impact of macro -economic indicators on stock market return (an indian experience)

IMPACT OF MACRO -ECONOMIC INDICATORS ON STOCK MARKET RETURN (AN INDIAN

EXPERIENCE)

1

ABSTRACT

IMPACT OF MACRO-ECONOMIC INDICATOR’S ON STOCK MARKET RETURN (AN INDIAN

EXPERIENCE)

Stock market acts as barometer to the economic development of a nation. A number of studies

has been conducted to investigate the relationship between the economic indicators and stock

market return. This study investigates the relationship between the real economic indicators and

the stock market return in India. Study uses empirical monthly data of Macro-economic

indicators, namely, growth, inflation rate, interest rate, money supply, exchange rate in India and

their effect on stock market return between fiscal year 2001-02 and 2013-14. The study is

especially important due to the surges, adjustments of the Indian stock market that is being

witnessed lately. The study employs correlation analysis to assess the relationship (direction and

magnitude) of independent variables with the stock market return. We have also used regression

analysis to evaluate the impact of individual indicator on the stock market return and their

contribution in the regression equation through part correlation. To assess the validity of the

multiple regression we have also checked linearity and multicollinearity. To validate linearity we

have employed Normal P-P plot and to check multicollinearity we have appropriated a tolerance

level of 0.1 and VIF of less than 10. The validity of regression has been found acceptable.

The study finds correlations between the stock market and the economic variables with inflation

having a negative relationship while rest all have a positive relationship. Exchange rate has the

lowest relationship and Money supply has the highest. Regression analysis showed the 5

indicators accounted for 94.1% movement of the stock market return. Money supply also has the

highest contribution in the regression model. And the contribution made by exchange rate is

found negligible in our regression equation. The study points out that the Indian stock market is

sensitive towards changing trend of macroeconomic variables in the economy and they can be

utilized to understand the general trend of stock prices. The regulatory authorities should keep

this mind while formulating policies. And investors should account the economic indicators

before making any decisions.


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Chapter - 1

Introduction

Capital Market is the market for medium and long term finance. Livingston famously quoted “It

is the business of the capital market to facilitate the movement of the stream of command over

capital to the points of highest yield. By so doing it enables control over resources to pass into

the hands of those who can employ them most efficiently, thereby increasing productive capacity

and swelling the national dividend.” Therefore we can infer that capital market mobilizes the

capital from non-productive to the productive sources. The capital market can be divided into

two i.e. Primary and Secondary Market. Primary Market is the market for new issues and the

outstanding shares are traded in the Secondary Market. This financial instruments may be issued

by companies or government. This includes common shares, preference shares, bonds and

others.

There are two reasons considered responsible for transaction in the secondary market. First is

based on information, wherein investors think they have superior information in comparison to

other investors. Second is based on liquidity where investors have insufficient cash or excess cash

in hand.

Prior to the 19th century, few entities such as government and stock of few large corporations

such as Bank of England, the Dutch and the East India Company were only traded. It is believed

that the first Stock Market was created by Jews in 1300s. Industrial Revolution had not still

affected the stock market. The companies were still small and their financial needs were met by

borrowing. Industrial revolution increased the living standard of the British middle class which

result in demand for more financial assets. On the other hand, the supply of government

securities was declining and the British government steadily paid off the debt incurred in the wars

of 1776 – 1815. Consequently, British investors started to buy more speculative domestic and

foreign issues.


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After the end of civil war, capital market rapidly developed in the United States. Jay Cooke and

other started the selling of railroad bonds to small investors. Besides these, the rapidly growing

insurance companies and saving banks provided an important market for long-term securities.

The securities of the manufacturing companies became important only after the 1990s. The scale

of the manufacturing expanded as technology advanced. As a result, their fund requirement for

the purpose of set up of plant and to combine small firms into larger one increased tremendously

which could be met by the capital market. Much of this finance was in the form of equities rather

than bonds. However, the growth of stock market before World War I was nothing compared to

the boom of the 1920s. The number of stocks listed number of issues, the volume of trading –all

these exploded during the said period. But stock market crash of 1929 and after that depression

in the world market exerted great impact on its growth and which could not revive until the

1950s.

Indian Stock Market is one of the oldest Stock Market in Asia. East India Company used to transact

Loan Securities by the end of 18th Century. In the 1830s, trading on corporate stocks and shares

in Bank and Cotton presses took place in Bombay. Few informal groups of Stock Brokers

organized themselves in 1875 and were formally organized as Bombay Stock Exchange (BSE). In

1956, the Government of India recognized the Bombay Stock Exchange as the first Stock

Exchange in the country under the Securities Contracts (Regulation) Act. But still there was no

means to measure the overall performance of the exchange. So, in 1986, Bombay Stock Exchange

developed BSE Sensex (Sensex = Sensitive Index), an index of top 30 companies, which gave a

means to measure the overall performance of the Exchange.

Empirical studies have shown that the stock market plays an important role in the development

of an economy. Stocks prices can act as indicator of real economic activity and suggest the

general mood of the economy. Increased economic performance generally reflects in the

increase of stock prices or vice versa. Investors look for economy with healthy stock prices and

return.


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The firms through the issue of financial instruments avail long term finance for themselves in the

primary market. The basic idea behind the secondary market is to provide liquidity to those

instruments. The stock market thus avail long-term capital to the firms by pooling funds from

different investors and allow them to expand in business. Stock market also offers investors

alternative investment avenues to put their surplus funds in. This helps company to grow and

share profit with the investors. Stock exchanges impose stringent rules to get listed in them, so

listed public companies have better management records than privately held companies. They

help government to rise fund for developmental activities through the issue of bonds. An investor

who buys them will be lending money to the government, which is more secure, and sometimes

enjoys tax benefits also. They maintain the stock indexes which are the indicators of the general

trend in the economy. They also regulate the stock price fluctuations. The Stock market act as

the barometer for economy

The impact of macroeconomic factors on stock prices or stock returns has been a long debated

issue amongst the scholars. As per the Efficient Market Hypothesis (Fama, 1970), in an efficient

market, price of the stock reflect all the information regarding the market so no one can earn

abnormal profit. However subsequent studies have challenged this notion.

Portfolio theory (1950s by Harry Markowitz, Tobin 1958). The basic idea behind this theory is risk

mitigation through diversification. With the expected rate of return, how assets can be combined

to minimize total risk, comprising unsystematic and systematic risk. Unsystematic risk also known

as firm risk can be minimized by diversification but systematic risk also known as market risk

cannot be minimized by diversification. Economic variables and forces form the systematic risk.

The Arbitrage Pricing Theory (APT) is a framework of the linkage between stock prices and

macroeconomic fundamentals. In this connection, several empirical studies have shown that

changes in stock prices are linked with macroeconomic fundamental. Chen et al. (1986) is one of

the first to examine the link between stock prices and macroeconomic

Variables in the line of APT and provides the basis to believe for the existence of a long-run

relationship between them.


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According to the behavioral Economics, it is all about the sentiment or irrational expectations

which are driven by fear and greed, Herd Mentality as it is commonly known.

The relationship is also documented by stock valuation models such as Dividend Discount Model

(DDM), Free Cash Flow Valuation, and Residual Income Valuation. According to these, the current

prices of an equity share is approximately equal to the present value of all future cash flows i.e.

economic variable affecting cash flows and required rate of return in turn influences the share

value as well.

However, unlike the stock exchanges of advanced economies, the stock markets of emerging

economies are a recent development. While there have been numerous attempts to develop and

stabilize the stock markets, the emerging economies are identified as most volatile (Engel &

Rangel, 2005). The stock markets of emerging economies are sensitive to domestic and

international business and political factors such as changes in the level of economic activities and

also related to the changes in other macroeconomic factors.

One needs to understand that the relationship between the factors might change from market

to market and in different sampling periods. Care should be taken that the study of the past

should not be taken as de-facto. Thus, the analysis should be continuous so as to accommodate

the changing pattern of the relationships between the variables.

India, being among the largest and fastest growing economies needs a special attention. Suffice

to say the Indian capital market has undergone tremendous changes after the adoption of

liberalization policy and it became more open to international investors. Recent crash due to

subprime lending in 2008 and recent resurgent shows the volatility in the market makes an

interesting empirical study in these ends.

The study uses monthly dataset for preceding 14 years i.e. 2001-2014 to investigate the effect of

Macroeconomic variable on Return from Bombay stock using five variable vis-à-vis 1.Interest

Rate 2.Money Supply 3.Inflation 4.Exchange Rate 5.Growth.


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1.2 Need & Scope of study:

Indian stock market is one the fastest growing exchanges and increasing more people is putting

their money on it. Moreover the stock market reflects the overall economic performance of any

nation. So there is a need to understand the Indian stock market.

1.3 Objective of study

1. To measure the impact of interest rate on the Stock Market returns.

2. To measure the impact of money supply on the Stock Market returns.

3. To measure the impact of inflation on the Stock Market returns.

4. To measure the impact of exchange rate on the Stock Market returns.

5. To measure the impact of growth on the Stock Market returns.

6. To construct a linear regression model for Sensex with the 5 economic variables.


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Chapter-2

LITERATURE REVIEW

We examine the various studies conducted on the determination of relationships between

Macroeconomic variables and stock prices movements. This forms the base for conducting our

research.

Pranthik, et al(2004) investigated the monthly data between 1993-2003 and found that the

economic variables like interest rate, IIP, exchange rate, inflation and money supply had some

fluctuations but overall had a consistent relationship with the BSE Sensex Index.

Al-Sharkas. (2004) the study found a long term equilibrium relationship with Macroeconomic

variables and the Amman Stock Exchange. There also existed cointegration between the

variables.

Christopher Gan, M. L. (2006) Studied the relationships between the New Zealand Stock Index

and a set of seven macroeconomic variables i.e. inflation rate (CPI), long term interest rate (LR),

short term interest rate (SR), the real trade weighted exchange rate index (EX), real gross

domestic product (GDP), narrowly defined money supply (M1) and domestic retail oil prices

(ROIL) from January 1990 to January 2003. The study concluded that there exists a long run

relationship between NZSE40 and the macroeconomic variables studied.

Macmillan, A. H. (2007) the study found the US stock prices are positively related to industrial

production and negatively related to both the consumer price index and a long term interest rate.

But the relationship between US stock prices and the money supply although positive were

insignificant.

Ahmed, S. (2008) the study found causal relationship between the Macroeconomic variables and

stock indices in the long run. The study revealed that stock price movement were not only

dependent on behaviour of Macroeconomic variables but rather they acted as one of the

determinants.


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Sezgin Acikalin, R. A. (2008) Investigated the relationships between stock market returns and

domestic macroeconomic variables in the Turkish. The study concluded that the past moves of

ISE, GDP, exchange rate and current account balance have negative impacts on the current

changes in ISE index. There existed a clear effect of stock market on the moves of interest rate

but the net impact whether positive or negative is uncertain.

Hussain, et al (2009) Studied relationship between macroeconomic variables and stock prices

(Lahore Stock Exchange). In the long-run, inflation had a negative impact on stock prices while

Industrial production index, real affective exchange rate, and Money supply affected stock

returns positively. However, three month Treasury bills rate showed insignificant positive impact

on stock returns in the long-run.

Ali, et al (2009) studied the relationship between the macroeconomic and the stock exchange

prices taking the data from1990-2008. Macro-economic variables taken were inflation, exchange

rate, balance of trade, IIP and Karachi Stock Exchange was taken as taken as the stock prices. The

study found no causal relationship between the Macroeconomic indicators and the stock prices.

Uddin, M. L. (2009) investigated the interactions between stock prices and exchange rates in

three emerging countries named as Bangladesh, India and Pakistan. He considered average

monthly nominal exchange rates of US dollar in terms of Bangladeshi Taka, Indian Rupee and

Pakistani Rupee and monthly values of Dhaka Stock Exchange General Index, Bombay Stock

Exchange Index and Karachi Stock Exchange. The study showed cointegrating relationship

between stock prices and exchange rates. And no causal relationship was found between the

variables.

Reddy, Lokeswar(2010) observed that the RGDP, Inflation and the interest rate accounted for

96.5% explanatory variables for the movement of the stock prices of certain companies in Nifty

index. Moreover, Real Gross Domestic Product influenced the stock price movement the most.

He concluded that the govt should try to increase the GDP and Implement policies to increase it.

Policies that lead to moderate inflation and interest rate should be adopted.


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Kuwornu, J. K. (2011) The study found that there is a strong relationship between stock market

returns and three macroeconomic variables; inflation rate, exchange rate and interest rate.

Inflation rate had a positive significant effect, while exchange rate and Treasury bill rate had

negative significant influence on stock market returns

Tripathy, N. (2011) The study found strong inverse relationship between interest rate and stock

market, exchange rate and stock market. The study also reported unidirectional causality running

from international stock market to domestic stock market, interest rate, exchange rate and

inflation rate indicating sizeable influence in the stock market.

Kumar and Padhi(2012) investigated relationship between five macroeconomic variables,

namely, industrial production index, wholesale price index, money supply, treasury bills rates and

exchange rates found between the economic variables and the BSE Sensex Index between 1994

and 2011. They concluded that afore mentioned were co integrated and had a long run

equilibrium relationship.

Nai, P. K. (2012) The study found that in the long-run, the stock prices are positively related to

money supply and index of industrial production. The inflation was found to be negatively related

to stock price index. The short term interest rate and the real effective exchange rate were

insignificant determinant of stock prices.

P.Samveg(2012) took monthly data from 1991 to 2011 and concluded that the economic

variables and the stock market returns had a long run relationship and this relationship fluctuated

in the short run.

Attari I J, et al (2013) studied the relationship between the stock price movement in

Pakistan(Karachi stock exchange) and the exchange rate with respect to dollar and found a strong

correlation between them.

Parmar, C. (2013) The study revealed different relationship between selected economic

variables; both negative and positive.. The highest positive relationship was found between gold,

lowest in positive correlation is on Oil Rate, Inflation Rate, Reverse Repo Rate, and Consumer


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Price Index. The study found negative correlation with Salutatory Liquidity Ratio with Gold and

lowest negative correlation is on Inflation Rate with Exchange Rate.

Sangeeta Jauhari, H. Y. (2014) found that the macroeconomic variables do not have strong

bearing except that of inflation .The study revealed that the macroeconomic variables i.e. GDP,

savings, capital formation, Gold price, industrial output, Money supply, foreign investment

,Exchange rate ,WPI , interest rate have concurrence with the volatility of the Sensex index.

Further, the study found that the causation in this relationship is one way with the maximum

variables but with certain variables like money supply, exchange rate and FIIs shows the

bidirectional relationship with the Sensex.

Singh, P. (2014) Found that the exchange rate with respect to dollar had negative impact on stock

market. The money supply has positive impact on the stock market that reveals that lager money

in circulation has favorable impact on stock market. The inflow of foreign capital is value addition

to the market as it has significant impact over stock market. The performance of Indian Stock

market improves with the increase in the performance of industrial concerns and with the high

level performance of industrial sector of India.


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Chapter: 3

Research Methodology

3.1 Nature of study:

The study uses a quantitative approach to the study. The aim of the quantitative research is to

determine the relationship between the dependent and the independent variables. Both

descriptive and experimental approaches have been used.

3.2 Research Problem:

To find out the impact of macroeconomic variable like interest rate, inflation, industrial index of

production, money supply and exchange rate on stock market (Sensex) return the study has been

titled as ‘IMPACT OF ECONOMIC VARIABLES ON STOCK MARKET RETURN’.

3.3 Model

Linear multiple regression equation has been used to create the model. Prime lending rate, CPI,

IIP, M3 and Rupee/Dollar has been used as proxy for the economic variables. And BSE Sensex has

been used as proxy for stock market return. The model tries to create a model using the economic

variables as the independent variable and the Stock market return as the dependent variable and

tries to predict the return using the variables.


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Figure: 1 Factors influencing Sensex

To measure the impact of all the above variables on stock market return following regression

equation has been used:

SENSEX = ƒ (IR, IF, ER, IIP, MS)

IR= INTEREST RATE

IF=INFLATION

ER=EXCHANGE RATE

IIP=INDEX OF INDUSTRIAL PRODUCTION

MS=MONEY SUPPLY


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Explanatory Variables:

Prime lending rate

Prime lending rate is a term applied in many countries to a reference interest rate used by bank.

The term originally indicated the rate of interest at which bank lent money to favored customer,

i.e., those with high credibility, though this is no longer always the case. Some variable interest

rate may expressed as a percentage above or below prime rate. Generally, the Indian stock

markets has been affected by change in interest rate because it affect the business profits,

demand for goods and services in the economy, attractiveness of competing financial assets, in

compare of it, like shares, bonds and debentures, and other fixed interest sources, from where

companies use to finance their operational costs.

Consumer Price Index (CPI)

We have taken CPI as a proxy of Inflation in our study. Inflation is defined as a continuous increase

in price of goods and services over a certain period of time. In India, inflation is measure in term

of Consumer Price Index.

A moderate inflation in economy is supposed to be good as it attract investment and stimulate

aggregate demand in the economy. On the other hand, when inflation begins to move upward,

it is likely to bring tight monetary policies by central reserve bank to curb the inflation in the

economy which results in increase in the discount rate. It indicates that the cost of borrowing

increases which discourage investment and production activity in the economy. The decrease in

production result in fall of companies sales and profit which is finally reflected as decrease in

share price of those companies. So, it is said that an increase in inflation is negatively related to

equity prices.

Index of Industrial Production (IIP)


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Index of Industrial Production (IIP) refers to a number, which magnitude represents the status of

industrial sectors’ productions for a given period of time in compare of a previous period of time

or base year production.

Industrial Production Index is used as proxy to measure the growth rate in industrial sector of an

economy. It is an indicator of the economic development and the short-term economic analysis.

Industrial production presents a measure of overall economic activity in the economy and affects

stock prices through its influence on expected future cash flows. Thus, it is expected that an

increase in industrial production index is positively related to stock price. The IIP and stock prices

are positively related because increase in IIP results in increase in production of industrial sector

that leads to increase in the profit of industries and corporations. As dividend increases, it results

in increase of share prices, therefore, it is expected to have positive relationship between IIP and

share price according to economic theory.

Money Supply

The money supply refers to the total amount of monetary assets available in an economy at a

specific time. There are four measures of money supply in India which are denoted by M1, M2,

M3 and M4. Money supply data are recorded and published, by the central bank of the country.

In this study we consider M3 as a measure of supply of money in the economy.

Exchange Rate

An exchange rate is defined as a rate between two currencies at which one currency will be

exchanged in another country currency. It is also regarded as the value of one country’s currency

in terms of another currency like dollar in rupee term. Exchange rates are determined in the

foreign exchange market by two major market forces i.e., demand and supply of money by buyers

and sellers. In this study we consider Rupee/Dollar as exchange rate.

Nature of the data required: For the study, we used the quantitative data


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Data source: Secondary data has been used for the analysis. Data has been taken from RBI

database. The data for BSE Sensex has been obtained from bse.in.

Time period covered in the study: For the study, we have covered the period from fiscal year

2001-02 to 2013-14. Monthly data of BSE Sensex, Interest rate, Inflation, IIP, Money Supply and

exchange rate has been used.

Analysis tools

Multivariate analysis tools (like) correlation and regression has been used in the study.

Correlation analysis has been used to validate the individual relationship of the economic

variables with the stock market return. Regression analysis has been used to construct model

and collective strength of the economic variables in predicting the stock market return.

SPSS has been used for calculation.

Limitation of the study: The study covers only the time period of 2001-02 to 2013-14 and it is

applicable to only in Indian market based on the described factors. Correlation and Regression

measures only relationship and not causality.


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Chapter: 4

Analysis and inference

Correlation between the economic variables and the stock market return has been examined the

correlation to check the individual relationship and later collective impact of interest rate,

inflation, money supply, growth and exchange rate has been verified through linear multiple

regression.

Correlation:

Correlation is a statistical measure that indicates the extent to which two or more variables

fluctuate together. A positive correlation indicates the extent to which those variables increase

or decrease in parallel; a negative correlation indicates the extent to which one variable increases

as the other decreases. The value of correlation lies between 1 and -1. Closer is the value to 1 or

-1 it implies strong positive or negative relationship respectively.

When the fluctuation of one variable reliably predicts a similar fluctuation in another variable,

there’s often a tendency to think that means that the change in one causes the change in the

other. However, correlation does not imply causation. There may be, for example, an unknown

factor that influences both variables similarly.

Our finding regarding the correlation between the interest rate, inflation, money supply, IIP and

exchange rate with stock market return has been presented in the following table.


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Table number: 1 Result of Correlation Analysis

Correlations Analysis

SENSEX IR IF MS IIP ER

Pearson

Correlation

SENSEX 1.000 .839 -.796 .878 .393 .282

IR .839 1.000 -.637 .908 .158 .483

IF -.796 -.637 1.000 -.594 -.539 -.054

MS .878 .908 -.594 1.000 .081 .648

IIP .393 .158 -.539 .081 1.000 -.469

ER .282 .483 -.054 .648 -.469 1.000

The results of correlation analysis reveals following

1. Correlation between Sensex and Interest rate:

Interest rate and Sensex has a correlation of 0.839. Suggesting a strong positive

relationship. The finding is in contrast with all the literature reviewed.

2. Correlation between Sensex and Inflation:

Inflation has a correlation of -0.769 with the Sensex. Suggesting a strong negative

relationship between the variables. This is consistent with findings all the literature

reviews.

3. Correlation between Sensex and Money Supply: Money Supply has a correlation of 0.878.

Therefore it has a strong positive relationship with the stock market return. The finding is

consistent with Kuwornu, J. K. (2011).


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4. Correlation between Sensex and Growth:

Growth has a correlation of 0.39.Therefore it has a weak positive relationship with the

stock market return. This is consistent with the findings of Hussain, et al (2009).

5. Correlation between Sensex and Exchange Rate

Exchange rate has a correlation of 0.282. Therefore has the weakest but positive

relationship with the stock market return. This contradicts the result found by Attari J, et

al (2013) where he concluded that the exchange rate had a strong correlation with the

stock market return.

Regression Analysis:

Impact of economic variables i.e. Interest rate, Inflation, Money supply, Growth and Exchange

rate on stock market return has been assessed by linear multiple regression analysis. Statistical

approach to forecasting change in a dependent variable (sales revenue, for example) on the basis

of change in one or more independent variables (population and income, for example). Known

also as curve fitting or line fitting because a regression analysis equation can be used in fitting a

curve or line to data points, in a manner such that the differences in the distances of data points

from the curve or line are minimized. Relationships depicted in a regression analysis are,

however, associative only, and any cause-effect (causal) inference is purely subjective. Also called

regression method or regression technique.

First we check linearity and multicollinearity to validate the regression equation.


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Linearity

Figure: 2 check of linearity

From the above Normal P-P plot, we find that the residuals do not deviate much from the

goodness of fit line.

Multicollinearity:

It can be defined as when the predictors or the independent variables correlate so closely to

each other that it becomes difficult to tell which predictor is doing the actual predicting. From

Table no. 2, we find that the tolerance levels are above the thresholds of 0.1 and variance

inflation factors are less than 10. The visualization of the table (3) reveals that there is no

major problem of multicollinearity regarding various independent variables.


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Table No. :Model Summary

Model R R Square Adjusted R Square Std. Error of the

Estimate

1 .971a .943 .941 1515.19362088

a. Predictors: (Constant), ERATE, INFLATION, GROWTH, IRATE, MS

b. Dependent Variable: SENSEX

Table: 3: Coefficients

We have R value of 0.971. R Square of 0.943 and Adjusted R^2 of 0.941 which is very high and

acknowledges the dependency of stock market return on factors such as interest rate, inflation,

money supply, growth and exchange rate. This suggests that the independent variables can

predict the independent variable with the accuracy of 94.1% with the standard error of estimate

of 1515.1936.


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The empirical data shows that the economic variables i.e. interest rate, inflation, money supply,

growth and exchange rate explains 94.1% movement of Sensex. This is a very high number. Also

contrary to other study, interest rate has been found to have positive correlation with stock

market return. Money supply has the highest correlation with the stock market return and

exchange rate has the weakest. Inflation is the only variable with the negative correlation.

It is also interesting to find negative contribution in the regression equation by interest rate and

money supply which has a positive correlation. Inflation also has a negative contribution. Money

supply and growth has positive contribution with money supply having the highest contribution.

The above findings results in following regression equation:

SENSEX = 28366.996- 0.123(IR) -0.0237(IF) +1.076(MS) +.032(IIP)-0.353(ER) + - (1515.19362088)


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Chapter 5

Finding and suggestions

Findings:

This study examined the relationship between the five macroeconomic variables, namely,

interest rate, inflation, money supply, growth and exchange rate. Following are the findings of

the study:

1. It has been observed that the Stocks Market Return is highly dependent on Macro economic

factors such as interest rate, inflation, growth, money supply and exchange rate.

2. Interest rate, growth, money supply are positively correlated to Stock market return and

inflation and exchange rate are negatively correlated.

3. Money supply and growth make a positive contribution to the regression model and other

variables makes a negative contribution.

4. Money supply is most significant in understanding the stock market.

Suggestions:

From the study, I would make the following suggestion:

1. An investor who actively invests in the stock market should take macro-economic factors like.

Interest rate, inflation, money supply, growth and exchange rate. These are the vital factors that

will show the long term trend of the stocks and the economy of any country.

2. Currently India’s GDP is growing at a healthy pace and inflation is under control as a result of

this, there is an increased stock market return. But one needs to consider the depressed oil prices

which could spike any time.


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3. IIP is a major contributor to the stock market and therefore the policy makers should support

industrial growth.

4. Money supply and Inflation are major factors affecting stock markets, so the regulatory body

should try to control them through Repo and Reverse Repo rates

5. Exchange rate contains some information to forecast stock market performance. Therefore,

Reserve Bank of India should try to maintain a healthy exchange rate. Since Exchange rate also

has a bearing on other macro-economic factors such as foreign investment.


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EXPERIENCE)

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Annexure

Monthly data

(Sources: rbi.com/database; bse.in)

DATE BSE

INTEREST

RATE CPI M 3 IIP EXCH RATE

Apr-01 3519.16 11.5 448 13,505.98 160.4 46.75567

May-

01 3631.91 11.5 451 13,694.67

162.5 46.898772

Jun-01 3456.78 11.5 457 13,843.78 159.0 46.972248

Jul-01 3329.28 11.5 463 13,876.31 160.4 47.121652

Aug-01 3244.95 11.5 466 13,984.92 162.2 47.108333

Sep-01 2811.6 11.5 465 14,078.86 161.7 47.589111

Oct-01 2989.35 11.5 468 14,208.23 162.2 47.996628

Nov-01 3287.56 11.5 472 14,392.08 167.0 47.9843

Dec-01 3262.33 11.5 469 14,504.87 177.1 47.9048

Jan-02 3311.03 11.5 467 14,584.07 176.9 48.271182

Feb-02 3562.31 11.5 466 14,743.66 170.3 48.664774

Mar-02 3469.35 11.5 468 14,983.36 184.2 48.7337

Apr-02 3338.16 11 469 15,422.10 167.0 48.908614

May-

02 3125.73 11 472 16,052.06

169.2 49.00224

Jun-02 3244.7 11 476 16,094.53 166.2 48.963447

Jul-02 2987.65 11 481 16,141.59 171.8 48.787774

Aug-02 3181.23 11 484 16,306.87 172.2 48.603228

Sep-02 2991.36 11 485 16,403.76 171.8 48.44445

Oct-02 2949.32 11 487 16,589.03 173.6 48.362591


EXPERIENCE)

28

Nov-02 3228.82 10.75 489 16,735.16 173.9 48.251105

Dec-02 3377.28 10.75 484 16,819.91 188.0 48.176333

Jan-03 3250.38 10.75 483 16,937.25 188.8 47.937694

Feb-03 3283.66 10.75 484 17,072.83 182.2 47.740106

Mar-03 3048.72 10.75 487 17,179.36 195.0 47.664501

Apr-03 2959.79 10.75 493 17,705.34 174.0 47.403571

May-

03 3180.75 10.5 494 17,846.96

180.0 47.098325

Jun-03 3607.13 10.5 497 18,023.02 177.3 46.74645

Jul-03 3792.61 10.5 501 18,066.44 183.1 46.245625

Aug-03 4244.73 10.5 499 18,194.33 182.1 45.943763

Sep-03 4453.24 10.5 499 18,315.88 184.7 45.846923

Oct-03 4906.87 10.5 503 18,648.61 184.4 45.385

Nov-03 5044.82 10.5 504 18,749.05 188.2 45.486158

Dec-03 5838.96 10.5 502 18,962.89 202.0 45.564722

Jan-04 5695.67 10.25 504 19,226.68 203.9 45.432223

Feb-04 5667.51 10.25 504 19,593.88 197.3 45.235938

Mar-04 5590.6 10.25 504 20,056.54 210.7 45.05465

Apr-04 5655.09 10.25 504 20,581.84 194.3 43.820866

May-

04 4759.62 10.25 508 20,562.33

197.5 45.123948

Jun-04 4795.46 10.25 512 20,631.30 196.0 45.4705

Jul-04 5170.32 10.25 517 20,626.35 204.6 45.9965

Aug-04 5192.08 10.25 522 20,831.61 203.9 46.304

Sep-04 5583.61 10.25 523 20,895.61 208.7 45.860485

Oct-04 5672.27 10.25 526 21,132.98 209.7 43.929104

Nov-04 6234.29 10.25 525 21,196.11 209.1 45.110681

Dec-04 6602.69 10.25 521 21,446.93 226.9 43.760714


EXPERIENCE)

29

Jan-05 6555.94 10.25 526 22,062.20 225.2 43.735192

Feb-05 6713.86 10.25 525 22,151.25 216.1 43.6175

Mar-05 6492.82 10.25 525 22,456.53 241.5 43.638871

Apr-05 6154.44 10.25 529 23,314.06 210.3 43.696167

May-

05 6715.11 10.25 527 23,299.37

220.0 43.452903

Jun-05 7193.85 10.25 529 23,465.64 219.7 43.557322

Jul-05 7635.42 10.25 538 23,584.46 213.9 43.490185

Aug-05 7805.43 10.25 540 23,855.45 219.2 41.960666

Sep-05 8634.48 10.25 542 24,696.30 223.5 43.876667

Oct-05 7892.32 10.25 548 24,710.03 229.8 44.729667

Nov-05 8788.81 10.25 553 24,888.05 221.0 45.629655

Dec-05 9397.93 10.25 550 25,155.41 238.7 45.694401

Jan-06 9919.89 10.25 119 25,227.66 244.0 44.351481

Feb-06 10370.24 10.25 119 25,679.60 233.4 44.254711

Mar-06 11279.96 10.25 119 27,194.93 261.0 44.370555

Apr-06 12042.56 10.25 120 27,634.91 230.2 44.801205

May-

06 10398.61 10.75 121 27,702.92

243.6 45.253648

Jun-06 10609.25 10.75 123 27,745.55 240.5 45.893571

Jul-06 10743.88 10.75 124 28,273.00 241.4 46.384958

Aug-06 11699.05 11 124 28,848.00 241.8 46.491078

Sep-06 12454.42 11 125 29,416.57 250.9 46.119517

Oct-06 12961.9 11 127 29,363.87 242.0 45.438276

Nov-06 13696.31 11 127 29,817.72 256.2 44.811532

Dec-06 13786.91 11.5 127 30,058.30 272.9 44.6325

Jan-07 14090.92 11.5 127 30,672.75 274.7 44.30621

Feb-07 12938.09 12.25 128 31,388.37 261.2 44.123729


EXPERIENCE)

30

Mar-07 13072.1 12.25 127 33,100.38 304.2 44.014345

Apr-07 13872.37 12.75 128 33,064.35 258.3 42.276563

May-

07 14544.46 12.75 129 33,219.31

272.0 40.870669

Jun-07 14650.51 12.75 130 33,811.45 262.1 40.753571

Jul-07 15550.99 12.75 132 34,558.61 262.5 40.420952

Aug-07 15318.6 12.75 133 34,858.15 268.4 40.843125

Sep-07 17291.1 12.75 133 35,850.09 269.4 40.388438

Oct-07 19837.99 12.75 134 36,152.14 270.9 39.548261

Nov-07 19363.19 12.75 134 36,803.44 268.2 39.439205

Dec-07 20286.99 12.75 134 37,055.14 293.7 39.465375

Jan-08 17648.71 12.75 134 38,043.34 291.7 39.366685

Feb-08 17578.72 12.25 135 38,818.76 287.0 39.720893

Mar-08 15644.44 12.25 137 40,178.55 320.7 40.340833

Apr-08 17287.31 12.25 138 40,375.83 273.2 40.02689

May-

08 16415.57 12.25 139 40,956.91

283.9 42.047174

Jun-08 13461.6 12.75 140 41,071.33 280.0 42.842487

Jul-08 14355.75 12.75 143 41,489.87 280.6 43.001054

Aug-08 14564.53 13.75 145 42,261.71 273.4 43.108455

Sep-08 12860.43 13.75 146 42,835.14 288.3 45.544457

Oct-08 9788.06 13.75 148 43,579.37 271.8 50.055371

Nov-08 9092.72 13 148 43,888.40 278.0 49.842751

Dec-08 9647.31 13 147 44,439.93 295.2 49.906565

Jan-09 9424.24 12.25 148 45,747.79 297.3 49.043306

Feb-09 8891.61 12.25 148 46,645.70 287.6 49.179551

Mar-09 9708.5 12.25 148 47,947.75 323.5 51.113321

Apr-09 11403.25 12.25 150 49,017.15 277.7 50.03327


EXPERIENCE)

31

May-

09 14625.25 12.25 151 49,517.20

288.7 48.605316

Jun-09 14493.84 12.25 153 49,585.65 304.1 47.671474

Jul-09 15670.31 11.75 160 50,486.98 300.9 48.398962

Aug-09 15666.64 12.25 162 50,656.63 302.1 48.271903

Sep-09 17126.84 12.25 163 51,205.35 312.0 48.3977

Oct-09 15896.28 12.5 165 51,828.50 299.3 46.705242

Nov-09 16926.22 12.5 168 52,306.93 309.5 46.569183

Dec-09 17464.81 12.5 169 52,453.13 348.2 46.532468

Jan-10 16357.96 12.75 172 53,688.61 347.2 45.981774

Feb-10 16429.55 13 170 54,572.73 331.1 46.3145

Mar-10 17527.77 13 170 56,026.98 373.8 45.46429

Apr-10 17558.71 13.25 170 56,493.36 323.9 44.4562

May-

10 16944.63 14 172 57,029.14

323.9 45.669935

Jun-10 17700.9 14 174 57,105.80 325.9 46.4813

Jul-10 17868.29 14.25 178 58,423.83 346.3 46.719452

Aug-10 17971.12 14.75 178 58,544.53 324.3 46.491516

Sep-10 20069.12 14.75 179 58,992.66 327.3 46.007067

Oct-10 20032.34 14.75 181 60,804.76 335.4 44.359613

Nov-10 19521.25 14.75 182 60,905.75 320.7 44.8883

Dec-10 20509.09 14.75 185 62,251.81 357.2 45.096839

Jan-11 18327.76 14.75 188 62,559.84 361.2 45.326452

Feb-11 17823.4 14.75 185 63,667.14 343.2 45.400643

Mar-11 19445.22 14.75 185 65,041.16 402.8 44.903345

Apr-11 19135.96 14.75 186 66,494.04 338.1 44.295267

May-

11 18503.28 14.75 187 66,714.95

335.0 44.834903


EXPERIENCE)

32

Jun-11 18845.87 14.75 189 66,966.07 340.0 44.818533

Jul-11 18197.2 14.75 193 68,150.40 167.2 44.394613

Aug-11 16676.75 14.75 194 68,521.31 161.4 45.2939

Sep-11 16453.76 14.75 197 68,787.79 164.3 47.29188

Oct-11 17705.01 14.75 198 69,846.20 158.3 49.178077

Nov-11 16123.46 14.75 199 70,335.34 167.5 50.574833

Dec-11 15454.92 14.75 197 72,213.42 180.3 52.333333

Jan-12 17193.55 14.75 198 71,848.30 177.6 51.234633

Feb-12 17752.68 14.75 199 72,530.52 175.2 49.151346

Mar-12 17404.2 14.75 201 73,848.31 187.6 50.207433

Apr-12 17318.81 14.75 205 75,317.32 164.1 51.5655

May-

12 16218.53 14.75 206 75,952.27

170.3 54.350864

Jun-12 17429.98 14.75 208 77,562.28 168.0 55.977269

Jul-12 17236.18 14.75 212 77,666.67 167.1 55.352806

Aug-12 17429.56 14.75 214 78,178.42 164.7 55.513323

Sep-12 18762.74 14.5 215 78,165.92 163.1 54.489467

Oct-12 18505.38 14.5 217 79,165.08 171.6 53.03271

Nov-12 19339.9 14.5 218 79,931.52 165.8 54.7929

Dec-12 19426.71 14.5 219 80,336.62 179.3 54.621371

Jan-13 19894.98 14.5 221 81,157.95 182.0 54.314581

Feb-13 18861.54 14.45 223 81,740.83 176.2 53.8065

Mar-13 18835.77 14.45 224 83,898.19 194.2 54.418984

Apr-13 19504.18 14.45 226 85,029.03 166.5 54.361967

May-

13 19760.3 14.45 228 86,276.79

166.0 54.881226

Jun-13 19395.81 14.45 231 87,405.71 164.9 58.179167

Jul-13 19345.7 14.45 235 87,329.72 171.4 59.699774


EXPERIENCE)

33

Aug-13 18619.72 14.45 237 87,619.10 165.4 62.618742

Sep-13 19379.77 14.55 238 88,330.81 167.5 63.801724

Oct-13 21164.52 14.55 241 90,048.38 169.6 61.485081

Nov-13 20791.93 14.75 243 91,825.57 163.6 62.5894

Dec-13 21170.68 14.75 239 92,229.92 179.5 61.863581

Jan-14 20513.85 14.75 237 92,958.27 184.0 62.074613

Feb-14 21120.12 14.75 238 93,636.59 172.7 62.180696

Mar-14 22386.27 14.75 239 94,973.26 193.3 60.997097

impact of macro -economic indicators on stock market return (an indian experience)

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