research artical

7/30/2019 Research Artical

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IMPACT OF GDP GROWTH RATE, INFLATION RATE & LENDING INTEREST RATE ON

SENSEX RETURNS

ByProf Anand Patil

Venkata Mahendra Prasad

Kausar K

ABSTRACT

The study aims to find the relationship between Gross Domestic Product Growth Rate, Inflation Rate andLending Interest Rate on Sensex Performance. The study revealed that there is no significant relationship betweenthe GDP Growth Rate, Inflation Rate & Lending Interest Rate on Sensex Returns.

KEY WORDS: GDP, Inflation, Interest Rate & SENSEX Performance

INTODUCTION

No economic activity operates in a vacuum. Market reacts promptly and uncharacteristically to rumors of war,changes in regulatory environment. Fluctuating political climate is seen as a negative factor by the business(investing) community and variation of Interest Rate to general performance of the economy. Some of the factorsinfluencing stock price behavior include company profits, political factors and economic performance. Others areInflationary Rate, GDP, and Shareholder-level taxes.

Financial investments associated with risk, with this context investors intend to identify whether portfoliodiversification is applied or not. To compensate risk of investment while gaining profit there is a need of tools tounderstand the behavior of stock market. This study is an effort to help the investors to understand therelationship between the GDP Growth Rate, Inflation Rate, and Lending Interest Rate on Stock Market Returns.

GDP Growth (Annual %): GDP is the sum of gross value added by all resident producers in the economy plus anyproduct taxes and minus any subsidies not included in the value of the products. It is calculated without making

deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. AnnualGrowth Rate of GDP at market prices based on constant local currency, aggregates are based on constant 2000 U.S.dollars.

Inflation, Consumer Prices (Annual %) : Inflation as measured by the Consumer Price Index reflects the annualpercentage change in the cost to the average consumer, of acquiring a basket of goods and services that may be fixedor changed at specified intervals, such as yearly.

Lending Interest Rate (%): Lending Interest Rate is the rate charged by banks on loans to prime customers.

Almost every country in the world suffered their worst stock market declines as measured in real values, during aperiod of high inflation or hyperinflation as stocks and the other financial assets failed to keep up with theincreases in the prices of goods. In addition, it also creates extreme volatility in stock market return. If the

government lacks the power to resolve the inflation, the stock will collapse in its value. In addition, SENSEXreturns represent activeness of the market. Unfortunately, SENSEX returns can be influenced by othermacroeconomic activities and thus create the global phenomenon. Especially the current trend of increasinginflationary pressures, result in the rising international prices of energy and commodities.

In Asia, Indian economy has gained importance in the last few years. The Indian stock market is often measuredby Sensex and Nifty. The Study of relationship of GDP Growth Rate, Inflation Rate & Lending Interest Rate onthe Sensex Performance will become a tool for researcher or policy maker to make further decision on analyzingthe key economic indicators for the countrys economy. This paper intends to assess the impact of GDP GrowthRate, Inflation Rate & Lending Interest Rate on Sensex Returns.


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LITERATURE REVIEW

There has been extensive research across the world with regard to the impact of macroeconomic factors on stockmarket returns. Some of the relevant literature is reviewed in the following.

Maysami et al (2004) studied the long-term interrelationship between selected macroeconomic variables, includinginflation, industrial production, money supply, exchange rates and interest rates, and the Singapore stock marketindex, using vector error correction model. They concluded that all the above macroeconomic variables have animpact on the Singapore stock market index.Oskenbayev et al (2011) investigated the causal relationship between macroeconomic indicators, including the indexof industrial production, inflation, exchange rate, oil prices volatility, volume of trade and long & short term interestrates, and the Kazakhstan Stock Exchange (KASE). They measured the long-term relationship using AutoregressiveDistributed Lag model, while they used the Johansen co-integration test and Granger causality test for identifyingthe equilibrium relationship.

Naka et al (1998) studied the impact of macroeconomic variables, including the index of industrial production,consumer price index, narrow money supply-M1, and money market rate in the Bombay interbank market, on Indianstock markets. They used vector error correction model (VECM) for this purpose. They found domestic inflationand domestic output growth to be key macroeconomic indicators affecting Indian stock markets.

Ray and Vani (2003) performed a similar study on Indian stock markets. Their study considered macroeconomicvariables such as the index of industrial production, broad money supply (M3), fiscal deficit, wholesale priceinflation, INR/USD exchange rate, SBI prime lending rate, and Foreign Institutional Investments. They used VectorAuto Regressive and Artificial Neural Networks in their analysis. The study identified the index of industrial

production, inflation, money supply, exchange rates and interest rates as key real economic variables affectingIndian stock markets.

Singh (2010) examined causal relationships between macroeconomic variables and Indian stock markets. Heconsidered three macroeconomic variables, IIP, WPI and exchange rates. He applied Granger causality test for this

purpose. He found that IIP was the only macroeconomic variable causing changes in SENSEX.

Dash and Rao (2011) found that the APM did not have significant better explanatory power over the CAPM forIndian capital markets. Apart from the market factor, they found that interest rates (the MIBOR factor) have a

significant role to play in influencing asset returns; but the market factor was found to be the most influential of thefactors, more than twice as important as interest rates.

OBJECTIVE OF THE STUDY

The Paper aims to achieve the following objectives:

1. To study the relationship between SENSEX returns with respect to GDP Growth Rate, Inflation Rate andLending Interest Rate.

2. To find the level of significance between SENSEX returns with GDP Growth Rate, Inflation Rate andLending Interest Rate.

RESEARCH DESIGN

Nature of the Study:

1. The research carried out will be descriptive in nature for the better understanding of the undertakenresearch analysis.

2. The research will also use Vector Auto Regression Model, to find out the significance level between thevariables under study.

3. The data regarding SENSEX returns, GDP Growth Rate, Inflation Rate, Lending Interest Rate will betaken for the last 15 years for the study.


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Collection of data:

1. Information regarding GDP Growth Rate, Inflation Rate, Lending Interest Rate, and SENSEX Returnswould be collected from the websites of Ministry of Finance, Economic Survey of India, BSE India,World Bank and RBI.

2. Books will be referred to support the formation of certain conceptual definitions and in-depth knowledgeof the subject.

3. Journals, Magazines and Newspapers will be used to accumulate the latest information about the variableunder this research.

METHODOLOGY

The present study was carried out to analyse the impact of GDP Growth Rate, Inflation Rate & Lending InterestRate on the Sensex returns. Yearly data of various macroeconomic variables, viz. GDP Growth Rate, Inflation Rate(Wholesale Price Index), Lending Interest Rate were collected for the 15 year period 1997-2011 from the WorldBank website. The study was conducted on BSE SENSEX. Yearly closing SENEX values were collected from theofficial website of the Bombay Stock Exchange.

At the outset, the Dickey-Fuller Unit Root Test was carried out to check for the stationarity /non-stationarity of the

variables. It is based on the following model: Yt= Yt-1+utwith rejection of the null hypothesis of a unit root if is significant and negative. The study used a vector autoregressive (VAR) model to test for the impact of themacroeconomic variables on Sensex returns. The unrestricted VAR model is given as follows:

St= + 1j.GDPt-j+

2jWPIt-j+

3jIRt-j+t

In the model, St Represents SENSEX returns, GDP represents percentage change in the Gross Domestic Product

Growth Rate, WPI represents the change in Inflation Rate, and IR represents the percentage change in Interest Rate.

The model used two-yearly lags for Inflation Rate & Interest Rate, one-yearly lags for GDP Growth Rate as

determined from the auto-correlation functions. The F-test of the VAR output was performed to determine the

significance of the impact of each macroeconomic variable on SENSEX returns.


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DATA ANALYSIS & FINDINGS

Data:

Year GDP Inflation

Interest

Rate SENSEX

1997 4.9 3.7 12.1 3,6591998 4 4 12.3 3,0551999 8.5 4.7 12.5 5,0062000 6.2 13.2 13.5 3,9722001 4 7.2 13.8 3,2622002 9.3 6.1 11.2 3,3772003 9.3 4.2 10.8 5,8392004 7.8 3.8 10.9 6,6032005 7.9 3.8 11.5 9,398

2006 3.9 4.4 11.9 13,787

2007 6.9 8.9 10.2 20,287

2008 9.6 12 8.3 9,6472009 8.2 10.9 12.2 17,465

2010 3.9 8.4 13.3 20,5092011 9.8 6.4 13 15,455

Data after Dickey-Fuller Unit Root Test to check for the stationarity /non-stationarity of the variables:

GDP D Inflation D Interest Rate Sensex

4 -16.58.5 0.7 0.2 63.83

6.2 8.5 1 -20.654 -6 0.3 -17.87

9.3 -1.1 -2.6 3.529.3 -1.9 -0.4 72.897.8 -0.4 0.1 13.08

7.9 0 0.6 42.33

3.9 0.6 0.4 46.7

6.9 4.5 -1.7 47.159.6 3.1 -1.9 -52.45

8.2 -1.1 3.9 81.033.9 -2.5 1.1 17.439.8 -2 -0.3 -24.64

TABLE 1: Raw Data; Source: World Bank

TABLE 2: Results of Unit Root Test after creating Lags


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VAR Model Description

Model Name MOD_4

Series Name 1 GDP growth

2 DIFF(Inflation,1)

3 DIFF(InterestRate,1)

4 SENSEX Returns

Transformation None

Non-Seasonal Differencing 0

Seasonal Differencing 0

Length of Seasonal Period No periodicity

Maximum Number of Lags 16

Display and Plot All lags

Applying the model specifications from MOD_4

Results of VAR Model:

EXHIBIT 1: Partial Autocorrelations; GDP Growth Rate


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EXHIBIT 2: Partial Autocorrelations; Inflation Rate

EXHIBIT 3: Partial Autocorrelations; Interest Rate

EXHIBIT 4: Partial Autocorrelations; SENSEX Returns


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VAR Model Results

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 .445a .198 -.069 43.28445

a. Predictors: (Constant), DIFF(Interest Rate,1),

DIFF(Inflation Rate,1), GDP Growth Rate

ANOVAb

Model

Sum of

Squares df

Mean

Square F Sig.

1 Regression 4172.474 3 1390.825 .742 .553a

Residual 16861.890 9 1873.543

Total 21034.364 12

a. Predictors: (Constant), DIFF(Interest Rate,1), DIFF(Inflation Rate,1),

GDP Growth rate

b. Dependent Variable: SENSEX Returns

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.B Std. Error Beta

1 (Constant) .651 45.824 .014 .989

GDP growth 2.707 6.020 .142 .450 .664

DIFF(Inflation,1) -.943 3.520 -.081 -.268 .795

DIFF(InterestRate,1) 11.690 8.167 .453 1.431 .186

a. Dependent Variable: SENSEX Returns

TABLE 3: Results of VAR Model; Summar


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GDP Growth Rate

Unrestricted ModelANOVA

b

ModelSum ofSquares

dfMeanSquare

F Sig.

1Regression 4172.474 3 1390.825 .742 .553a

Residual 16861.890 9 1873.543Total 21034.364 12

Restricted ModelANOVA

b

ModelSum ofSquares

dfMeanSquare

F Sig.

1Regression 3793.670 2 1896.835 1.100 .370a

Residual 17240.694 10 1724.069Total 21034.364 12

Inflation Rate

Unrestricted Model

ANOVAb

ModelSum ofSquares df

MeanSquare F Sig.

1 Regression 4172.474 3 1390.825 .742 .553a

Residual 16861.890 9 1873.543

Total 21034.364 12

TABLE 4: Results of VAR Model; GDP Growth Rate

F-TestF Calculation: 0.202186P Value: 0.663596From above we can infer that the results are not significant. Hence we can state that GDP has no impact onSEXSEX returns.


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Restricted Model

ANOVAb


MeanSquare F Sig.

1 Regression 4037.951 2 2018.975 1.188 .344

a

Residual 16996.413 10 1699.641

Total 21034.364 12

Interest Rate

Unrestricted Model

ANOVAb


MeanSquare F Sig.

1 Regression 4172.474 3 1390.825 .742 .553a

Residual 16861.890 9 1873.543Total 21034.364 12

Restricted Model

ANOVAb


MeanSquare F Sig.

1 Regression 333.823 2 166.912 .081 .923a

Residual 20700.541 10 2070.054

Total 21034.364 12

TABLE 6: Results of VAR Model; Interest Rate

TABLE 5: Results of VAR Model; Inflation Rate

F-TestF Calculation: 0.071801P Value: 0.794772From above we can infer that the results are not significant. Hence we can state that Inflation has no impact on

SEXSEX returns.

F-TestF Calculation: 2.048872P Value: 0.186114From above we can infer that the results are not significant. Hence we can state that Interest Rate has noimpact on SEXSEX returns.


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The result of the unit root test was significant for GDP Growth Rate & not significant for Inflation Rate & LendingInterest Rate, hence the lags were created for Inflation rate & Lending Interest Rate, which later indicated that all ofthe time series were stationary.

This validates the application of vector autoregressive modeling in the present context. The results of the F-test ofthe Vector Autoregressive Model indicate that GDP Growth Rate, Inflation Rate & Lending Interest Rate to have nosignificant impact on the SENSEX returns.

LIMITATIONS OF THE STUDY

1. The study has considered only the Annual Data for past 15 Years.

2. The study has considered only 3 Macro Economic Indicators.

3. The results of the same study may vary if Weekly or Monthly data is considered.

CONCLUSIONS

This study focus mainly to reinvestigate the impact of GDP Growth Rate, Inflation Rate, Lending Interest Rate onSensex Returns. There is no significant relationship between these variables. Hence any change in these macrovariables would not have an impact on Sensex Returns.

Though the results of the present study are interesting, there is scope for further study in examining the impact ofother macroeconomic variables, as well as in examining the pre- and post- global financial meltdown investmentscenarios.

REFERENCES

1. Caroline Geetha , Rosle ,Mohidin Vivin Vincent Chandran Victoria Chong "The Relationship BetweenInflation And Stock Market: Evidence From Malaysia, United States And China. International JournalOf Economics And Management Sciences Vol. 1, No. 2, 2011, Pp. 01-16.

2. Daferighe. Emmanuel E " An Impact Analysis of Gross Domestic Product , Inflation, and Interest Rateson Stock Prices of Quoted Companies in Nigeria

3. Kendall, M.G. (1953), The Analysis of Economic Time Series- Part I: Prices, Journal of the RoyalStatistical Society, vol. 116(1), pp. 11-34.

4. Mossin, J. (1966), "Equilibrium in a Capital Asset Market," Econometrics 34.

5. Naka, A., Mukherjee, T.K., and Tufte, D.R. (1998), Macroeconomic variables and the performance of theIndian Stock Market, University of New Orleans, Department of Economics and Finance Working Papers.

6. Ray, P. and Vani, V. (2003), What Moves Indian Stock Market: A Study on the Linkage with RealEconomy in the Post-Reform Era, oii.igidr.ac.in:8080/dspace/bitstream/2275/123/1/prantik.pdf

7. Singh, D. (2010), Causal Relationship between Macro-Economic Variables and Stock Market: A Case

Study for India, Pakistan Journal of Social Sciences, vol. 30(2), pp. 263-274.

8. Sharpe, W. F. (1964), "Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk,"Journal of Finance 19.

9. www.bseindia.com

10. www.worldbank.org

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