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Money Supply and Stock Prices Dr T M Srinivasan and Dr N Balakumar Preamble In the literature of finance, the universally accepted
proposition is that the changes in monetary policy strongly influence the changes
in security prices. This has led to several research attempts to isolate
money supply as one of the determinants of changes in stock prices. One of
the primary aims of this article is to bring out the established economic
theory, which forms the basis of the analysis, and to assess various studies
in this field. The other is to estimate the relationship between the stock
prices and the money supply with or without lags in the Indian environment. Theoretical Background Supply of money affects industrial security prices through
several ways. According to Friedman, the quantity theory of money is a theory
of the demand to hold money. The demand to hold money varies according to the
variations in the money supply. Imbalance in portfolio is caused due to an
increase in money supply. Since investors like to retain the proportion of
money constant in their portfolio, they allocate their excess money balances
to other uses, such as buying more commodities or to acquire more financial
assets. Thus, when demand for stocks increases, the stock prices
will raise. Interest rates, also, have an impact on stock prices. If
commercial banks' rate of interest on deposit accounts (time deposits) or
lending rate is lower, implying a loose money policy, then money supply will
raise which, in turn, will give rise to increase in stock prices and vice
versa. Thus, interest rates and stock prices have an inverse relationship. Earlier Works Friedman and Schwartz (1963) have thoroughly documented
the historical record of the empirical relationship that exists between
changes in the growth rate of the stock of money and subsequent changes in
aggregate economic activity. Their empirical results indicated that when
there is a change in money supply, the initial effect is on financial markets
and subsequently on the aggregate economy. In terms of securities market this
would indicate that there should be a relationship between changes in the
growth rate of money supply and changes in stock prices, that is, changes in
the growth rate of the money supply should precede changes in the level of
stock prices. Since Milton Friedman's and Anna Schwartz's (1963)
monetary theories have been so widely discussed, substantially confirmed by
experience, and increasingly accepted - much attention has been focused on
money supply changes as precursors of changes in both general economic
conditions and stock prices. Sprinkel, Beryl (1964) has confirmed the
existence of the relationship between changes in money supply growth rate and
changes in stock prices. However, he has, also, found that the timing is not
always consistent and the lead appears to be getting shorter. Subsequently,
Palmer (1970) has tested the relationship between the money supply growth rate
and a moving average of percentage changes in stock prices and concluded that
money supply, generally, leads to stock price changes, both having a
consistent relationship. Keran (1971) has developed a model intended to
explain the level of stock prices that included money supply growth as one of
the affecting factors. While the overall results are quite good and the money
supply variable is, statistically, appeared to be slight. Homa and Jaffee
(1971), using regression analysis have found that money supply and growth in
money supply, explain the stock price variations significantly. Their
empirical results reveal that an investment policy, which considered money
supply, outperformed a buy-and-hold strategy, whereas mixed results are found
when money supply is not considered. Hamburger and Kochin (1972) have checked whether money
supply has had a direct impact on securities market and its influence on
stock risk. They have found that money supply changes do have a direct effect
on share prices and its volatility has an impact on stock risk. Though the above works revealed a strong relationship
between changes in supply of money and security prices and few indicated that
money supply led stock prices, there are studies, which questioned these
findings, in contrast. Miller (1972), on statistical grounds, has objected to
Keran and Hamburger-Kochin studies; Pesaudo (1974) , after reexamining the
models and by using Canadian data, has concluded that "Finally, the fact
that these models do not appear to have captured stable structural
relationships suggests that one should not attach undue importance to their
quantitative estimates of the impact of changes in the money supply on common
stock prices." Auerbach (1976) likewise has questioned the Keran and Homa-Jaffee
findings based on statistical reasoning. He has removed the trend and
cyclical components of the money and stock prices series and correlated the
adjusted series. The results indicate that the past changes in the M money
supply are not related to future stock price changes, but that stock returns
are related to current and future changes in the M money supply series,
although the relationship is weak. Rozeff (1975) has tested Sprinkel's theory
and found that current changes in stock prices are for all practical purposes
unrelated to past changes in money growth rates. Very few studies have been reported using money supply
data in the Indian context except the works of Chawla, D. and Srinivasan, G.
(1980), and Ramachandran, G. (1989). In sum, to quote Rozeff , "It is simply not true that
past money supply data can provide a profitable guide to investment timing or
improve a portfolio's rate of return. Information is reflected in stock
prices so rapidly that published data tell the investor virtually nothing
about the future changes in stock prices. In particular, Sprinkel's trading
rule, which uses the money supply as an indicator of future stock market
movements, cannot be executed without prior knowledge of business cycle
turning points and, when applied mechanically, does not outperform a naive
buy-and-hold policy." Data Base and Methodology A random sample of 59 actively traded Indian shares on
Bombay Stock Exchange for the study period 1980 to 1989 have been selected
for the purpose of this study and the weekly closing prices of the sample
have been collected. In order to assess the influence of money supply and its
derivatives (that is, lagged variables) as explanatory variables on share
prices, linear regression analysis has been used. Research Results and Practical
Implication There exists a positive relationship between the price
variation and the current money supply variation. However, the impact of
current money supply on the share prices is numerically higher than future
impacts, corresponding highest value being +0.087285. Though the regression results strongly reveal the positive
association between stock prices and current and future money supply, can
this, in practice, be utilized successfully as an instrument for investment decision-making
process? It is worth to point out, in this context that Indian
money supply definition does not include the operations of non-monetary
financial institutions such as life and general insurance corporations,
development banks, investment and trust companies and the Unit Trust of
India. Also, during the decade of 1980 the non-banking finance companies grew
at a considerable rate (In 1981, fixed deposits mobilised by them was Rs.
1475.7 crores. It increased to Rs. 10484.9 crores in 1989 and further to Rs.
17236.2 crores in 1991. [Source: RBI]). The Indian definition of money supply
does not take this into account. Thus, it can, comfortably, be concluded that inspite of
the existence of positive influence of money supply data on security prices,
it cannot be used, beneficially, as an indicator by which one can forecast
the future share price movements. Concluding Remarks In spite of a statistically significant regression model, it
may be difficult or impossible to explain the movement of share prices
through the use of structural model. The reasons are: (a) Data are not available for all
those explanatory variables which affect share prices; and (b) To obtain a forecast for Y
from a regression equation, those explanatory variables that are not lagged
must themselves be forecasted, and this may be more difficult than
forecasting Y itself. Thus, there is a need to seek for other means of obtaining
a forecast for Y. Such an alternative approach is modern time series
analysis. |
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