ASIAN JOURNAL OF MANAGEMENT RESEARCH Online Open Access publishing platform for Management Research

Transcription

1 Online Open Access publishing platform for Management Research Copyright 2010 All rights reserved Integrated Publishing association Research Article ISSN Policy rate changes and the movement of stock market (With special reference to nifty) Acropolis Institute of Technology and Research, Manglia Square, Indore (M.P.), India ABSTRACT Monetary policy is the process by which the Central Bank or Monetary authority of a country controls the supply of money, because of which share price movement also get affected. Every year Reserve Bank of India changes the cash reserve ratio (CRR), statutory liquidity ratio (SLR), Repo Rate, Reverse Repo Rate, etc. to control the money supply of the country. This paper aim to discuss about the impact of these ratios in the share price with special reference to Nifty. The analysis of the study showed that the security prices reacted to the announcements of these ratios. To do these analysis we have taken daily basis database of different variable considered in the study. Keywords: Monetary policy, cash reserve ratio, Statutory Liquidity Ratio, Repurchase Rate, Reverse Repurchase Rate, Stock Market (Nifty). 1. Introduction The monetary policy of any country refers to the regulatory policy, whereby the monetary authority maintains its control over the supply of money for the realization of general economic objectives. Monetary policy can be broadly defined as "the deliberate effort by the Central Bank to influence economic activity by variations in the money supply, in availability of credit or in the interest rates consistent with specific national objective." In the context of developing economies like India, monetary policy acquires a wider role and it has to be designed to meet the particular requirements of the economy. It stimulates or discourages spending on goods and services and, thus, influences economic activities and prices by regulating the supply of money, and the cost and availability of credit to producers and consumers in the economy. Households and business units make spending and investment decisions based upon current and expected future monetary policy actions. The various sectors of the economy respond in different ways, depending on the extent to which they are borrowers or lenders and the importance and relative availability of credit to the sector. By affecting the demand side of the economy, monetary policy tries to damp or perhaps even eliminate business fluctuations - economy-wide recessions and booms arising from fluctuations in aggregate demand. In India, the three major objectives of economic policy are growth, social justice (equitable distribution of income and wealth) and price stability. Of these, price stability is perhaps the one that can be pursued most effectively by the monetary authorities of the country. The monetary policy of an economy operates through three important instruments, viz., the regulation of money supply, control over aggregate credit and the interest rate policy. In pre reform period, given the largely underdeveloped state of financial system, regulated nature of financial markets and plan priorities, the RBI often 91

2 resorted to the direct instruments of monetary policy like CRR, SLR and interest rate for allocating credit and regulating money supply in the economy. Gradual liberalization and globalization of the economy, strengthening and development of the financial system, restrictions on the automatic monetization of fiscal deficit and various other changes in the economy had made it possible for the RBI to operate with the indirect instruments of monetary policy such as bank rate, repo rate and OMOs (open market operations). Accordingly, there has been a distinct shift in the monetary policy framework and operating procedures from direct instruments of monetary control to market based indirect instruments in the recent years. The thrust has been to provide the market mechanism a greater role in the economy, to provide the banks more operational flexibility and to bring the allocative efficiency in the economy. In the recent years, changes in the monetary policy have also affected the stock market prices in great perspective. The stock market is getting affected by several monetary policy measures, the important amongst which are changes in CRR, SLR, repo and reverse repo rate, which directly influence the money supply in the market with immediate effect without creating any distortions in the economy. That is the reason, they are perceived to be the most appropriate by the monetary authorities in forming trend in the stock market. Hence the efforts are made in this paper to make the econometric study of impact of changes in CRR, SLR, repo rate and reverse repo rate adopted by the monetary authorities in forming trends in the stock market. CRR, SLR, Repo rate and reverse repo rate are the key policy rates which stipulate the interest rate in the economy. All these policy rates have a direct impact on the lending rate which is now benchmarked to the base rate replacing the erstwhile BPLR. To understand the impact of the policy rates on the stock market prices, let us look into all these rates at a glance. CRR is the percentage of cash deposits which banks maintain with RBI on an everyday basis. Increase in CRR will result in increase in interest rate loans. At the close of business every day, every bank is required to maintain a minimum proportion of its net demand and time liabilities as liquid assets in the form of cash, gold, and unencumbered approved securities. The ratio of liquid assets to demand and time liabilities is known as Statutory Liquidity Ratio (SLR). Repo rate is the short term interest rate at which the RBI lends money to banks. When the repo rate increases, the interest rates on loans also moves up as bank has to fund these loans at a higher cost Reverse Repo Rate is the rate at which RBI borrows fund from banks. It has similar impact on the interest rates on loan. Now since the RBI has narrowed down the spread between repo and reverse repo by 25 basis points and has announced that it will double the frequency of reviewing the monetary policy, the short term volatility in overnight rates will be reduced. This will bring stability in financial market. All these rates collectively impact the stock market liquidity which in turn influences the stock market price & returns. 2. Conceptual framework 2.1 Cash reserve ratio 92

3 The Reserve Bank of India (Amendment) Bill, 2006, has been enacted and has come into force with its gazette notification. Consequent to the amendment to sub-section 42(1), the Reserve Bank, having regard to the needs of securing the monetary stability in the country, can prescribe Cash Reserve Ratio (CRR) for scheduled banks without any floor rate or ceiling rate. (Before the enactment of this amendment, in terms of Section 42(1) of the RBI Act, the Reserve Bank could prescribe CRR for scheduled banks between 3 percent and 20 percent of their total demand and time liabilities). CRR is the percentage of money that the banks keep with the RBI for security. How does it impact the banks profitability? For example, if bank A collects Rs 10,000 deposit from you, then out of the Rs 10,000, it has to keep Rs 500 with the RBI. The net amount left with the bank will be Rs 9,500. If CRR is getting hiked, then the RBI will suck the money from the system in order to meet the trade deficit. Same time, the bank will have money supply deficit to meet all the loan demand. Once the money supply will be reduced then the loan rates or lending rates will increase. Thus we can say, RBI uses CRR either to drain excess liquidity or to release funds needed for the economy from time to time. Increase in CRR means that banks have fewer funds available and money is sucked out of circulation. Thus, we can say that this serves duel purposes; i.e., it not only ensures that a portion of bank deposits is totally risk-free, but also enables the RBI to control liquidity in the system, and thereby inflation, by tying the hands of the banks in lending money. Then 80% of banks lending will be short-term trade loan, which settle on fourth night basis. The increase in interest rate will directly impact the banking industry, housing industry, automobile industry, etc. in the short term. Continuous increase in CRR may impact the quarterly profitability of the above sectors which in turn affects the prices in the stock market. 2.2 Statutory liquidity ratio At the close of business every day, every bank is required to maintain a minimum proportion of its net demand and time liabilities as liquid assets in the form of cash, gold, and unencumbered approved securities. The ratio of liquid assets to demand and time liabilities is known as Statutory Liquidity Ratio (SLR). Present SLR is 23%. The RBI is empowered to increase this ratio up to 40%. 2.3 Repo rate Repo (repurchase) rate is the rate at which the RBI lends shot-term money to the banks. When the repo rate increases, borrowing from the RBI becomes more expensive. Therefore, we can say that in case RBI wants to make it more expensive for the banks to borrow money, it increases the repo rate; similarly, if it wants to make it cheaper for banks to borrow money, it reduces the repo rate. Repo rate is used by the central bank to repurchase government securities from the commercial banks, depending on the level of money supply it decides to maintain in the country's monetary system. To temporarily expand the money supply, the central bank decreases repo rates (so that banks can swap their holdings of government securities for cash), to contract the money supply it increases the repo rates. Alternatively, the central bank 93

4 decides on a desired level of money supply and lets the market determine the appropriate repo rate. The central bank has the power to lower the repo rates while expanding the money supply in the country. This enables the banks to exchange their government security holdings for cash. In contrast, when the central bank decides to reduce the money supply, it implements a rise in the repo rates. 2.4 Reverse repo rate Reverse repo rate is the rate at which banks park their short-term excess liquidity with the RBI. The RBI uses this tool when it feels there is too much money floating in the banking system. An increase in the reverse repo rate means that the RBI will borrow money from the banks at a higher rate of interest. As a result, banks would prefer to keep their money with the RBI. The reverse repo rate or reverse repurchase rate is applicable when a country's reserve borrows money from banks. If reverse repo rate rises, it means that banks will provide more funds to the reserve. This is a safe proposition as lending money to most reserves is an extremely safe financial transaction. In cases of reserves borrowing money from banks, excess money left with the particular bank is channeled into the reserve. This causes money to be taken out of the economic system. Reverse repo rates come into play when there is a fund shortage being faced by the reserve. The central bank manages short-term shortfalls and surpluses in the banking system through its liquidity adjustment facility (LAF), whereby it borrows and lends money at fixed rates under the repo and reverses repo facilities. Since the RBI technically has an unlimited capacity to lend and borrow money, the repo and reverse repo rates act as a ceiling and a floor for the interest rates. By reducing the reverse repo rate, the RBI has made it less attractive for banks to park money in the LAF window. So, banks would be forced to lend to corporates. Reducing the reverse repo rate will inject liquidity in the economy through corporate lending. Thus, the repo rate signifies the rate at which liquidity is injected in the banking system by RBI, whereas the reverse repo rate signifies the rate at which the central bank absorbs liquidity from the banks. 2.5 Stock market (Nifty) The artificial portfolio which is created to know the overall performance of different segments/companies is known as Index. 3. S&P CNX NIFTY which is the most tradable index in India, represents the economic condition and stability of financial markets with its growth prospects in long run. The Standard & Poor's CRISIL NSE Index 50 or S&P CNX Nifty nicknamed Nifty 50 or simply Nifty (NSE: ^NSEI), is the leading index for large companies on the National Stock Exchange of India. The Nifty is a well diversified 50 stock index accounting for 23 sectors of the economy. It is used for a variety of purposes such as benchmarking fund portfolios, index based derivatives and index funds. Nifty is owned and managed by India Index Services and 94

5 Products Ltd. (IISL), which is a joint venture between NSE and CRISIL. IISL is India's first specialized company focused upon the index as a core product. IISL has a marketing and licensing agreement with Standard & Poor's. Nifty has shaped up as the largest single financial product in India, with an ecosystem comprising: exchange traded funds (onshore and offshore), exchange-traded futures and options (at NSE in India and at SGX and CME abroad), other index funds and OTC derivatives (mostly offshore). The S&P CNX Nifty covers 23 sectors of the Indian economy and offers investment managers exposure to the Indian market in one portfolio. The S&P CNX Nifty stocks represent about 60% of the total market capitalization of the National Stock Exchange (NSE). 4. Review of literature In the development markets, many studies have been conducted to test the efficiency of capital markets with respect to monetary policy announcements. In India, only very few studies has been conducted. Some of the selected studies relevant to the present study are reviewed: Arijit Ghosh, et al: The following paper tries to investigate and predict optimal condition of the primary factors responsible for affecting Bombay Stock Exchange (BSE) in India. We considered the following determinants Oil prices, Gold price, Cash Reserve Ratio, Food Price Inflation, Call Money Rate, Dollar Price, F D I, Foreign Portfolio Investment and Foreign Exchange Reserve (Forex). We have taken into consideration the Multicollinearity problem among different macroeconomic variables and attempted to eliminate it. To do this analysis we have taken monthly basis database of different economical variables. Then we applied Factor Analysis to find out Factors affecting BSE Sense. We found that Dollar Price along with Factor 1 i.e; External Reserve and Factor score 2 i.e; Inflation Inertia are significantly affecting BSE Sensex. Then with the help of Linear Programming Problem the optimality conditions of the primary factors are traced out to ascertain the optimal value of BSE Sensex. T. Mallikarjunappa & Afsal: This paper studies the volatility implications of the introduction of derivatives on stock market volatility in India using the S&P CNX Nifty Index as a benchmark. To account for non-constant error variance in the return series, a GARCH model is fitted by incorporating futures and options dummy variables in the conditional variance equation. We find clustering and persistence of volatility before and after derivatives, while listing seems to have no stabilization or destabilization effects on market volatility. The postderivatives period shows that the sensitivity of the index returns to market returns and any day-of-the-week effects have disappeared. That is, the nature of the volatility patterns has altered during the post-derivatives period. Stefano (2004) evaluated the effects of monetary policy on stock market indices in the G-7 countries and Spain using the methodology of structural VARs. A model is estimated for each country and the effects of monetary policy shocks. Rudra and Indranil (2006) found that the RBI s policy actions had an impact in most segments of the financial market in India, its impact on the stock market was negligible. The authors employing a SVAR model, to ascertain whether the gradual emphasis on indirect 95

6 instruments have facilitated the task of conveying the monetary policy stance and also provide evidence of asymmetric response of financial markets to monetary policy shocks. Agrawal (2007) found that the random walk hypothesis implies the price movements that are virtually independent of past price movement, as the future prices is independent of such factors as volume of sales, short interest, odd-lot sales, and stock advances and declines. The study provided evidences that the random walk hypothesis may be incorrect or, at least incomplete. Martin et al. (2007) contributed to the literature measuring the response of stock markets to monetary policy actions. The study analyzed the reaction of European stock market returns to unexpected interest rate decisions by the ECB. Endogeneity between interest rate changes and stock returns is taken into account using the identification through heteroskedasticity approach. Relying on different methods to extract monetary policy shocks, the study found a negative and significant relation between unexpected ECB decisions and European stock markets performance. Ernst (2009) found that the impact of monetary policy surprises by the FED or Bundesbank/ECB on the return volatility of German stocks and bonds. The stock return volatility is susceptible to monetary policy surprises in the United States, whereas monetary policy surprises in the Euro zone matter for bond return volatility. These findings are robust for other Euro zone stock markets, but not significant for other Euro zone bond markets. 4 Research objectives 4.1 To study the impact of change in policy rates on Nifty movement. 4.2 To study the coorelationship between different variable like CRR, SLR, Repo Rate, Reverse Repo Rate and Nifty. 5. Research methodology Research methodology deals with a systematic and scientific methods that can be adopted to solve research problems. Methodology is a crucial step in any research because it directly influences the whole research and its findings. The research study carried out is casual research study. The data collected for the study is secondary in nature. The objective of the study is to carry out an econometric study of the impact of changes in CRR, SLR, Repo rate and reverse repo rate on foreign Exchange reserves. The following hypotheses are set for the study: Hypothesis: Hypothesis 1: CRR is positively correlated to Nifty. Hypothesis 2: SLR and Nifty are positively correlated. Hypothesis 3: Repo Rate and Nifty are positively correlated. Hypothesis 4: Reverse Repo Rate and Nifty are positively correlated. An econometric study of impact of changes in CRR, SLR, Repo and Reverse repo rate on Foreign Exchange Reserves is carried out during the period April 2006 to March

7 5.1 Data analysis and interpretations To test the above hypothesis, the data for CRR rate, SLR rate, Repo Rate, Reverse Repo Rate and Nifty is taken during the period April 2006 to March Table 1: Correlations Nifty CRR SLR Reporate Revreporate Pearson Correlation ** **.169 **.282 ** Nifty Sig. (2-tailed) N Pearson Correlation ** **.219 ** * CRR Sig. (2-tailed) N Pearson Correlation **.687 ** ** ** SLR Sig. (2-tailed) N Pearson Correlation.169 **.219 ** ** ** Reporate Sig. (2-tailed) N Pearson Correlation.282 ** * **.939 ** 1 Revreporate Sig. (2-tailed) N **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). The correlation between CRR & Nifty is highly significant (-.182, p=.000) indicating that both are negatively correlated, increase in CRR causes decrease in Nifty. Thus we can say that hypothesis 1 is rejected. The correlation between SLR & Nifty is highly significant (-.469, p=.000) indicating that both are negatively correlated, increase in SLR causes reduction in Nifty. Thus we can say that hypothesis 2 is rejected. The correlation between Repo Rate & Nifty is highly significant (.169, p=.000) indicating that both are positively correlated, increase in Repo Rate causes increase in Nifty. Thus we can say that hypothesis 3 is accepted. The correlation between Reverse Repo Rate & Nifty is highly significant (.282, p=.000) indicating that both are positively correlated, increase in Repo Rate causes increase in Nifty. Thus we can say that hypothesis 4 is accepted. Table 2: Collinearity Diagnostics a Mode l Dimensio n Eigenvalu e Condition Index Variance Proportions (Constant ) CRR SLR Reporat e Revreporat e a. Dependent Variable: Nifty High Condition index of & in Repo and Reverse Repo rate shows collinearity problem arises. 97

8 Table 3: Model Summary Model R R Adjusted Std. Error Change Statistics Square R Square of the R Square F df1 df2 Sig. F Estimate Change Change Change a a. Predictors: (Constant), Revreporate, CRR, SLR, Reporate The above model shows Adjusted R Square is 35.4 % i.e. less than 50% of the variance is explained by the variables in the model taken which is not good fit for the model. Table 4: ANOVA a Model Sum of Squares Df Mean Square F Sig. Regression b Residual Total a. Dependent Variable: Nifty b. Predictors: (Constant), Revreporate, CRR, SLR, Reporate The ANOVA shows the Model is fit for regression (F= , p=.000) Table 5: Coefficients a Model Unstandardized Coefficients Standardized Coefficients T Sig. Collinearity Statistics B Std. Error Beta Tolerance VIF (Constant) CRR SLR Reporate Revreporate a. Dependent Variable: Nifty Highly significant positive beta value( β=.682 (t=18.483, p=.000)) shows increase in 1 standard deviation of CRR will cause increase of.682 in Nifty. Highly significant negative beta value ( β=-.695 (t= , p=.000)) shows increase in 1 standard deviation of SLR will cause reduction of.695 in Nifty. Highly significant negative beta value ( β= (t= , p=.000)) shows increase in 1 standard deviation of Repo rate will cause reduction of in Nifty. Highly significant positive beta value( β=1.401 (t=17.159, p=.000)) shows increase in 1 standard deviation of Reverse Repo Rate will cause increase of in Nifty. 5.2 Limitations of the study The study is accepted at macro level. 98

9 5.2.2 The study was limited to Nifty during the study period April 2006 to March As the study was based mainly on secondary data, it is beset with certain limitations which are bound to arise while dealing exclusively with secondary data.\ 5.3. Conclusion Every year RBI changes the CRR, SLR, repo rate etc, to control the money supply of the country. This study is an effort to understand whether these ratios hold any informational content for the stock market that may lead to changes in the stock price. From the above study, it has been observed that the effect of CRR & SLR on nifty movement is negative as increase in these ratios means that banks have fewer funds available and money is sucked out of circulation, which affects the liquidity in the market & have ultimately negative impact on the stock market. Alternatively, the effect of Repo Rate & Reverse Repo Rate on nifty movement is positive. 6. References 1. Arijit Ghosh, Gautam Bandyopadhyay and Kripasindhu Choudhuri Forecasting BSE Sensex under Optimal Conditions: An Investigation Post Factor Analysis. 2. Bhattacharya, B, Mukherjee, J., (2002), The nature of the casual relationship between stock market and macroeconomic aggregates in India: An empirical analysis, Paper presented in the 4th annual conference on money and finance, Mumbai, India. 3. Bulmash, S.B., Trivoli, G.W., (1991), Time-lagged interactions between stock prices and selected economic variables, Journal of portfolio management, 17 (4), pp Chen, Nai-Fu, Richard Roll and Stephen A. Ross., (1986), Economic forces and the stock market. Journal of business, 59, pp Chien-Hsiu Lin., (2011), Exchange rate exposure in the Asian emerging markets, Journal of multinational financial Management, 21, pp Darat, A.F. and Mukherjee. T.K., (1987), The behaviour of a stock market in a developing economy, Economic letters, 22, pp Ming-Shiun Pan, Robert Chi-Wing Fok, Y. Angela Liu., (2007), Dynamic linkages between exchange rates and stock prices: Evidence from East Asian markets, International review of economics and finance, 16, pp Mirza Allim Baig, V. Narasimhan, M. Ramachandran (2003), Exchange market pressure and the Reserve bank of India s intervention activity, Journal of policy modeling, p Naveen Srinivasan, Sumit Jain, Ramchandran, (2009), Monetary policy and the behavior of inflation in India: Is there a need for institutional reform? Journal of Asian economics, 20, pp Pankaj Kumar and Pratik Mitra., Fiscal stance, Credibility and inflation persistence in India. RBI working paper series. 99

10 11. Pethe, A., Karnik, A., (2000), Do Indian stock markets matter? Stock market indices and macro economic variables, Economic and political weekly 35(5), pp Piti Disyatat, Gabriele Galati., (2007), The effectiveness of foreign exchange intervention in emerging market countries: Evidence from the Czech Koruna, Journal of international money and finance, 26, pp T. Mallikarjunappa and Afsal., The impact of derivatives on stock market volatility: A study of the nifty index Asian academy of management journal of accounting and finance. 100