIL(-4))
[-0.23870] [-0.17208] [ 0.87864]
0.126579 0.009834 -0.059621 (0.12343) (0.08865) (0.01739) D(EXCHANGE(-1))
[ 1.02551] [ 0.11093] [-3.42854]
-0.180983 -0.015679 0.160205 (0.12362) (0.08879) (0.01742) D(EXCHANGE(-2))
[-1.46407] [-0.17660] [ 9.19884]
-0.032079 -0.069958 -0.01547 (0.12380) (0.08892) (0.01744) D(EXCHANGE(-3))
[-0.25911] [-0.78676] [-0.88696]
0.002271 0.031010 -0.064738 (0.12361) (0.08878) (0.01741) D(EXCHANGE(-4))
[ 0.01837] [ 0.34929] [-3.71745]
0.000744 0.000236 0.000256 (0.00060) (0.00043) (8.4E-05) C
[ 1.24753] [ 0.55099] [ 3.04764]
It is observed from the table that there is a little positive influence of exchange rate and Crude oil prices on stock market prices vice versa. The crude oil prices were also influenced by exchange rates and vice versa.
4. Conclusion
This study developed the hypothesis that stock market price movement has relationship with crude oil prices movement and exchange rate movement. There is insignificant upward trend in the stock market since 2nd January, 1991 to 2nd June 2003; the depreciation of rupee in this period has not influenced the stock market movement, where as there is unambiguous upward trend in the stock market prices in the period rupee started appreciating (3rd June, 2003 to 12th December, 2007). Similar observation is made in case of crude oil price movement versus stock market movement. The average real return (34.5%) is lesser in the rupee depreciation period than that of average real return (141.94%) rupee appreciation period. Similar observation is made in case of crude oil prices. We found the evidence of cointegration among stock market prices, crude oil prices and exchange rates. We also found the existence of unit root among the series. We found the existence of support for our hypothesis that the exchange rates and crude oil prices influence the stock prices with lag of 50 days, where as exchange rates only influence the stock prices with a lag of 25 days. Since the exchange rate, crude oil prices and exchange rates are influencing the stock prices with a lag of 25 days and 50 days respectively, it is suggested that, the multinational corporations as well as for retail investors to be cautious in taking the decision of investment.
This study has a lot of policy implications in the sense that the government should think of the optimal mix of fiscal, monitory policy that integrates exchange rate market, crude oil market and stock market in India. Futures study may take into account fiscal with monitory and financial mixed variables do draw upon the robustness of the present findings.
References:
Ajayi, R.A and Mougoue, M. (1996), “On the Dynamic relation between stock prices and exchange rates”, Journal of Financial Research, 19, 193-207.
Ciner, C. (2001), Energy Shocks and Financial Markets: Nonlinear Linkages, Studies in Nonlinear Dynamics and Econometrics, October, 5(3), 203-212.
Desislava Dimitrova (2005),The relationship between Exchange Rates and Stock Prices : Studied in a multivariate Model, Issues In Political Economy, Vol.14, August, 2005
Hetson, S and K.G.Rouwenhorst(1994), “Does Industrial Structure explain the benefits of International Diversification” Journal of Financial Economics, 36, 3-27
Jones, C.M, and Kaul, G (1996), Oil and the Stock markets, The Journal of Finance, Vol LI, No.2, Kearney, .C (1998), “ The causes of volatility in a small internationally integrated stock market:
Ireland, Julu 1975 –June –June 1994” Journal of Financial Research, 21(1), 85-104.
Koutoulas and Kryzanoswski , L.(1996), “ Macrofactor conditional volatility time varying risk premia and stock return behavior” Financial review, 31, 169-95.
Papapetru , E.(2001), “ Oil Price Shocks, Stock market, Economic Activity and Employment in Greece, Energy Economics, Vol.23 (5), September, 511-532
Raphael Sauter and Shimon Awerbuch (2003), “ Oil Price Volatility and economic Activity: A Survey and Literature review, Exposure Draft: 25 sep, 2002, IEA Research Paper, IEA, Paris.
Sandorsky, P.(1999) , “ Oil price Shocks and Stock market activity, Energy Economics 2, 449-469
Annex on line at the journal Website: http://www.usc.es/economet/aeid.htm
Annex.
Table:1 Frequency Distribution:
In the Era of Depreciation Exchange Average
Index
Change in return
Actual Return
Percentage Return
10-20 1124.59 0
20-30 2328.897 1204.307 1.07088539 107.08
30-40 3445.927 1117.03 0.47963907 47.96
40-50 3725.014 279.087 0.0809904 8.09
10624.428 2600.424 163.15
Average Return 40.78
Real Return 34.35
In the Era of Appreciation
Exchange Average Index Change in Return Actual Return Percentage Return
45-47 5053.674 0
43-45 19936.215 14882.541 2.94489534 294.48
41-43 Average Return 147.24
Real Return 141.94
In the Era of Depreciation
Oil Average Index Change in Return Actual Return Percentage Return
20-30 2896.7 0 0
20-30 3698.095 801.395 0.27665792 27.66
Average Return 13.83
Real Return 7.4
In the Era of Appreciation
Oil Average Index Change in Return Actual Return Percentage Return
30-40 4906.977 0
40-50 5610.468 703.491 0.14336546 14.33
50-60 6805.814 1195.346 0.21305638 21.30
60-70 11988.405 5182.591 0.76149466 76.14
111.79
Average Return 27.94
Real Return 22.64
Note: Where in depreciation era average annual inflation were 6.43 and in appreciation era average annual inflation were 5.3.
Table 2: KPSS Test
Variable Level 1st difference 2nd difference
Sensex 4.068 0.074 -
Oil 5.102 0.229 -
Exchange 6.458 1.238 0.226
Table 3: Multivariate Co-integration (Trace Statistics) Lags interval (in first differences): 1-4
Unrestricted Cointegration Rank Test (Trace) at 0.01 level of significance levels Hypothesized
No. f CE(s)
Eigenvalue Trace Statistics 0.1 Critical Value
Prob.**
None* 0.13793 56.40491 35.45817 0.0000
At most 1 0.002481 10.61252 15.93711 0.2365
At most 2 0.000735 2.424054 6.634897 0.1195
Trace test indicates 1 conintegrating eqn(s) at the 0.01 level
* denotes rejection of the hypothesis at the 0.01 level
**MacKinnon-Haug-Michelis(1999) P-Values
Table 4: Multivariate Co-integration (Max-Eigen Statistics) Lags interval (in first differences): 1to 4
Unrestricted Cointegration Rank Test (Maximum Eigenvalue) at 0.01 level of significance levels
Hypothesized No. f CE(s)
Eigenvalue Maximum Eigenvalue
0.1 Critical Value
Prob.**
None* 0.013793 45.79239 25.86121 0.0000
At most 1 0.002481 8.188465 18.52001 0.3599
At most 2 0.000735 2.424054 6.634897 0.1195
Maximum Eigenvalue test indicates 1 conintegrating eqn(s) at the 0.01 level
* denotes rejection of the hypothesis at the 0.01 level
**MacKinnon-Haug-Michelis(1999) P-Values
Figure 1
Sensex trend in the era of Indian currency depreciation- Fig: 1
0 1000 2000 3000 4000 5000 6000 7000
1/2/1991 7/2/1991 1/2/1992 7/2/1992 1/2/1993 7/2/1993 1/2/1994 7/2/1994 1/2/1995 7/2/1995 1/2/1996 7/2/1996 1/2/1997 7/2/1997 1/2/1998 7/2/1998 1/2/1999 7/2/1999 1/2/2000 7/2/2000 1/2/2001 7/2/2001 1/2/2002 7/2/2002 1/2/2003
Time
Sensex
sensex
Table 7: Variance Decomposition of SENSEX, OIL and EXCHANGE SENSEX:
Period S.E. SENSEX OIL EXCHANGE
1 0.035548 100.0000 0.000000 0.000000
2 0.046894 99.98508 9.98E-05 0.014822
3 0.053397 99.97239 0.012030 0.015584
4 0.059197 99.91383 0.065323 0.020851
5 0.064766 99.88686 0.090012 0.023129
6 0.069842 99.87491 0.101161 0.023924
7 0.074469 99.86294 0.112257 0.024798
8 0.078771 99.85095 0.123685 0.025360
9 0.082809 99.84015 0.134205 0.025648
10 0.086617 99.83028 0.143986 0.025737
OIL:
Period S.E. SENSEX OIL EXCHANGE
1 0.024484 0.002073 99.99793 0.000000
2 0.034451 0.002218 99.99738 0.000398
3 0.041300 0.001667 99.99806 0.000277
4 0.047127 0.001645 99.99376 0.004591
5 0.052308 0.002434 99.99077 0.006798
6 0.056990 0.004206 99.98711 0.008687
7 0.061285 0.006867 99.98332 0.009808
8 0.065273 0.010387 99.97898 0.010638
9 0.069009 0.014781 99.97404 0.011176
10 0.072530 0.020054 99.96841 0.011539
EXCHANGE:
Period S.E. SENSEX OIL EXCHANGE
1 0.004786 0.113297 0.007791 99.87891
2 0.006568 0.075216 0.019459 99.90533
3 0.008393 0.050598 0.034347 99.91505
4 0.009811 0.041465 0.082862 99.87567
5 0.011099 0.037828 0.112247 99.84993
6 0.012233 0.036391 0.137346 99.82626
7 0.013275 0.036191 0.156052 99.80776
8 0.014234 0.036868 0.172211 99.79092
9 0.015131 0.038196 0.186149 99.77566
10 0.015975 0.039999 0.198819 99.76118
Table 8: Impulse Response:
Response of SENSEX:
Period SENSEX OIL EXCHANGE
1 0.035548 0.000000 0.000000
(0.00044) (0.00000) (0.00000)
2 0.030579 4.69E-05 0.000571
(0.00073) (0.00062) (0.00062)
3 0.025530 0.000584 -0.000344
(0.00088) (0.00082) (0.00081)
4 0.025510 0.001395 -0.000535
(0.00098) (0.00093) (0.00092)
5 0.026241 0.001219 -0.000489
(0.00078) (0.00080) (0.00085)
6 0.026115 0.001077 -0.000444
(0.00072) (0.00075) (0.00085)
7 0.025812 0.001136 -0.000456
(0.00076) (0.00076) (0.00084)
8 0.025641 0.001204 -0.000445
(0.00078) (0.00077) (0.00084)
9 0.025512 0.001236 -0.00043
(0.00078) (0.00077) (0.00084)
10 0.025363 0.001265 -0.000415
(0.00079) (0.00078) (0.00083)
Response of OIL:
Period SENSEX OIL EXCHANGE
1 0.000111 0.024484 0.000000
(0.00042) (0.00030) (0.00000)
2 -0.000118 0.024236 6.88E-05
(0.00060) (0.00052) (0.00043)
3 4.59E-05 0.022777 2.01E-06
(0.00072) (0.00066) (0.00060)
4 9.00E-05 0.022698 -0.000312
(0.00082) (0.00077) (0.00071)
5 0.000173 0.022694 -0.00029
(0.00074) (0.00074) (0.00072)
6 0.000265 0.022619 -0.00031
(0.00070) (0.00072) (0.00073)
7 0.000348 0.022533 -0.000294
(0.00072) (0.00072) (0.00073)
8 0.000430 0.022461 -0.000291
(0.00073) (0.00072) (0.00073)
9 0.000511 0.022389 -0.000281
(0.00073) (0.00073) (0.00073)
10 0.000592 0.022317 -0.000274
(0.00074) (0.00073) (0.00073)
Response of EXCHANGE:
Period SENSEX OIL EXCHANGE
1 -0.000161 4.22E-05 0.004783
(8.3E-05) (8.3E-05) (5.9E-05)
2 -8.06E-05 8.13E-05 0.004496
(0.00011) (0.00011) (0.00010)
3 -5.66E-05 0.000126 0.005225
(0.00015) (0.00015) (0.00013)
4 -6.53E-05 0.000236 0.005074
(0.00017) (0.00017) (0.00016)
5 -8.18E-05 0.000242 0.005184
(0.00016) (0.00017) (0.00017)
6 -8.86E-05 0.000259 0.005136
(0.00016) (0.00018) (0.00018)
7 -9.65E-05 0.000264 0.005147
(0.00016) (0.00018) (0.00018)
8 -0.000105 0.000272 0.005129
(0.00017) (0.00018) (0.00018)
9 -0.000113 0.000278 0.005124
(0.00017) (0.00018) (0.00018)
10 -0.000121 0.000285 0.005113
(0.00017) (0.00018) (0.00018)
Journal published by the EAAEDS: http://www.usc.es/economet/eaa.htm
