This is the powerpoint presentation of a research conducted on the causal relationship between stock market (that are nifty50 and sensex30 indices) and real GDP of India. The idea is to identify whether former Granger causes the latter or vice versa.

1. SAMYAK CHAUDHARY
SHAHEED SUKHDEV COLLEGE OF
BUSINESS STUDIES

2. Objective
 This study tries to evaluate the causal relationship
between stock market and the real economy of
India by applying Granger Causality test on Nifty 50
and BSE Sensex data with real GDP of India
 It also finds out the direction of causality.
 This study explains the theories related to such a
relationship

3. Scope of research
 The report only theoretically explains the relationship
between the entities based on previous literature
 It only finds the presence and the direction of the causality
to know what causes what.
 Assumes that there indeed exists a relationship between
the two entities
 Proxy for real economy is taken as Real GDP
 Use of Real economy is an important addition to this
report.
 Uses GDP at Factor cost instead of market price
 Indian Scenario Only

4. Data
 This study is mainly conducted on Indian data using the Indian
GDP values and Indian stock market indices.
 It uses both quarterly and annual data for real GDP and Market
indices.
 The quarterly period is from year 1996 Q4 to 2015 Q3.
 The annual period is from the year 1990 to 2014.
 The CNX BSE Sensex data has been obtained from BSE official
website, whereas, Nifty50 data is taken from NSE Website
(from1990 to 1995) and Investing.com (from 1996 to 2015)
 Nominal GDP at Factor Cost in Indian Rupees and the Real GDP
index with base as 2010 prices taken as 100 are the necessary data
for real GDP collected from IMF database (International
Financial Statistics)

5. Adjustment
 Calculation of Real GDP is done on the basis of this
formula
 Real GDP at FC= Nominal GDP at FC*Real GDP index
(base=2010 prices)/100
Hypothesis
 Null Hypothesis is Stock index do not Granger cause
GDP
 Alternate Hypothesis is Stock index Granger cause
GDP

6. Research Methodology
 The data used is tested for stationarity. For this, augmented
Dickey Fuller Test is applied. Non-stationary series is
converted to stationary at required differences.
 After that, the number of lagged terms included in all
Granger tests conducted is going to be determined on the
basis of the VAR lag length criteria.
 Autocorrelation LM tests are applied to test Serial
autocorrelation of residuals.
 Furthermore, Granger Tests are applied first to see whether
real GDP Granger causes each of the Stock Market Indices
and vice-versa is also checked.

7. Results
difference
Quarterly data Annual Data
GDP 2nd 3rd
BSE SENSEX 2nd 1st
Nifty50 2nd 1st
ADF Unit root test Results

8. ADF Unit root test Results
GDP
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -8.393624 0.0000
Test critical values: 1% level -2.685718
5% level -1.959071
10% level -1.607456
Sensex annual
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -6.176505 0.0000
Test critical values: 1% level -2.669359
5% level -1.956406
10% level -1.608495
Nifty 50
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -6.445014 0.0000
Test critical values: 1% level -2.669359
5% level -1.956406
10% level -1.608495

9. Lag terms Results
GDP and Nifty50 annual
Lag LogL LR FPE AIC SC HQ
0 -324.0403 NA 4.95e+11 32.60403 32.70360 32.62347
1 -312.7392 19.21188 2.40e+11 31.87392 32.17264 31.93223
2 -300.6326 18.15992* 1.08e+11* 31.06326* 31.56112* 31.16045*
GDP and Sensex annual
Lag LogL LR FPE AIC SC HQ
0 -348.0916 NA 5.49e+12 35.00916 35.10873 35.02859
1 -337.4617 18.07070 2.84e+12 34.34617 34.64489 34.40449
2 -324.7454 19.07453* 1.21e+12* 33.47454* 33.97241* 33.57173*

10. Lag terms Results
Lag terms
Quarterly data Annual Data
BSE and GDP 2 BSE and GDP 2
Nifty and GDP 2 Nifty and GDP 2

11. LM test Results
Lags LM-Stat Prob
1 1.943917 0.7461
2 5.043514 0.2829
3 7.552821 0.1094
Lags LM-Stat Prob
1 2.389563 0.6645
2 5.138375 0.2734
3 7.687445 0.1037
GDP and Nifty50 annualGDP and Sensex annual

12. Granger Causality Test Results
Pairwise Granger Causality Tests
Sample: 1990 2014
Lags: 2
Null Hypothesis: Obs F-Statistic Prob.
DBSESENSEX does not Granger Cause D3GDPANNUAL 20 0.41221 0.6695
D3GDPANNUAL does not Granger Cause DBSESENSEX 5.54492 0.0157
Pairwise Granger Causality Tests
Sample: 1990 2014
Lags: 2
Null Hypothesis: Obs F-StatisticProb.
DNIFTY50ANNUAL does not Granger Cause
D3GDPANNUAL 20 0.41595 0.6671
D3GDPANNUAL does not Granger Cause DNIFTY50ANNUAL 5.33656 0.0178

13. Granger Causality Test Results
Quarterly p-value Status Annually p-Value Status
BSE sensex does not Granger cause
GDP
0.0975 TRUE BSE sensex does not Granger cause
GDP
0.6695 TRUE
GDP does not Granger cause BSE
sensex
0.3199 TRUE GDP does not Granger cause BSE
sensex
0.0157 FALSE
Nifty50 does not Granger cause
GDP
0.0997 TRUE Nifty50 does not Granger cause
GDP
0.6671 TRUE
GDP does not Granger cause
Nifty50
0.4296 TRUE GDP does not Granger cause
Nifty50
0.0178 FALSE

14. Conclusion
 In case of Annual Data sets there was a Unidirectional
Causality from real GDP to both stock indices.
 The previous yearly values of GDP explain a stronger
relationship with market indices rather than previous
values of market indices themselves.
 Both the indices are showing same results, we can say
that the result is consistent irrespective of the market
index.
 And GDP precede market indices on annual basis as
GDP takes a year’s time to actually have some effect.

15. Limitation of the study
 This study fails to explain how strong the relationship
is and how strongly GDP growth causes stock market
movement.
 Other macro economic factors that affect stock prices
are not considered for analysis.
 Data constraint as real GDP data was found to be
limited
 Base research was done developed economies however
India is developing.
 We still cannot say the cause and effect relationship as
Granger cause does not necessarily mean causation. It
is more of precedence.

16. Further Scope
 Further research can be done to appropriately explain
the true reasons for the existence of the Granger
relationships.
 May use macroeconomic variables
 relative smallness of the market (as per base research)
may suggest a lack of causality between the stock
market and the economy

17. 0.00
5000.00
10000.00
15000.00
20000.00
25000.00
30000.00
US Japan France China India
Market Capitalization and GDP
(current billion US$)
Market Capitalization
GDP
0
20
40
60
80
100
120
140
160
US Japan France China India
Market Capitalization % of GDP
Market Capitalization %
of GDP

18.  If economy causes the stock market movement,
then macroeconomic indicators become really
helpful for an investor.
 On the other hand, if opposite happens, then we
can consider share prices as an economic indicator
and can predict an economic slowdown or recession
(like Great Depression)