shilpa bs-0347-exchange rates & stock prices
TRANSCRIPT
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
1/74
EXCHANGEE RATES & STOCK PRICE:ITS RELATIONSHIP IN INDDIAN
CONTEXT
! # ) 2 4 2 4 29 2 8 #
4
B C E F H I I P F H R H S I E T H P I E S E W B Y ` b I
d e f g i g q r t v d e f r f y q f f t v
0$677(552)%86,1(6666$''0,1,6775$$7,211OF BANGALORE UNIVERSITY
%
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
2/74
DECLARATION
I hereby declare that the research work embodied in the dissertation
entitled EXCHANGE RATES & STOCK PRICES: ITS
RELATIONSHIP IN INDIAN CONTEXT is the result of research work
carried out by me, under the guidance and supervision of Dr. Nagesh
Malavalli, Principal, M.P.Birla Institute of Management, Bangalore.
I also declare that this report has not been submitted to any other
University or Institute for award of any Degree or Diploma.
PLACE: (Shilpa. B S)
DATE: (Reg. No.
03XQCM6096)
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
3/74
DECLARATION
I hereby declare that the research work embodied in the dissertation
entitled EXCHANGE RATES & STOCK PRICES: ITS
RELATIONSHIP IN INDIAN CONTEXT is the result of research work
carried out by me, under the guidance and supervision of Dr. Nagesh
Malavalli, Principal, M.P.Birla Institute of Management, Bangalore.
I also declare that this report has not been submitted to any other
University or Institute for award of any Degree or Diploma.
PLACE: (Shilpa. B S)
DATE: (Reg. No.
03XQCM6096)
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
4/74
GUIDE CERTIFICATE
This is to certify that the Project titled EXCHANGE RATES &
STOCK PRICES: ITS RELATIONSHIP IN INDIAN CONTEXT
has been prepared by Ms. SHILPA B S bearing registration
number 03XQCM6096, under the guidance of Dr. Nagesh
Malavalli, M.P.Birla Institute of Management, Associate Bharatiya
Vidya Bhavan, Bangalore.
Place: Bangalore
Date: (Dr. Nagesh
Malavalli)
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
5/74
PRINCIPALS CERTIFICATE
This is to certify that the Project titled EXCHANGE RATES &
STOCK PRICES: ITS RELATIONSHIP IN INDIAN CONTEXT
has been prepared by Ms. SHILPA B S bearing registration
number 03XQCM6096, under the guidance of Dr. Nagesh
Malavalli, M.P.Birla Institute of Management, Associate Bharatiya
Vidya Bhavan, Bangalore.
Place: Bangalore Dr.NAGESHMALAVALLI
Date: (Principal)
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
6/74
ACKNOWLEDGEEMENT
The completion of the research would have been impossible without
the valuable contributions of people from the academics, family and
friends.
I hereby wish to express my sincere gratitude to all those who
supported me throughout the study.
I am thankful to Dr. NAGESH MALAVALLI, Principal, M.P.Birla
Institute of Management, Bangalore, for his valuable guidance,
academic and moral support which made thisreport a reality.
I am greatly thankful to Prof. T.V. Narasimha Rao (Finance) and
Prof. Santhanam (Statistics) for their support in completion of this
report.
I also thank my family members and friends whose support and
encourage has meant a lot to me personally and also for the
completion of the report.
(Shilpa. B.S)
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
7/74
CONTENTS
Chapter No. PARTICULARS Page No.
Abstract1. Introduction
o Backgroundo Purpose of the studyo Problem statemento Objectives of the studyo Hypothesiso Limitations of the studyo Theoretical frame work
1-111334445
2. Review of Literatureo Theoretical literatureo Empirical literature
12-151213
3. Methodology 16-20
4. Data analysis andInterpretation
21-45
5. Discussions and conclusionso Discussionso conclusions
46-504649
Bibliography
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
8/74
Annexure
o Sample data
List of Tables
Table No. PARTICULARS Page No.
1 Sensex companies 17
2 Nifty companies 18
3 CNX IT companies 19
4 Bankex companies 19
5 Import Index and Export Index companies 20
6 Correlation and T value for ER and Sensexfrom 2000- 2002
23
7 Correlation and T value for ER and Sensexfrom 2002- 2005
24
8 Correlation and T value for ER and Niftyfrom 2000- 2002
26
9 Correlation and T value for ER and Niftyfrom 2002- 2005
27
10 Correlation and T value for ER and CNX ITfrom 2000- 2002
29
11 Correlation and T value for ER and CNX ITfrom 2002- 2005
30
12 Correlation and T value for ER and Bankexfrom 2002- 2005
32
13 Correlation and T value for ER and Importfrom 2000- 2002
34
14 Correlation and T value for ER and Importfrom 2002- 2005
35
15 Correlation and T value for ER and Exportfrom 2000- 2002
37
16 Correlation and T value for ER and Exportfrom 2002- 2005
38
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
9/74
17 Correlation and T value for ER and ABB
from 2000- 2005
40
18 Correlation and T value for ER and BATA
from 2000- 2005
42
ABSTRACT
Stock market and foreign exchange market are the barometers of the
economy and both the markets are sensitive segments of the
economy. Any changes in the policies of the country are quickly
reflected in these markets. There are different factors, which affect the
stock markets like interest rates, company performance, future growth
prospects, inflation, political stability, exchange rates etc. There are
different factors, which affect the Exchange rates are like the flow of
capital between nations, inflation, interest rates, faith in government' s
ability to protect the value of currency, speculation etc. This study
attempts to analyze the interlinkages between exchange rates and
stock prices. The study is conducted by considering exchange rates
and various indices form 2000 to 2005. This is analyzed by using
statistical tools cross correlation both Zero order correlation and
correlation by taking 12 day lag. From the results it is clear that there is
no significant relationship between the exchange rates and index
values. Six Multinational companies were also considered in the study
but found that the share prices of the individual company are not at
affected by fluctuations in the exchange rates.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
10/74
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
11/74
Introduction
BackgroundTraditionally the stock market and the exchange market have
been regarded as sensitive segments of the financial market, as the
impact of any policy changes get quickly reflected in these two
markets. Rampant fluctuations of exchange rates and stock prices
have attracted a great deal of interest from policy makers and domestic
as well as foreign investors. Stock markets as well as exchange
markets are considered as the barometers of the state and health of
the economy through which the countrys exposure towards outside
world is most readily felt.
Globalization of world economies in general and liberalization of
financial sector reforms in India specifically ushered a change in the
financial architecture of the Indian economy. In the contemporary
scenario, the activities in the financial markets and their relationships
with the real sector have assumed significant importance. Since the
inception of the financial sector reforms in the beginning of 1990s, the
implementation of various reform measures, including a number of
structural and institutional changes in the different segments of the
financial markets, particularly since 1997, have brought in a dramatic
change in the functioning of the financial sector of the economy. The
advent of floating exchange rates, opening up of current account,
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
12/74
liberalization of capital account, reduction of customs duties, the
development of 24-hour screen based global trading, the increased use
of national currencies outside the country of issue and innovations in
internationally traded financial products have led to the cross country
linkages of capital markets and international integration of domestic
economy. Altogether, the whole lot of institutional reforms, introduction
of new instruments, change in procedures, widening of network of
participants, influenced a reexamination of the relationship between the
stock market and the foreign exchange sector of India.
In the present scenario, interesting results are emerging
particularly for the developing countries where the markets are
experiencing new relationships between money markets, forex
markets, capital markets, international events, oil prices, WTO
agreements etc which were not perceived earlier. The analysis on
stock markets is important as it is considered as the most sensitive
segment of the economy and through this segment the countrys
exposure to the outer world is most readily felt. The impact of
fluctuation in exchange rate on domestic companies, companies
importing or exporting and on multi national corporations with the
degree of exposure is increasing in each case respectively. The
movements in exchange rate indirectly affect the value and hence the
stock prices of these companies. The value of the company is affected
due to the forex exposures namely Transaction exposures, translation
exposure and economic exposure.
An exchange rate has two effects on stock prices, a direct effect
through Multi National Firms and an indirect effect through domestic
firms. In case of Multi National Firms involved in exports, a change in
rate will change the demand of its product in the international market,
which ultimately reflects in its B/S as profit or loss. Once the profit or
loss is declared, the stock price will also change for a domestic firm.
On the other hand, currency devaluation could either raise or decrease
a firms stock prices. This depends on the nature of the firms
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
13/74
operations. A domestic firm that exports part of its output will benefit
directly from devaluation due to an increase in demand for its output.
As higher sales result in higher profits, local currency devaluation will
cause firm stock price to rise in general. On the other hand, if the firm
is a user of imported inputs, currency devaluation will raise cost and
lower profits. Thus, it will decrease the firms stock price.
Purpose of the StudyTheory says that exchange rates should have a direct impact on the
companies with heavy import or export activities and thus affecting the
profitability and hence the stock prices. The impact of fluctuation in
exchange rates on domestic companies, companies importing or
exporting and on multi national corporations with the degree of
exposure is increasing in each case respectively. The movements in
exchange rate indirectly affect the value and hence the stock prices of
these companies, to check for the relevance of this effect, the test has
been undertaken. In an increasingly complex scenario of the financial
world, it is of paramount importance for the researchers, practitioners,
market players and policy makers to understand the working of the
economic and financial system and assimilate the mutual interlinkages
between the stock and exchange markets in forming their expectations
about the future policy and financial variables. The study would be
helpful to all investors, speculators, arbitragers, brokers, dealers etc as
the foreign exchange rates can also be considered as one of the
factors, which affect the stock prices and in the same way stock prices
as a factor affecting exchange rates.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
14/74
Problem sttatementThere are various studies have been done to study the relationship
between exchange rates and stock prices by taking various indices.
This study explores the evidence of relationship between exchange
rates and stock prices and also lead lag relationship between
exchange rates and stock prices.
Objectives of tthe study To analyze the relationship between stock market and exchange
market
To find out whether the relationship changes with the different
indices
To find out which variable is leading and which variable is
lagging.
Hypothesis of the study
Hypothesis 1
H0: There is no significant relation between stock prices and
exchange rates
H1: There is significant relation between stock prices and exchange
rates
Hypothesis 2
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
15/74
H0: There is no significant lead and lag relationship between stock
prices and
exchange rates
H1: There is significant lead and lag relationship between stock prices
and
exchange rates
Limitations of the study
The study is limited to six indices and six Multi National
Companies
The study is limited to Indian rupee versus US dollar only
The study is limited to a period of five years
Theoretical Framework
The Indian Financial System
The Indian financial system consists of many institutions,
instruments and markets. Financial instruments range from the
common coins, currency notes and cheques, to the more exotic futures
swaps of high finance.
Financial Markets
Generally speaking, there is no specific place or location to
indicate financial markets. Wherever a financial transaction takes
place, it is deemed to have taken place in the financial market. Hence
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
16/74
financial markets are pervasive in nature since financial transactions
are themselves very pervasive throughout the economic system.
However, financial markets can be referred to as those centres
and arrangements which facilitate buying and selling of financial
assets, claims and services. Sometimes, we do find the existence of a
specific place or location for a financial market as in the case of stock
exchange.
Classification of financial markets
Financial markets can be classified as
i) Unorganized Markets
In these markets there a number of money lenders, indigenous
bankers, traders etc. who lend money to the public.
ii) Organized Market
In organized markets, there are standardized rules and
regulations governing their financial dealings. There is also a high
degree of institutionalization and instrumentalization. These markets
are subject to strict supervision and control by the RBI or other
regulatory bodies.
Organized markets can be further divided into capital market and
Money market.
Capital market
Capital market is a market for financial assets which have a long or
definite maturity.
Which can be further divided into
Industrial Securities Market
Government Securities Market
Long Term Loans Market
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
17/74
Industrial Securities Market
It is a market where industrial concerns raise their capital or debt
by issuing appropriate Instruments. It can be subdivided into two. They
are
Primary Market or New Issues Market
Primary market is a market for new issues or new
financial claims. Hence, it is also called as New Issues Market.
The primary market deals with those securities which are issued
to the public for the first time
Secondary Market or Stock Exchange
Secondary market is a market for secondary sale of
securities. In other words, securities which have already passed
through the new issues market are traded in this market. Such
securities are listed in stock exchange and it provides a
continuous and regular market for buying and selling of
securities. This market consists of all stock exchanges
recognized by the government of India.
Importance of Capital Market
Absence of capital market serves as a deterrent factor to
capital formation and economic growth. Resources would
remain idle if finances are not funneled through capital market.
It serves as an important source for the productive use of
the economys savings.
It provides incentives to saving and facilitates capital
formation by offering suitable rates of interest as the price
of the capital
It provides avenue for investors to invest in financial assets.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
18/74
It facilitates increase in production and productivity in the
economy and thus enhances the economic welfare of the
society.
A healthy market consisting of expert intermediaries
promotes stability in the value of securities representing
capital funds.
It serves as an important source for technological
upgradation in the industrial sector by utilizing the funds
invested by the public.
Foreign Exchange Market
The foreign exchange market is the market in which currencies
of various countries are bought and sold against each other. The
foreign exchange market is an over-the-counter market.
Geographically, the foreign exchange markets span all time zones from
New Zealand to the West Coast of United States of America.The retail market for foreign exchange deals with transactions
involving travelers and tourists exchanging one currency for another in
the form of currency notes or travelers cheques. The wholesale marketoften referred to as the interbank market is entirely different and the
participants in this market are commercial banks, corporations and
central banks.The foreign exchange market provides the physical and
institutional structure through which the money of one country is
exchanged for that of another country, the rate of exchange between
currencies is determined, and foreign exchange transactions arephysically completed.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
19/74
Foreign exchange market spans the globe, with prices moving
currencies trading 24 hours a day.
Foreign exchange means the money of a foreign country; that is,
foreign currency bank balances, banknotes, drafts etc.
A Foreign exchange transaction is an agreement between a buyer and
seller that a fixed amount of one currency will be delivered for some
other currency at a specified rate.
A Foreign exchange rate is the price of one currency expressed in
terms of another currency.
A Foreign exchange quotation is a statement of willingness to buy or
sell currency at an announced price.
Functions of foreign exchange market
The foreign exchange market is the mechanism by which participants
Transfer purchasing power between countries,
Obtain or provide credit for international trade transactions, and
Minimize exposure to the risks of exchange rate changes
Foreign Exchange Market participants
The foreign exchange market consists of two tiers: the interbank orwholesale market and the client or retail market.
Five broad categories of participants operate within these two tiers:
Bank and nonblank foreign exchange dealers
Banks and a few nonblank foreign exchange dealers
operate in both the interbank and client markets. They profit
from buying foreign exchange at a bid price and reselling it at a
slightly higher ask price. Dealers in the foreign exchange
departments of large international banks often function as
market makers.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
20/74
Currency trading is quite profitable for commercial and
investment banks. Small to medium sized banks are likely to
participate but not as market makers in the interbank market.
Instead of maintaining significant inventory positions, they buy
from and sell to large banks to offset retail transactions with their
own customers.
Individuals and firms conducting commercial or investment
transactions
Importers and exporters, international portfolio investors,
Multi National Enterprises, tourists, and others use the foreign
exchange market to facilitate execution of commercial or
investment transactions. Some of these participants use the
market to hedge foreign exchange risk.
Speculators and arbitragers
Speculators and arbitragers seek to profit from trading in
the market itself. They operate in their own interest, without a
need or obligation to serve clients or to ensure a continuous
market. A large proportion of speculation and arbitrage is
conducted on behalf of major banks by traders employed by
those banks. Thus banks act both as exchange dealers and as
speculators and arbitrages.
Central banks and treasuries
Central bank and treasuries use the market to acquire or
spend their countrys foreign exchange reserves as well as to
influence the price at which their own currency is traded. They
may act to support the value of their own currency because of
policies adopted at the national level or because of
commitments entered into through membership in joint float
agreements.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
21/74
Foreign exchange brokers
Foreign exchange brokers are agents who facilitate
trading between dealers. Brokers charge small commission for
the service provided to dealers. They maintain instant access to
hundreds of dealers world wide via open telephone lines.
Foreign exchange transactions
Transactions within the foreign exchange market are executed
either on a spot basis, requiring settlement two days after the
transaction, or on a forward or swap basis, which requires
settlement at some designated future date.
Quotations can be direct or indirect.
A direct quote is the home currency price of a unit of foreign
currency. Indirect quote is the home currency price of a unit of
home currency.
To be successful in the foreign exchange markets, one has to
anticipate price changes by keeping a close eye on world events and
currency fluctuations.
Exchange rates are determined by the dual forces of demand andsupply. Various factors affect these, which in turn affect the exchange
rates:
The business environment: Positive indications (in terms of govt.
policy, competitive advantages, market size etc) increase the demand
of the currency, as more and more entities want to invest there. This
investment is for two basic motives purely business motive, and for
risk diversification purposes. Foreign direct investment is for taking
advantage of the comparative advantages and the economies of scale.
Portfolio investment is mainly done for risk diversification purposes.
Stock market: The major stock indices also have a correlation with the
currency rates. Three major forces affect the indices:
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
22/74
1) Corporate earnings, forecast and actual;
2) Interest rate expectations and
3) Global considerations.
Consequently, these factors channel their way through the local
currency.
Political Factors: All exchange rates are susceptible to political
instability and anticipations about the new ruling party.
Economic Data: Economic data items like labour report (payrolls,
unemployment rate and average hourly earnings), CPI, PPI, GDP,
international trade, productivity, industrial production, consumer
confidence etc. also affect the exchange rate fluctuations.
Confidence in a currency is the greatest determinant of the exchange
rates. Decisions are made keeping in mind the future developments
that may affect the currency. And any adverse sentiments have a
contagion effect.
1) The sudden discovery that reserves is less than previously believed
2) Unexpected devaluation (often in part for its role in signaling the
depletion of reserves); and,
3) Contagion from neighboring countries, in a situation of perceived
vulnerability (low reserves, high short-term debt, overvalued currency).
Government influence: A country' s government may reduce the
growth in the money supply, raising interest rates, and encouraging
demand for its currency. Or a government may simply buy or sell forex
to maintain stability or to support either exporters or importers.
Productivity of an economy: An increase in productivity of an
economy tends to impact exchange rates. Its affects are more
prominent if the increase is in the traded sector.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
23/74
Exchange rates are also influenced by the flow of capital between
nations, inflation, interest rates, faith in government' s ability to protect
the value of currency, speculation, rumors and even human error.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
24/74
REVIEW OF LLITERATURE
THEORETICAL LITERATURE
Foreign exchange and capital market how are they possibly
interlinked?
The possible interlinkages between stock prices and exchange
rates suggested by several arguments/hypothesis, particularly those
identified in goods market approaches explaining likely impact of
exchange rate on stock prices and portfolio balance approaches forjustifying impact in reverse direction.
The arguments provided in goods market approachesflow that,
as many companies borrow in foreign currencies to fund their
operations, a change in exchange rate affects the cost of funds and
value of earnings of many firms, which in turn affect the
competitiveness of a firm and its stock prices a depreciation
(appreciation) of local currency makes exporting goods more (less)attractive to foreigners, which results in increase (decrease) of foreign
demand for goods, which in turn raises (reduces) the revenue of the
firm, value of firms appreciates(depreciates) and thus stock prices
increase (decrease). The sensitivity of an importing firm to a change in
exchange rate is just opposite to that of an exporting firm. Therefore,
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
25/74
on a macro basis the impact of exchange rate fluctuations on stock
market seems to depend on both the importance of a countrys
international trade in its economy and the degree of the trade
imbalance.
To complete the linkage, influence in reverse direction can be
justified by portfolio balance approaches under the exchange rate
regime that allows exchange rate to be determined by market
mechanism (i.e. the demand and supply conditions). A glooming stock
market would attract capital flows from foreign investors, which may
cause an increase in the demand for a countrys currency. Thus, local
currency appreciates.
The reverse would happen in case of fallen stock prices where
the investors would try to sell their stocks to avoid further losses and
would convert their money in to foreign currency to move out of the
country. There would be demand for foreign currency in exchange of
local currency. As a result rising (declining) stock prices would lead to
an appreciation (depreciation) in local currency. Moreover, foreign
investment in domestic equities could increase over time due to
benefits of international diversification that foreign investors would gain.
Further more, movements in stock prices may influence exchange
rates (and money demand) because investors wealth (and liquidity
demand) could depend on the performance of the stock market.
EMPIRICAL LITERATURE
Frank and Youngs (1972) was the first study to examine the
impact of exchange rate changes on stock markets. The study
investigated the relationship between stock prices and exchange rates,
by using six different exchange rates and found no relationship
between these two financial variables.
Solnik (1987), employing regression analysis on monthly and
quarterly data for eight industrialized countries from 1973 to 1983, finds
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
26/74
a negative relationship between real domestic stock returns and real
exchange rate movements. However, for monthly data over 197983,
he observes a weak but positive relation between the two variables.
Jorion (1988) attempted to analyze and compare the empirical
distribution of returns in the stock market and in the foreign exchange
market by using the maximum likelihood estimation procedure and
ARCH model in daily data of exchange rates and stock returns
spanning from June 1973 to December 1985. The study found that
exchange rates display significant jump components, which are more
manifest than in the stock market. The statistical
analysis of the study for the foreign exchange market and stock market
suggests there are important differences in the structures of these
markets.
Alok Kumar Mishra in his article Stock Market and Foreign
Exchange Market in India: Are they Related? attempts to examine
whether stock market and foreign exchange markets are related to
each other or not. The study uses Grangers Causality test and Vector
Auto Regression technique on monthly stock return, exchange rate,
interest rate and demand for money for the period April 1992 to March
2002. The major findings of the study are
(a) There exists a unidirectional causality between the exchange rate
and interest rate and between the exchange rate return
and demand for money;
(b) There is no Grangers causality between the exchange rate
return and stock return.
Through Vector Auto Regression modeling, the study confirms that
though stock return, exchange rate return, the demand for money and
interest rate are related to each other but any consistent relationship
doesnt exist between them. The forecast error variance decomposition
further evidences that
(a) The exchange rate return affects the demand for money,
(b) The interest rate causes exchange rate return change,
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
27/74
(c) The exchange rate return affects the stock return,
(d) The demand for money affects stock return,
(e) The interest rate affects the stock return, and
(f) The demand for money affects the interest rate.
Apte (2001) investigated the relationship between the volatility of
the stock
market and the nominal exchange rate of India by using the EGARCH
specifications on the daily closing USD/INR exchange rate, BSE 30
(Sensex) and NIFTY-50 over the period 1991 to 2000. The study
suggests that there appears to be a spillover from the foreign exchange
market to the stock market but not the reverse.
Bhattacharya and Mukharjee (2002) studied the nature of causal
relation between the stock market, exchange rate, foreign exchange
reserves and value of trade balance in India from 1990 to 2001 by
applying the co-integration and long-run Granger Non-causality tests.
The study suggests that there is no causal linkage between stock
prices and the three variables under consideration.
To examine the dynamic linkages between the foreign exchange
and stock markets for India, Nath and Samanta (2003) employed the
Granger causality test on daily data during the period March 1993 to
December 2002. The empirical findings of the study suggest that these
two markets did not have any causal relationship. When the study
extended its analysis to verify if liberalization in both the markets
brought them together, it found no significant causal relationship
between the exchange rate and stock price movements, except for the
years 1993, 2001 and 2002 during when a unidirectional causal
influence from stock index return to return in forex market is detected
and a very mild causal influence in the reverse direction is found in
some years such as 1997 and 2002.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
28/74
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
29/74
MethodologyyStudy Design
a) Study Type:The study type is analytical, quantitative and historical.
Analytical because facts and existing information is used for the
analysis,
Quantitativeas relationship is examined by expressing variables in
measurable terms and also Historicalas the historical information isused for analysis and interpretation.
b) Study population: population is the entire stock market and all
indices and exchange rates of rupee versus currencies of all the
countries.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
30/74
c) Sampling frame: Sampling Frame would be Indian stock market and
rupee versus most traded currencies.
d) Sample: Sample chosen is daily closing values of BSE Sensex,
CNX Nifty, CNX IT, BSE Bankex, created Import index and an
export index and exchange rates of Rupee/Dollar from 1-1-2000 to
31-5-2005.
e) Sampling technique: Deliberate sampling is used because only
particular units are selected from the sampling frame. Such a
selection is undertaken as these units represent the population in a
better way and reflect better relationshipwith the other variable.
Data gathering procedures and instruments:
Data: Historical daily share prices and information about their forex
exposure. Historical daily closing values of BSE Sensex, CNX Nifty,
CNX IT, BSE Bankex, import index and export index. Direct and
indirect quotes of rupee per dollar
Data Source: Historical share prices of the sample companies andthe index points for the period has been taken from the database of
Capital Market Publishers (India) Ltd., Capitaline 2000 and exchange
rates information has been taken from www.exchangerate.com
An exchange rate has two effects on share prices, a direct effect
through Multi National Firms and indirect effect through domestic
firms.
Even though exchange rate has effect on stock prices of
companies, the study has been conducted by considering different
indices because index values are nothing but the weighted average
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
31/74
of different companys share prices and indices are the proxies of
stock market.
BSE Sensex is considered as it is a barometer of the state of the
economy. It follows the free float methodology. The companies in
the Sensex are domestic companies, so it has been taken to see
the indirect effect of exchange rates.
Table No.1: BSE SENSEX COMPANIES
1 Associated Cement Companies Ltd. 16 I T C Ltd
2 Bajaj Auto 17 Infosys Technologies Ltd.
3 Bharti Televentures 18 Maruthi Udyog4 Bharat Heavy Electricals Ltd. 19 Larsen & Toubro Ltd.
5 Cipla Ltd. 20 ONGC
6 Dr.Reddy' s Laboratories Ltd. 21 Ranbaxy Laboratories Ltd.
7 Grasim Industries Ltd. 22 Reliance Energy
8 Gujarat Ambuja Cements Ltd. 23 Reliance
9 Herohonda Motors 24 Satyam Computers
10 Hindalco 25 State Bank Of India
11 Hindustan Lever Ltd. 26 Tata Iron And Steel Co. Ltd.
12 Hindustan Petroleum Corporation Ltd 27 Tata Motors
13 Housing Development Finance Co 28 Tata Power
14 HDFC Bank 29 Wipro Ltd15 ICICI Bank 30 Zee Telefilms Ltd
CNX Nifty has been taken because CNX Nifty and BSE Sensex are
considered as trust worthy indices of India, to see whether both the
indices move in the same direction or not.
Table No.2: CNX NIFTY COMPANIES
1 ABB Ltd. 26 Larsen & Toubro Ltd.
2Associated Cement CompaniesLtd. 27 Mahanagar Telephone Nigam Ltd.
3 Bajaj Auto Ltd. 28 Mahindra & Mahindra Ltd.4 Bharat Heavy Electricals Ltd. 29 Maruti Udyog Ltd.5 Bharat Petroleum Corporation Ltd. 30 National Aluminium Co. Ltd.6 Bharti Tele-Ventures Ltd. 31 Oil & Natural Gas Corporation Ltd.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
32/74
7 Cipla Ltd. 32 Oriental Bank of Commerce8 Colgate-Palmolive (India) Ltd. 33 Punjab National Bank9 Dabur India Ltd. 34 Ranbaxy Laboratories Ltd.10 Dr. Reddy' s Laboratories Ltd. 35 Reliance Energy Ltd.11 GAIL (India) Ltd. 36 Reliance Industries Ltd.
12
Glaxosmithkline Pharmaceuticals
Ltd. 37 Satyam Computer Services Ltd.13 Grasim Industries Ltd. 38 Shipping Corporation of India Ltd.14 Gujarat Ambuja Cements Ltd. 39 State Bank of India15 HCL Technologies Ltd. 40 Steel Authority of India Ltd.
16 HDFC Bank Ltd. 41Sun Pharmaceutical IndustriesLtd.
17 Hero Honda Motors Ltd. 42 Tata Chemicals Ltd.18 Hindalco Industries Ltd. 43 Tata Consultancy Services Ltd.19 Hindustan Lever Ltd. 44 Tata Iron & Steel Co. Ltd.
20Hindustan Petroleum CorporationLtd. 45 Tata Motors Ltd.
21Housing Development FinanceCorporation Ltd. 46 Tata Power Co. Ltd.
22 I T C Ltd. 47 Tata Tea Ltd.23 ICICI Bank Ltd. 48 Videsh Sanchar Nigam Ltd.
24Indian Petrochemicals CorporationLtd. 49 Wipro Ltd.
25 Infosys Technologies Ltd. 50 Zee Telefilms Ltd.
CNX IT constitutes 20 IT companies. These companies will have more
forex exposure and most of the transactions are undertaken in foreign
currencies and these companies undertake many international
projects. So, the study attempts to see how IT stocks affect due to
exchange rate fluctuations.
Table No.3:CNX-IT COMPANIES1. CMC Ltd. 11. Mastek Ltd.2. Flextronics Software Systems Ltd. 12. Moser Baer India Ltd.3. GTL Ltd. 13. Mphasis BFL Ltd.4. HCL Infosystems Ltd. 14. Patni Computer Systems Ltd.5. HCL Technologies Ltd. 15. Polaris Software Lab Ltd.6. Hexaware Technologies Ltd. 16. Rolta India Ltd.
7. Hinduja TMT Ltd. 17. Satyam Computer Services Ltd.8. I-Flex Solutions Ltd. 18. Tata Elxsi Ltd.9. iGate Global Solutions Ltd. 19. Tata Consultancy Services Ltd.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
33/74
10. Infosys Technologies Ltd. 20. Wipro Ltd.
Another index is BSE Bankex, as the banks are the major participants
in foreign exchange market, banks index i.e. Bankex has been
considered.
Table No.4: BANKEX INDEX COMPANIES
1 Allahabad bank Ltd
2 Andhra Bank3 Bank of Baroda4 Bank Of India
5 Canara Bank6 HDFC Bank Ltd.7 ICICI Bank Ltd.8 Indian Overseas Bank9 Kotak Mahindra Bank Ltd.10 Oriental Bank of Commerce
11 Punjab National Bank12 State Bank of India13 Union Bank Ltd.14 UTI Bank Ltd.15 Vijaya Bank
According to theory exchange rates should have a direct impact on the
companies with heavy import or export activities. So, two special
indices are constructed by considering companies which have large
amount of exports or imports.
Steps in the process of constructing index:
The companies which had good amount of exports or imports
were picked up
The criteria for selecting the companies is, for exporting
company percentage of exports to sales revenue should be
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
34/74
greater than 30% and for importing companies percentage of
imports to purchases should be greater than 30%
The best of 15 companies each having more than 30%
according criteria are used for constructing index
All the companies are listed in BSE were taken
Finally, the indices are constructed by taking simple average of
closing share prices of these 15 companies
Table No.5: IMPORT AND EXPORT INDEX COMPANIES
IMPORT COMPANIES EXPORT COMPANIES
1 Associated Cement Company Ltd. 1 Bajaj Auto Ltd2 Bharat Heavey Electricals Ltd 2 CIPLA3 Grasim Cements Ltd 3 Indian Petrochemicals Corporation Ltd.
4 Gujrat Ambuja Cements Ltd. 4 INFOSYS Technologies Ltd.5 Hero Honda Motors 5 National Aluminium Company Ltd.6 HINDALCO 6 SATYAM Computers7 Hindusthan Lever Ltd 7 WIPRO Ltd8 Hidustan Petroleum Corporation Ltd 8 Zee Telefilms9 ITC Ltd 9 Arvind Mills Ltd10 RANBAXY Laboratories Ltd 10 Kesoram Industries Ltd11 DR.Reddys Laboratories Ltd 11 Tata Motors Ltd12 Relliance Industries 12 Tata Tea Ltd13 Tata Iron And Steel Company 13 Videsh Sanchar Nigam Ltd.14 Tata Power Ltd 14 Nahar Spinning Mills Ltd15 Micro Inks Ltd 15 Gail
In the foreign exchange market, the Indian rupee per US dollar is
considered. As most of the transactions are carried in terms of $
and $ is considered as Transaction Currency.
The daily returns in foreign exchange and indices are calculated by
taking Log Normal of P1/P0. These returns represent continuously
compounded returns in respective markets.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
35/74
Data Analysis and Interpretation
The data has been analyzed by using cross correlation. The
correlation has been calculated for zero date and by taking lag length
of 12 days. The analysis has been done by taking exchange rate as
independent variable and its impact on index or company share price
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
36/74
for 12 lags. In the similar way, index is taken as independent variable
and its impact on exchange rate for 12 lags.
Cross correlation
Cross correlation is a standard method of estimating the degree
to which two series are correlated. Consider two series x(i) and y(i)
where i=0,1,2...N-1. The cross correlation r at delay d is defined as
Where mx and my are the means of the corresponding series. If
the above is computed for all delays d=0,1,2,...N-1 then it results in a
cross correlation series of twice the length as the original series.
There is the issue of what to do when the index into the series is
less than 0 or greater than or equal to the number of points. (i-d < 0 or
i-d >= N) The most common approaches are to either ignore these
points or assuming the series x and y are zero for i < 0 and i >= N. In
many signal processing applications the series is assumed to be
circular in which case the out of range indexes are "wrapped" back
within range, ie: x(-1) = x(N-1), x(N+5) = x(5) etc.
Abbreviations
ER: Exchange rate
Sensex: BSE Sensex
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
37/74
Nifty: CNX Nifty
Import: Import Index
Export: Export Index
ABB: Asea Brown Boveri Ltd
BATA: Bata India Ltd.
HLL: Hindustan Lever Ltd.
MICO: Machine Industries Company Ltd.
Glaxo: Glaxo Smithkline Pharmaceuticals Ltd.
Colgate: Colgate Palmolive (India) Ltd.
LEADING LAGGING
LAGGING LEADING
NEGATIVELAG
INDEX- ER
ER - INDEX
POSITIVELAG
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
38/74
Table No. 6 Correlation and T values of ER and SENSEX for the period 2000 to 2005I half of 2000 II half of 2000 I half of 2001 II half of 2001 I half of 2002
Lag Correlation Correlation Correlation Correlation Correlation
-120.042(0.438)
-0.011(0.117)
0.126(1.326)
-0.011(0.110)
0.038(0.400)
-110.033(0.344)
0.087(0.935)
-0.093(0.979)
0.123(1.242)
-0.001(0.011)
-100.085(0.895)
0.099(1.065)
-0.017(0.181)
0.108(1.091)
0.012(0.128)
-90.003(0.032)
0.148(1.609)
-0.235(2.500)*
0.051(0.520)
0.11(1.170)
-8-0.038(0.404)
-0.081(0.880)
-0.121(1.287)
-0.022(0.224)
0.063(0.677)
-70.092(0.979)
0.116(1.261)
0.101(1.086)
0.103(1.062)
0.154(1.656)
-60.064(0.681)
0.066(0.725)
0.072(0.774)
-0.039(0.402)
0.134(1.457)
-50.182(1.957)
0.102(1.121)
0.069(0.750)
-0.158(1.646)
0.028(0.304)
-40.065(0.699)
-0.205(2.253)*
0.023(0.250)
-0.176(1.833)
-0.108(1.174)
-3
0.119
(1.293)
0.037
(0.411)
0.209
(2.272)*
-0.009
(0.095)
0.032
(0.352)
-20.011(0.120)
-0.2(2.222)*
0.111(1.220)
-0.121(1.274)
0.198(2.176)*
-10.055(0.598)
-0.002(0.022)
-0.205(2.253)*
-0.409(4.351)*
0.01(0.110)
00.002(0.022)
-0.162(1.820)
-0.076(0.835)
-0.328(3.489)*
-0.068(0.756)
10.071(0.772)
-0.055(0.618)
-0.169(1.857)
-0.307(3.266)*
-0.002(0.022)
2-0.096(1.043)
0.123(1.367)
0.012(0.132)
-0.079(0.832)
0.023(0.253)
30.136(1.478)
-0.091(1.011)
-0.004(0.043)
-0.169(1.779)
0.094(1.033)
4-0.029(0.312)
0.044(0.484)
0.019(0.207)
-0.057(0.594)
-0.084(0.913)
5 -0.071(0.763) -0.03(0.330) -0.024(0.261) -0.139(1.448) -0.03(0.326)
6-0.086(0.915)
0.069(0.758)
-0.067(0.720)
-0.052(0.536)
-0.087(0.946)
7-0.049(0.521)
-0.275(2.989)*
0.008(0.086)
-0.014(0.144)
-0.084(0.903)
8-0.147(1.564)
0.021(0.228)
-0.035(0.372)
-0.051(0.520)
-0.031(0.333)
90.01(0.105)
-0.149(1.620)
-0.075(0.798)
-0.028(0.286)
-0.039(0.415)
10-0.067(0.705)
0.074(0.796)
0.009(0.096)
-0.136(1.374)
-0.05(0.532)
11-0.116(1.208)
-0.163(1.753)
0.033(0.347)
-0.054(0.545)
-0.042(0.447)
12-0.174(1.813)
-0.034(0.362)
-0.044(0.463)
0.034(0.340)
0.04(0.421)
Numbers with in brackets indicate T values = correlation/ standard error
* indicates t values greater than 2, @ 5% significance level
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
39/74
Table No. 7 Correlation and T values of ER and SENSEX for the period
2002 to 2005
II half 2002 I half 2003 II half 2003 I half 2004 II half 2004 I half 2005
Lag Correlation Correlation Correlation Correlation Correlation Correlation
-12-0.047(0.495)
0.024(0.247)
-0.024(0.255)
-0.006(0.063)
-0.031(0.326)
0.14(1.273)
-11
0.109
(1.147)
0.085
(0.885)
0.085
(0.914)
-0.09
(0.947)
-0.013
(0.137)
-0.063
(0.573)
-10-0.07(0.745)
-0.111(1.156)
-0.158(1.699)
-0.039(0.411)
0.076(0.809)
0.006(0.055)
-9-0.081(0.862)
0.003(0.032)
0.066(0.717)
0.054(0.574)
-0.001(0.011)
0.001(0.009)
-8-0.073(0.777)
-0.056(0.589)
0.049(0.533)
-0.049(0.521)
0.068(0.723)
-0.107(0.991)
-7-0.007(0.075)
-0.081(0.862)
-0.025(0.272)
0.044(0.468)
0.036(0.387)
-0.068(0.636)
-60.006(0.065)
-0.066(0.702)
0.033(0.363)
0.023(0.247)
-0.147(1.581)
-0.106(0.991)
-50.06(0.652)
0.114(1.213)
-0.034(0.374)
-0.224(2.409)*
0.053(0.576)
0.14(1.321)
-4-0.024(0.261)
-0.131(1.409)
0.168(1.846)
-0.143(1.554)
0.151(1.641)
-0.113(1.076)
-3 -0.082(0.891) -0.014(0.151) -0.042(0.467) 0.021(0.228) -0.103(1.120) -0.012(0.114)
-2-0.04(0.440)
-0.092(1.000)
-0.172(1.911)
-0.183(1.989)
-0.009(0.099)
-0.05(0.481)
-10.137(1.505)
-0.076(0.826)
-0.123(1.382)
-0.165(1.813)
0.032(0.352)
-0.251(2.413)*
0-0.123(1.352)
0.12(1.304)
-0.012(0.135)
-0.111(1.220)
-0.188(2.066)*
-0.009(0.087)
1-0.065(0.714)
-0.017(0.185)
-0.09(1.011)
0.121(1.330)
-0.004(0.044)
0.022(0.212)
2-0.011(0.121)
-0.106(1.152)
-0.062(0.689)
-0.023(0.250)
-0.192(2.110)*
-0.107(1.029)
30.126(1.370)
0.049(0.527)
-0.16(1.778)
0.02(0.217)
0.08(0.870)
-0.05(0.476)
4-0.01(0.109)
-0.151(1.624)
0.049(0.538)
0.03(0.326)
-0.003(0.033)
0.081(0.771)
50.063(0.685)
-0.079(0.840)
-0.048(0.527)
0.036(0.387)
0.014(0.152)
0.138(1.302)
60.027(0.290)
0.086(0.915)
0.032(0.352)
0.068(0.731)
0.065(0.699)
0.063(0.589)
7-0.027(0.290)
-0.099(1.053)
-0.09(0.978)
-0.006(0.064)
-0.051(0.548)
-0.004(0.037)
80.073(0.777)
-0.089(0.937)
0.006(0.065)
0.008(0.085)
0.225(2.394)*
0.046(0.426)
9-0.127(1.351)
0.009(0.095)
0.101(1.098)
0.01(0.106)
-0.014(0.149)
-0.139(1.287)
10-0.086(0.915)
-0.009(0.094)
0.025(0.269)
-0.058(0.611)
-0.095(1.011)
0.194(1.780)
11-0.065(0.684)
0.04(0.094)
0.122(1.312)
0.183(1.926)
-0.027(0.284)
0.054(0.491)
120.174(1.832)
-0.002(0.021)
0.171(1.819)
-0.015(0.156)
0.028(0.295)
0.083(0.755)
Numbers with in brackets indicate T values = correlation/ standard error
* indicates t values greater than 2, @ 5% significance level
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
40/74
Interpretation:
From the above table, it is clear that in first half of 2000, T value for all
the leads and lags is not statistically significant. So there is no impact
of ER on sensex and vice versa.
In the second half of 2000 T value at -2 lag and at -4 lag is significant.
This shows that ER at zero date has an inverse effect on second and
fourth days share prices and T value at + 7 lag is also significant. So
SENSEX inversely affects the ER.
In the first half of 2001 SENSEX is affected by ER on first, third and
ninth day. In the second half of 2001 on the same day and next day
there was an inverse affect on Index due to fluctuations in ER. And
there was cyclical relationship between the variables during this period.
In the year 2002 and in first half of 2003, ER and SENSEX are not
affected by each other. In the second half 2003 ER affects SENSEX on
the second day. In the first half of 2004 ER leads SENSEX at five day
lag and SENSEX leads ER at five day lag. In the first half of 2005
fluctuations in ER are reflected in SENSEX on the next day.
So finally we can find that there is no systematic pattern of lead or lag
between the variables in this period.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
41/74
Table No.8 Correlation and T values of ER and NIFTY for the period 2000 to 2002
I half of 2000 II half of 2000 I half of 2001 II half of 2001 I half of 2002
Lag Correlation Correlation Correlation Correlation Correlation
-120.039
(0.406)-0.011(0.117)
0.101(1.063)
0.004(0.040)
0.047(0.495)
-11
0.043
(0.448)
0.119
(1.280)
-0.071
(0.747)
0.113
(1.141)
0.013
(0.138)
-100.1
(1.053)0.098
(1.054)-0.032(0.340)
0.112(1.131)
-0.003(0.032)
-9-0.027(0.284)
0.135(1.467)
-0.232(2.468)*
0.041(0.418)
0.094(1.000)
-8-0.01
(0.106)-0.078(0.848)
-0.096(1.021)
-0.012(0.122)
0.072(0.774)
-70.067
(0.713)0.108
(1.174)0.104
(1.118)0.117
(1.206)0.171
(1.839)
-60.096
(1.021)0.075
(0.824)0.049
(0.527)-0.024(0.247)
0.148(1.609)
-50.17
(1.828)0.065
(0.714)0.071
(0.772)-0.16
(1.667)0.031
(0.337)
-40.055
(0.591)-0.181(1.989)
0.028(0.304)
-0.179(1.865)
-0.112(1.217)
-30.146
(1.587)0.02
(0.222)0.203
(2.207)*0.004
(0.042)0.013
(0.143)
-20.042
(0.457)-0.155(1.722)
0.105(1.154)
-0.146(1.537)
0.235(2.582)*
-10.033
(0.359)-0.03
(0.337)-0.165(1.813)
-0.42(4.468)*
0.012(0.132)
00.036
(0.396)-0.17
(1.910)-0.099(1.088)
-0.365(3.883)*
-0.072(0.800)
10.04
(0.435)-0.068(0.764)
-0.152(1.670)
-0.335(3.564)*
-0.002(0.022)
2-0.053(0.576)
0.129(1.433)
0.018(0.198)
-0.105(1.105)
0.027(0.297)
30.132
(1.435)-0.112(1.244)
-0.009(0.098)
-0.17(1.789)
0.079(0.868)
4-0.046(0.495)
0.069(0.758)
0.011(0.120)
-0.075(0.781)
-0.084(0.913)
5-0.051(0.548)
-0.026(0.286)
-0.016(0.174)
-0.149(1.552)
-0.021(0.228)
6-0.069(0.734)
0.029(0.319)
-0.063(0.677)
-0.048(0.495)
-0.074(0.804)
7-0.07
(0.745)-0.263(2.859)
-0.002(0.022)
-0.015(0.155)
-0.118(1.269)
8-0.113(1.202)
0.03(0.326)
-0.021(0.223)
-0.041(0.418)
-0.052(0.559)
90.001
(0.011)-0.151(1.641)
-0.084(0.894)
-0.032(0.327)
-0.03(0.319)
10-0.096(1.011)
0.069(0.742)
0.01(0.106)
-0.139(1.404)
-0.05(0.532)
11
-0.081
(0.844)
-0.169
(1.817)
0.05
(0.526)
-0.063
(0.636)
-0.057
(0.606)
12-0.161(1.677)
-0.053(0.564)
-0.055(0.579)
0.038(0.380)
0.035(0.368)
Numbers with in brackets indicate T values = correlation/ standard error
* indicates t values greater than 2, @ 5% significance level
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
42/74
Numbers with in brackets indicate T values = correlation/ standard error
* indicates t values greater than 2, @ 5% significance level
Table No. 9 Correlation and T values of ER and NIFTY for the period 2002 to 2005
II half of 2002 I half of 2003 II half of 2003 I half of 2004 II half of 2004 I half of 2005
Lag Correlation Correlation Correlation Correlation Correlation Correlation
-110.109
(1.147)0.078
(0.813)0.053
(0.570)-0.092(0.968)
-0.016(0.168)
0.008(0.073)
-10-0.069(0.734)
-0.093(0.969)
-0.139(1.495)
-0.045(0.474)
0.091(0.968)
-0.004(0.037)
-9-0.079(0.840)
-0.002(0.021)
0.109(1.185)
0.056(0.596)
-0.002(0.021)
0.006(0.056)
-8-0.057(0.606)
-0.053(0.558)
0.063(0.685)
-0.026(0.277)
0.043(0.457)
-0.113(1.046)
-7-0.004(0.043)
-0.078(0.830)
-0.025(0.272)
0.055(0.585)
0.039(0.419)
-0.019(0.178)
-6-0.027(0.290)
-0.074(0.787)
0.008(0.088)
0.018(0.194)
-0.158(1.699)
-0.148(1.383)
-50.073
(0.793)0.087
(0.926)-0.009(0.099)
-0.241(2.591)*
0.081(0.880)
0.159(1.500)
-4-0.067(0.728)
-0.088(0.946)
0.146(1.604)
-0.141(1.533)
0.126(1.370)
-0.107(1.019)
-3-0.102(1.109)
-0.008(0.086)
-0.038(0.422)
0.001(0.011)
-0.113(1.228)
-0.047(0.448)
-2
0.088
(0.967)
-0.102
(1.109)
-0.189
(2.100)*
-0.181
(1.967)
0.007
(0.077)
-0.024
(0.231)
-10.093
(1.022)-0.075(0.815)
-0.112(1.258)
-0.172(1.890)
0.043(0.473)
-0.222(2.135)*
0-0.111(1.220)
0.103(1.120)
-0.014(0.157)
-0.101(1.110)
-0.169(1.857)
-0.063(0.612)
1-0.112(1.231)
0.004(0.043)
-0.091(1.022)
0.132(1.451)
-0.014(0.154)
0.003(0.029)
20.035
(0.385)-0.082(0.891)
-0.083(0.922)
-0.003(0.033)
-0.154(1.692)
-0.035(0.337)
30.095
(1.033)0.039
(0.419)-0.145(1.611)
0.027(0.293)
0.076(0.826)
-0.032(0.305)
40.029
(0.315)-0.141(1.516)
0.016(0.176)
0.045(0.489)
-0.02(0.217)
0.038(0.362)
50.045
(0.489)-0.099(1.053)
-0.022(0.242)
0.034(0.366)
0.019(0.207)
0.179(1.689)
6-0.028(0.301)
0.063(0.670)
0.018(0.198)
0.069(0.742)
0.068(0.731
-0.014(0.131)
70.017
(0.183)-0.093(0.989)
-0.096(1.043)
0.006(0.064)
-0.038(0.409)
0.08(0.748)
80.124
(1.319)-0.086(0.905)
0.061(0.663)
-0.009(0.096)
0.173(1.840)
0.022(0.204)
9-0.134(1.426)
0.025(0.263)
0.119(1.293)
-0.002(0.021)
-0.009(0.096)
-0.128(1.185)
10-0.058(0.617)
-0.028(0.292)
0.035(0.376)
-0.022(0.232)
-0.093(0.989)
0.179(1.642)
11-0.049(0.516)
0.018(0.188)
0.119(1.280)
0.163(1.716)
-0.018(0.189)
0.044(0.400)
120.175
(1.842)0.012
(0.124)0.195
(2.074)*-0.008(0.083)
0.021(0.221)
0.116(1.055)
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
43/74
Interpretation:
From the above tables, it is clear that in the year 2000, there is no
relationship between the variables. In the year 2001 there was cyclical
relation between the variables. In the year 2002 and first half 2003
there was no significant relationship between the variables. In the
second half 2003 ER affects NIFTY on the second day. In the first half
of 2004 ER leads NIFTY at five day length and NIFTY leads ER at five
day length. In the first half of 2005 fluctuations in ER are reflected in
NIFTY on the next day.
So finally we can find that there is no systematic pattern of lead or lag
between the variables in this period. This also shows that SENSEX and
NIFTY are moving in the same direction.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
44/74
Table No. 10 Correlation and T values of ER and CNX IT
I half of 2000 II half of 2000 I half of 2001 II half of 2001 I half of 2002
Lag Correlation Correlation Correlation Correlation Correlation
-12-0.059(0.615)
-0.044(0.468)
0.136(1.432)
-0.123(1.230)
-0.020(0.211)
-11-0.019(0.198)
0.042(0.452)
-0.077(0.811)
-0.03(0.303)
0.022(0.234)
-10-0.021(0.221)
0.155(1.667)
0.025(0.266)
-0.039(0.394)
-0.006(0.064)
-90.064
(0.674)0.121
(1.315)-0.212
(2.255)*-0.044(0.449)
0.023(0.245)
-80.003
(0.032)-0.057(0.620)
-0.123(1.309)
-0.013(0.133)
0.017(0.183)
-70.159
(1.691)0.101
(1.098)0.052
(0.559)0.154
(1.588)0.135
(1.452)
-60.071
(0.755)0.137
(1.505)0.158
(1.699)-0.021(0.216)
0.162(1.761)
-50.255
(2.742)*0.128
(1.407)0.036
(0.391)-0.05
(0.521)0.065
(0.707)
-4 0.09(0.968) -0.175(1.923) 0.098(1.065) -0.191(1.990) -0.059(0.641)
-30.074
(0.804)0.041
(0.456)0.147
(1.598)-0.124(1.305)
-0.143(1.571)
-2-0.094(1.022)
-0.150(1.667)
0.186(2.044)*
-0.116(1.221)
0.152(1.670)
-1-0.066(0.717)
0.067(0.753)
-0.144(1.582)
-0.477(5.074)*
-0.029(0.319)
0-0.091(1.000)
-0.147(1.652)
-0.111(1.220)
-0.295(3.138)*
-0.069(0.767)
1-0.009(0.098)
-0.069(0.775)
-0.129(1.418)
-0.248(2.638)*
-0.048(0.527)
2-0.123(1.337)
0.128(1.422)
-0.107(1.176)
-0.021(0.221)
0.185(2.033)*
3
0.1
(1.087)
-0.063
(0.700)
-0.022
(0.239)
-0.13
(1.368)
0.097
(1.066)
4-0.08
(1.087)-0.060(0.659)
0.099(1.076)
-0.018(0.188)
-0.035(0.380)
5-0.099(1.065)
0.022(0.242)
-0.026(0.283)
-0.064(0.667)
-0.007(0.076)
6-0.114(1.213)
0.086(0.945)
-0.151(1.624)
-0.075(0.773
0.041(0.446)
7-0.219
(2.330)*-0.254
(2.761)*-0.053(0.570)
-0.031(0.320)
-0.132(1.419)
8-0.202
(2.149)*0.052
(0.565)-0.007(0.074)
-0.046(0.469)
-0.139(1.495)
9-0.102(1.074)
-0.160(1.739)
-0.06(0.638)
-0.048(0.490)
-0.042(0.447)
10-0.121(1.274)
0.082(0.882)
-0.014(0.149)
-0.126(1.273)
0.000(0.000)
11-0.157(1.635)
-0.143(1.538)
0.032(0.337)
-0.055(0.556)
-0.102(1.085)
12-0.152(1.583)
0.028(0.298)
-0.02(0.211)
0.037(0.370)
-0.030(0.316)
Numbers with in brackets indicate T values = correlation/ standard
error
* indicates t values greater than 2, @ 5% significance level
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
45/74
Table No. 11 Correlation and T values of ER and CNX IT
II half 2002 I half 2003 II half 2003 I half 2004 II half 2004 I half 2005
Lag Correlation Correlation Correlation Correlation Correlation Correlation
-12-0.114(1.200)
0.058(0.598)
-0.062(0.660)
0.059(0.615)
-0.101(1.063)
0.111(1.009)
-110.082
(0.863)0.085
(0.885)0.073
(0.785)-0.179(1.884)
-0.029(0.305)
-0.052(0.473)
-10-0.012(0.128)
0.003(0.031)
-0.141(1.516)
0.03(0.316)
0.024(0.255)
-0.039(0.358)
-9-0.033(0.351)
0.006(0.063)
0.089(0.967)
0.022(0.234)
-0.018(0.191)
0.009(0.083)
-8-0.085(0.904)
0.061(0.642)
0.02(0.217)
0.174(1.851)
0.052(0.553)
-0.095(0.880)
-70.073
(0.785)0.031
(0.330)-0.077(0.837)
-0.044(0.468)
0.073(0.785)
-0.087(0.813)
-6-0.07
(0.753)-0.110(1.170)
-0.028(0.308)
0.003(0.032)
-0.047(0.505)
-0.091(0.850)
-50.003
(0.033)0.068
(0.723)0.095
(1.044)-0.061(0.656)
0.017(0.185)
0.179(1.689)
-4-0.167(1.815)
0.013(0.140)
0.137(1.505)
-0.021(0.228)
0.154(1.674)
-0.066(0.629)
-3-0.062(0.674)
-0.049(0.527)
0.096(1.067)
-0.002(0.022)
-0.037(0.402)
-0.037(0.352)
-20.248
(2.725)*-0.074(0.804)
-0.087(0.967)
-0.036(0.391)
0.082(0.901)
-0.058(0.558)
-10.043
(0.473)0.024
(0.261)-0.012(0.135)
0.002(0.022)
0.030(0.330)
-0.116(1.115)
0-0.052(0.571)
-0.023(0.250)
0.01(0.112)
0.001(0.011)
-0.031(0.341)
-0.09(0.874)
1-0.199
(2.187)*0.024
(0.261)-0.035(0.393)
0.041(0.451)
0.005(0.055)
0.093(0.894)
20.068
(0.747)0.026
(0.283)-0.055(0.611)
0.097(1.054)
-0.144(1.582)
-0.015(0.144)
30.065
(0.707)-0.069(0.742)
-0.215(2.389)*
0.079(0.859)
0.090(0.978)
-0.03(0.286)
4
0.117
(1.272)
-0.054
(0.581)
0.034
(0.374)
0.044
(0.478)
-0.079
(0.859)
-0.01
(0.095)
50.018
(0.196)-0.085(0.904)
0.055(0.604)
-0.01(0.108)
-0.044(0.478)
0.213(2.009)*
6-0.053(0.570)
0.057(0.606)
-0.001(0.011)
0.065(0.699)
-0.014(0.151)
0.022(0.206)
70.022
(0.237)-0.056(0.596)
-0.037(0.402)
-0.039(0.415)
0.012(0.129)
0.058(0.542)
80.186
(1.979)-0.111(1.168)
0.081(0.880)
-0.046(0.489)
0.223(2.372)*
0.015(0.139)
9-0.023(0.245)
0.061(0.642)
0.006(0.065)
-0.121(1.287)
-0.113(1.202)
-0.144(1.333)
10-0.076(0.809)
-0.070(0.729)
0.01(0.108)
-0.079(0.832)
-0.005(0.053)
0.227(2.083)*
11-0.023(0.242)
0.016(0.167)
0.074(0.796)
0.056(0.589)
-0.070(0.737)
0.112(1.018)
120.175
(1.842)0.010
(0.103)0.165
(1.755)-0.101(1.052)
0.080(0.842)
0.062(0.564)
Numbers with in brackets indicate T values = correlation/ standard
error
* indicates t values greater than 2, @ 5% significance level
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
46/74
Interpretation:
From the above tables, it is clear that in the year 2000, T value at -5,
+7and at +8 lag is statistically significant. This shows that variables
were randomly related. In the year 2001 there was cyclical relationship
between the variables. The year 2002 CNX IT had influenced ER at
two day lag and ER also influenced IT index after two days. In the
years 2003 and 2004 IT had not at all affected by ER fluctuations. In
the year 2005 IT leads ER on fifth and tenth day, but it has not affected
by ER.
So we find that there was no noticeable relation between the variables.
As there was no systematic pattern of lead or lag.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
47/74
Table No. 12 Correlation and T values of ER and BANKEX for the period 2002 to 2005
I half 2002 II half 2002 I half 2003 II half 2003 I half 2004 II half 2004 I half 2005
Lag Correlation Correlation Correlation Correlation Correlation Correlation Correlation
-120.111
(1.168)0.121
(1.274)-0.031(0.320)
0.018(0.191)
-0.056(0.583)
-0.06(0.632)
0.052(0.473)
-11
0.059
(0.628)
-0.098
(1.032)
-0.052
(0.542)
0.047
(0.505)
-0.216
(2.274)*
0.034
(0.358)
-0.04
(0.364)
-10-0.096(1.021)
-0.045(0.479)
0.101(1.052)
-0.163(1.753)
-0.111(1.168)
0.112(1.191)
0.03(0.275)
-90.137
(1.457)0.037
(0.394)-0.01
(0.105)0.146
(1.587)0.074
(0.787)-0.04
(0.426)-0.088(0.815)
-80.12
(1.290)-0.051(0.543)
-0.107(1.126)
0.104(1.130)
0.023(0.245)
-0.033(0.351)
-0.003(0.028)
-70.241
(2.591)*-0.010(0.108)
0.096(1.021)
-0.051(0.554)
0.069(0.734)
0.069(0.742)
0.009(0.084)
-60.182
(1.978)0.037
(0.398)-0.052(0.553)
0.024(0.264)
0.024(0.258)
-0.172(1.849)
-0.06(0.561)
-50.003
(0.033)0.017
(0.185)0.061
(0.649)-0.088(0.967)
-0.199(2.140)*
-0.019(0.207)
0.123(1.160)
-4-0.037(0.402)
-0.028(0.304)
-0.02(0.215)
0.043(0.473)
-0.157(1.707)
0.042(0.457)
-0.146(1.390)
-30.16
(1.758)0.067
(0.728)-0.018(0.194)
-0.083(0.922)
0.026(0.283)
-0.158(1.717)
-0.066(0.629)
-20.146
(1.604)0.065
(0.714)-0.06
(0.652)-0.182
(2.022)*-0.197
(2.141)*-0.005(0.055)
0.025(0.240)
-10.003
(0.033)-0.075(0.824)
-0.041(0.446)
-0.092(1.034)
-0.229(2.516)*
0.029(0.319)
-0.209(2.010)*
00.009
(0.100)-0.084(0.923)
0.041(0.446)
0.002(0.022)
-0.144(1.582)
-0.075(0.824)
-0.159(1.544)
10.079
(0.868)0.034(0.374
0.125(1.359)
-0.071(0.798)
0.139(1.527)
0.015(0.165)
0.031(0.298)
2-0.01
(0.110)-0.014(0.154)
-0.076(0.826)
-0.034(0.378)
0.004(0.043)
-0.243(2.670)*
-0.033(0.317)
3-0.183
(2.011)*0.091
(0.989)0.005
(0.054)-0.06
(0.667)0.035
(0.380)0.101
(1.098)0.038
(0.362)
4
0.04
(0.435)
0.068
(0.739)
0.145
(1.559)
0.033
(0.363)
-0.002
(0.022)
-0.023
(0.250)
-0.054
(0.514)
50.1
(1.087)-0.130(1.413)
-0.168(1.787)
-0.111(1.220)
0.033(0.355)
-0.006(0.065
0.251(2.368)*
6-0.11
(1.196)-0.055(0.591)
0.206(2.191)*
0.04(0.440)
0.071(0.763)
0.132(1.419)
0.021(0.196)
7-0.158(1.699)
0.078(0.839)
-0.046(0.489)
-0.105(1.141)
0.010(0.106)
-0.12(1.290)
0.048(0.449)
8-0.051(0.548)
-0.076(0.809)
-0.484(5.095)*
-0.044(0.478)
0.020(0.213)
0.132(1.404)
-0.027(0.250)
90.03
(0.319)0.054
(0.574)0.395
(4.158)*0.186
(2.022)*-0.019(0.202)
-0.096(1.021)
-0.146(1.352)
100.01
(0.106)0.011
(0.117)0.02
(0.208)0.012
(0.129)-0.008(0.084)
-0.084(0.894)
0.196(1.798)
110.062
(0.660)-0.025(0.263)
-0.058(0.604)
0.084(0.903)
0.176(1.853)
-0.018(0.189)
-0.004(0.036)
12-0.069(0.726)
-0.005(0.053)
-0.051](0.526)
-0.015(0.160)
0.000(0.000)
-0.103(1.084)
0.136(1.236)
Numbers with in brackets indicate T values = correlation/ standard
error
* indicates t values greater than 2, @ 5% significance level
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
48/74
Interpretation:
From the above tables, it is clear that in the year 2002,t value at -7 and
at +3 lag is statistically significant and in the second half of 2002 there
was no relationship between the variables. In the first half of 2003 T
value at +6 lag is statistically significant and T value at -2 lag in the
second half of 2003 is significant. So there was a little affect on one
variable from the other variable. In the first half of 2004 T value at -1 , -
2 ,-5 and -11 lag is statistically significant. So in this period ER affects
BANKEX. In the second half of 2004 there was negligible relationship
between the variables. In the first half of 2005 T value at -1 lag and at
+5 lag is significant.
So we find that there was no noticeable relation between the variables.
As there was no systematic pattern of lead or lag.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
49/74
Table No. 13 Correlation and T values of ER and IMPORT for the period 2000 to 2002
I half 2000 II half 2000 I half 2001 II half 2001 I half 2002
Lag Correlation Correlation Correlation Correlation Correlation
-120.129
(0.510)-0.032(0.340)
0.003(0.032)
0.093(0.930)
0.010(0.105)
-110.049
(1.421)0.087
(0.935)-0.074(0.779)
0.093(0.939)
0.021(0.223)
-100.135
(0.221)0.127
(1.366)-0.169(1.798)
0.079(0.939)
0.060(0.638)
-9-0.021(0.415)
-0.043(0.467)
-0.23(2.447)*
0.051(0.520)
0.118(1.255)
-80.039
(0.777)-0.097(1.054)
0.162(1.723)
-0.029(0.296)
0.088(0.946)
-70.073
(0.585)0.107
(1.163)0.08
(0.860)0.038(0.392
0.139(1.495)
-60.055
(0.129)0.000
(0.000)0.186
(2.000)*-0.047(0.485)
0.057(0.620)
-50.012
(1.247)-0.014(0.154)
0.036(0.391)
-0.178(1.854)
-0.070(0.761)
-40.116
(1.793)-0.129(1.418)
0.103(1.120)
-0.228(2.375*
-0.123(1.337)
-30.165
(0.891)-0.132(1.467)
0.137(1.489)
-0.045(0.474)
-0.003(0.033)
-20.082
(0.380)-0.004(0.044)
-0.033(0.363)
-0.08(0.842)
0.215(2.363)*
-10.035
(0.473)-0.096(1.079)
-0.146(1.604)
-0.292(3.106)*
0.031(0.341)
00.043
(0.272)-0.153(1.719)
-0.026(0.286)
-0.309(3.287)*
-0.062(0.689)
10.025
(1.000)0.082
(0.921)-0.064(0.703)
-0.263(2.798)*
-0.023(0.253)
20.092
(0.402)0.072
(0.800)0.069
(0.758)-0.107(1.126)
-0.057(0.626)
30.037
(0.108)-0.088(0.978)
-0.023(0.250)
-0.121(1.274)
0.065(0.714)
4
0.01
(0.656)
-0.030
(0.330)
-0.048
(0.522)
-0.12
(1.250)
-0.137
(1.489)
50.061
(0.468)0.086
(0.945)-0.077(0.837)
-0.142(1.479)
-0.087(0.946)
60.044
(0.777)-0.186
(2.044)*-0.04
(0.430)-0.138(1.423)
-0.097(1.054)
70.073
(0.234)-0.141(1.533)
0.003(0.032)
0.021(0.216)
-0.069(0.742)
8-0.022(0.379)
-0.014(0.152)
-0.096(1.021)
-0.035(0.357)
-0.064(0.688)
90.036
(1.558)-0.039(0.424)
0.024(0.255)
-0.081(0.827)
-0.031(0.330)
10-0.148(0.229)
-0.030(0.323)
-0.001(0.011)
-0.093(0.939)
0.001(0.011)
11-0.022(1.000)
-0.133(1.430)
-0.043(0.453)
-0.05(0.505)
-0.021(0.223)
12-0.096(0.000)
-0.073(0.777)
-0.05(0.526)
0.134(1.340)
0.039(0.411)
Numbers with in brackets indicate T values = correlation/ standard
error
* indicates t values greater than 2, @ 5% significance level
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
50/74
Numbers with in brackets indicate T values = correlation/ standard
error
* indicates t values greater than 2, @ 5% significance level
Table No. 14 Correlation and T values of ER and IMPORT for the period 2002 to 2005II half 2002 I half 2003 II half 2003 I half 2004 II half 2004 I half 2005
Lag Correlation Correlation Correlation Correlation Correlation Correlation
-120.041
(0.432)0.060
(0.619)-0.058(0.617)
0.018(0.188)
0.044(0.463)
0.086(0.782)
-110.106
(1.116)0.010
(0.104)0.069
(0.742)-0.045(0.474)
-0.100(1.053)
-0.022(0.200)
-10-0.041(0.436)
-0.197(2.052)*
-0.041(0.441)
-0.035(0.368)
0.027(0.287)
0.015(0.138)
-9-0.144(1.532)
-0.055(0.579)
0.066(0.717)
0.031(0.330)
-0.009(0.096)
0.000(0.000)
-8-0.009(0.096)
-0.040(0.421)
-0.053(0.576)
-0.042(0.447)
0.118(1.255)
-0.100(0.926)
-7-0.048(0.516)
-0.178(1.894)
-0.023(0.250)
0.016(0.170)
0.002(0.022)
-0.110(1.028)
-6-0.067(0.720)
-0.001(0.011)
-0.034(0.374)
0.015(0.161)
-0.117(1.258)
-0.074(0.692)
-50.066
(0.717)-0.008(0.085)
-0.049(0.538)
-0.205(2.204)*
0.047(0.511)
0.044(0.415)
-40.057
(0.620)-0.085(0.914)
0.145(1.593)
-0.149(1.620)
0.080(0.870)
-0.080(0.762)
-3-0.144(1.565)
0.086(0.925)
-0.052(0.578)
-0.044(0.478)
-0.122(1.326)
-0.072(0.686)
-2-0.037(0.407)
-0.139(1.511)
-0.177(1.967)
-0.202(2.196)*
-0.031(0.341)
-0.063(0.606)
-10.178
(1.956)-0.052(0.565)
-0.065(0.730)
-0.206(2.264)*
-0.005(0.055)
-0.254(2.442)
0-0.147(1.615)
0.074(0.804)
0.009(0.101)
-0.086(0.945)
-0.233(2.560)*
0.001(0.010)
1-0.142(1.560)
-0.155(1.685)
-0.144(1.618)
0.083(0.912)
-0.061(0.670)
0.102(0.981)
20.011
(0.121)-0.093(1.011)
-0.026(0.289)
-0.019(0.207)
-0.111(1.220)
-0.028(0.269)
30.047
(0.511)0.145
(1.559)-0.043(0.478)
0.063(0.685)
0.082(0.891)
-0.075(0.714)
4
-0.089
(0.967)
-0.112
(1.204)
-0.025
(0.275)
0.031
(0.337)
-0.008
(0.087)
0.001
(0.010)
50.048
(0.522)-0.062(0.660)
-0.095(1.044)
0.055(0.591)
0.032(0.348)
0.170(1.604)
60.058
(0.624)0.084
(0.894)0.040
(0.440)0.035
(0.376)0.033
(0.355)-0.039(0.364)
7-0.013(0.140)
-0.103(1.096)
-0.058(0.630)
0.003(0.032)
-0.044(0.473)
0.070(0.654)
80.031
(0.330)0.014
(0.147)0.103
(1.120)0.004
(0.043)0.108
(1.149)0.076
(0.704)
9-0.082(0.872)
0.058(0.611)
0.159(1.728)
0.019(0.202)
0.092(0.979)
-0.070(0.648)
10-0.104(1.106)
-0.052(0.542)
0.117(1.258)
0.001(0.011)
-0.075(0.798)
0.129(1.183)
11-0.018(0.189)
0.059(0.615)
0.163(1.753)
0.145(1.526)
-0.032(0.337)
0.016(0.145)
120.145
(1.526)0.007
(0.072)0.186
(1.979)-0.008(0.083)
0.081(0.853)
0.167(1.518)
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
51/74
Interpretation:
From the above tables, it is clear that in the year 2000 there was no
interrelation between the variables. In the first half of 2001, there was
negative effect of ER on index at 9 day lag and direct effect of index on
ER at 6 day lag.
In the second half of 2001, there was cyclical relation between the
variables unlike other variables.
In all the other periods there was no significant relation between the
variables.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
52/74
Table No. 15 Correlation and T values of ER and EXPORT for the period 2000 to 2002I half 2000 II half 2000 I half 2001 II half 2001 I half 2002
Correlation Correlation Correlation Correlation Correlation
-120.037
(0.385)0.162
(1.723)-0.017(0.179)
-0.096(0.960)
-0.005(0.053)
-11
-0.026
(0.271)
-0.027
(0.290)
0.134
(1.411)
0.009
(0.091)
-0.016
(0.170)
-10-0.046(0.484)
0.067(0.720)
-0.046(0.489)
-0.004(0.040)
-0.031(0.330)
-9-0.009(0.095)
0.148(1.609)
0.020(0.213)
-0.007(0.071)
0.061(0.649)
-80.026
(0.277)0.141
(1.533)-0.242
(2.574)*-0.014(0.143)
0.069(0.742
-7-0.012(0.128)
-0.033(0.359)
-0.126(1.355)
0.126(1.299)
0.187(2.011)*
-60.130
(1.383)0.158
(1.736)0.044
(0.473)0.011
(0.113)0.138
(1.500)
-50.084
(0.903)0.102
(1.121)0.175
(1.902)-0.079(0.823)
0.026(0.283)
-40.222
(2.387)*0.145
(1.593)0.039
(0.424)-0.141(1.469)
-0.084(0.913)
-3 0.129(1.402) -0.2(2.222)* 0.076(0.826) -0.114(1.200) -0.071(0.780)
-20.095
(1.033)0.016
(0.178)0.130
(1.429)-0.112(1.179)
0.191(2.099)*
-1-0.079(0.859)
-0.167(1.876)
0.152(1.670)
-0.465(4.947)*
-0.037(0.407)
0-0.049(0.538)
0.03(0.337)
-0.200(2.198)*
-0.344(3.660)*
-0.096(1.067)
1-0.041(0.446)
-0.166(1.865)
-0.121(1.330)
-0.306(3.255)*
-0.002(0.022)
20.040
(0.435)-0.035(0.389)
-0.167(1.835)
-0.104(1.095)
0.179(1.967)
3-0.126(1.370)
0.123(1.367)
-0.085(0.924)
-0.148(1.558)
0.079(0.868)
40.090
(0.968)-0.052(0.571)
0.005(0.054)
-0.076(0.792)
-0.105(1.141)
5-0.036(0.387)
-0.066(0.725)
0.126(1.370)
-0.169(1.760)
-0.031(0.337)
6-0.089(0.947)
0.023(0.253)
-0.037(0.398)
-0.170(1.753)
0.008(0.087)
7-0.090(0.957)
0.059(0.641)
-0.172(1.849)
-0.060(0.619)
-0.162(1.742)
8-0.162(1.723)
-0.241(2.620)*
-0.078(0.830)
-0.077(0.786)
-0.172(1.849)
9-0.201
(2.116)*0.001
(0.011)0.023
(0.245)-0.062(0.633)
-0.115(1.223)
10-0.057(0.600)
-0.147(1.581)
-0.069(0.734)
-0.138(1.394)
-0.042(0.447)
11-0.089(0.927)
0.057(0.613)
-0.039(0.411)
-0.074(0.747)
-0.035(0.372)
12
-0.159
(1.656)
-0.146
(1.553)
0.017
(0.179)
0.044
(0.440)
-0.015
(0.158)
Numbers with in brackets indicate T values = correlation/ standard
error
* indicates t values greater than 2, @ 5% significance level
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
53/74
Table No. 16 Correlation and T values of ER and EXPORT for the period 2000 to 2005II half 2002 I half 2003 II half 2003 I half 2004 II half 2004 I half 2005
Lag Correlation Correlation Correlation Correlation Correlation Correlation
-12-0.066(0.695)
0.031(0.320)
-0.008(0.085)
0.006(0.063)
-0.111(1.168)
0.044(0.400)
-110.081
(0.853)0.105
(1.094)0.067
(0.720)-0.066(0.695)
-0.064(0.674)
-0.037(0.336)
-10-0.071(0.755)
-0.032(0.333)
-0.098(1.054)
-0.049(0.516)
0.071(0.755)
-0.013(0.119)
-9-0.029(0.309)
-0.009(0.095)
0.125(1.359)
0.013(0.138)
0.017(0.181)
0.006(0.056)
-8-0.126(1.340)
0.043(0.453)
0.008(0.087)
-0.041(0.436)
0.082(0.872)
-0.174(1.611)
-70.058
(0.624)0.008
(0.085)-0.047(0.511)
0.073(0.777)
-0.008(0.086)
-0.093(0.869)
-60.028
(0.301)-0.102(1.085)
-0.015(0.165)
0.021(0.226)
-0.075(0.806)
-0.141(1.318)
-50.044
(0.478)0.038
(0.404)0.100
(1.099)-0.173(1.860)
0.052(0.565)
0.145(1.368)
-4-0.139(1.511)
0.002(0.022)
0.120(1.319)
-0.135(1.467)
0.136(1.478)
-0.040(0.381)
-3
-0.063
(0.685)
-0.088
(0.946)
0.030
(0.333)
0.078
(0.848)
-0.061
(0.663)
0.011
(0.105)
-20.201
(2.209)*-0.030(0.326)
-0.101(1.122)
-0.139(1.511)
0.062(0.681)
-0.040(0.385)
-10.063
(0.692)0.074
(0.804)-0.014(0.157)
-0.078(0.857)
-0.050(0.549)
-0.192(1.846)
0-0.105(1.154)
-0.078(0.848)
-0.058(0.652)
-0.034(0.374)
-0.055(0.604)
-0.076(0.738)
1-0.094(1.033)
-0.004(0.043)
-0.101(1.135)
0.088(0.967)
-0.019(0.209)
0.060(0.577)
20.031
(0.341)-0.003(0.033)
-0.116(1.289)
-0.042(0.457)
-0.165(1.813)
-0.072(0.692)
30.067
(0.728)-0.012(0.129)
-0.189(2.100)*
0.009(0.098)
0.104(1.130)
-0.089(0.848)
40.111
(1.207)-0.064(0.688)
0.022(0.242)
0.022(0.239)
-0.038(0.413)
0.056(0.533)
5 0.059(0.641) -0.100(1.064) -0.021(0.231) 0.047(0.505) -0.045(0.489) 0.207(1.953)
6-0.003(0.032)
0.054(0.574)
0.010(0.110)
0.053(0.570)
-0.057(0.613)
0.022(0.206)
70.006
(0.065)-0.098(1.043)
-0.059(0.641)
-0.035(0.372)
0.037(0.398)
0.020(0.187)
80.133
(1.415)-0.104(1.095)
0.070(0.761)
0.036(0.383)
0.249(2.649)*
0.000(0.000)
9-0.081(0.862)
0.030(0.316)
-0.014(0.152)
0.023(0.245)
-0.099(1.053)
-0.119(1.102)
10-0.084(0.894)
-0.104(1.083)
0.027(0.290)
-0.031(0.326)
-0.048(0.511)
0.179(1.642)
110.003
(0.032)0.042
(0.438)0.125
(1.344)0.173
(1.821)-0.061(0.642)
0.045(0.409)
120.163
(1.716)-0.006(0.062)
0.192(2.043)*
0.019(0.198)
0.054(0.568)
0.056(0.509)
Numbers with in brackets indicate T values = correlation/ standard
error
* indicates t values greater than 2, @ 5% significance level
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
54/74
Interpretation:
From the above tables, it is clear that in the year 2000, t value at -4lag
and at +9 lag is statistically significant. In the second half of 2000, t
value at -3 and at +8 lag is statistically significant and in the year 2001
there was significant interrelationship between the variables like with
other indices. In the first half of 2002, t value at -2 and -7 lag is
significant and in the second half, t value at -2 lag is significant. But in
all the other periods there was no significant relationship between the
variables.
So for both import and export indices there were no normal or special
impact of ER on index values.
The results show that there is no zero order or lead lag relation
between the two variables so six Multi national companies are
considered in the study. These companies were selected fron CNX
MNC list. The companies are ABB, BATA, Colgate Palmolive, Glaxo
smithkline, Hindustan Lever Ltd. and Mico.
For all the six companies the test shows that the share prices of these
companies are not influenced by the exchange rate fluctuations. The
sample o two companies among six are analyzed below.
-
7/31/2019 Shilpa BS-0347-Exchange Rates & Stock Prices
55/74
Table No.17: Correlation and T values of ER and ABB
for the period 2000 to 2005
YEAR 2000 2001 2002 2003 2004 2005
Lag Correlation. Correlation Correlation Correlation Correlation Correlation
-100.041(0.631)
-0.011(0.164)
0.041(0.631)
0.073(1.123)
0.051(0.785)
-0.044(0.407)
-9-0.005(0.077)
0.006(0.090)
0.069(1.062)
0.154(2.369)*
0.02(0.308)
0.019(0.176)
-80.09(1.385)
0.145(2.197)*
0.002(0.031)
-0.013(0.200)
0.072(1.108)
0.104(0.972)
-70.091(1.400)
0.163(2.470)*
0.05(0.769)
0(0.000)
-0.021(0.323)
-0.01(0.093)
-60.021(0.323)
0.036(0.545)
0.017(0.262)
-0.013(0.200)
-0.071(1.092)
-0.152(1.434)
-5 0.056(0.875 -0.083(1.258) -0.03(0.462) 0.042(0.656) -0.024(0.369) 0.015(0.143)
-40.029(0.453)
-0.018(0.273)
-0.101(1.578) 0.012
(0.188)-0.061(0.953)
-0.068(0.648)
-3-0.01(0.156)
-0.039(0.591)
0.009(0.141)
-0.02(0.313)
-0.08(1.250)
-0.236(2.269)*
-20.041(0.641)
-0.183(2.773)*
0.033(0.516)
-0.092(1.438)
-0.057(0.891)
-0.116(1.115)
-10.039(0.609)
-0.111(1.708)
0.121(1.891)
-0.027(0.422)
-0.066(1.031)
-0.054(0.524)
00.004(0.063)
-0.061(0.938)
0.061(0.953)
-0.085(1.328)
-0.029(0.453)
0.12(1.165)
1
0.069
(1.078)
-0.087
(1.338)
0.085
(1.328)
0.045
(0.703)
0.011
(0.172)
0.084
(0.816)
2-0.076(1.188)
-0.068(1.030)
0.011(0.172)