Study on Monetary Policy and the Stock Market

Study on fiscal Policy and the Stock MarketM cardinaltary polity is the regulation of the interest estimate and coin communicate of a coun canvass by its Central Bank or national Reserve in other to achieve the major(ip) economic goals which intromit price stability, full employment, economic growth etc. The blood line commercialize on the other fade is often considered a primary index number of a countrys economic strength and development as it is a major source of savings and income for most individuals. score has shown that the thrift of any country moves strongly to movements in tenor prices and is replete with examples in which large swings in stock, ho utilize and exchange rate grocerys shinecided with prolonged booms and busts (Cecchetti, Genberg, Lipsky and Wadhwani, 2000). young happenings even confirm this as the latest economic recession was preceded by a crash in the stock market.As a result of the birth between the stock market and the economy, it is v ery important to the Central bank building that the stock market performs well as bad performance can bad disrupt the economy. This is because the stock market serves as a primary source of income and retirement savings to many and movements in stock prices can have a major effect on the economy as it exercises legitimate activities such as consumption, investments, savings etcWhile some economists say that fiscal polity decisions consider on stock price movements, some others believe that stock price movements depend on financial constitution decisions. In this paper, we disassemble both sides of the coin by looking at how stock markets react to monetary indemnity and how monetary policy reacts to movements in stock markets. This research work is aimed at determination out which granger causes which using the Granger Causality test. We depart also analyze the consanguinity between both interest rank and monetary policy and that between money supply and monetary poli cy.In section II, a thorough review of the relevant literature of the topic is carried out as we try to understand to a greater extent(prenominal) about the family between monetary policy and the stock market and the set up of both components (money supply and interest judge) of monetary policy 0n the stock market. In the next section, we describe the variables and information set use in the study and the empirical model is developed. Results are presented and discussed in the next section. We cogitate the paper in section V and suggestions for further studies are pointed out and policy implications are considered.REVIEW OF RELEVANT LITERATUREMonetary policy is one of the most effective tools a Central Bank has at its disposal (Maskay, 2007) and is used to achieve the macroeconomic goals set by the government. This is done by regulation the two components of monetary policy which are interest place and money supply to maintain balance in the economy. The stock market is an i mportant indicator of the wellbeing of the economy as stock prices reflect whether the economy is doing well or non. Movements in stock prices have a prodigious impact on the macroeconomy and are thitherfore likely to be an important operator in the determination of monetary policy (Rigobon and Sack, 2001). The stock market is a financial market where equities are bought and sold either as an IPO (Initial Public Offer) in the primary market or exchange of existing shares between interested parties in the secondary market. Although stocks are claims on strong assets and researchers have found considerable evidence that monetary policy can regard veritable stock prices in the short run (e.g Bernanke and Kuttner, 2005), monetary neutrality implies that monetary policy should non affect real stock prices in the long run (Bordo, Dueker and Wheelock, 2007).To understand the kinship between monetary policy and the stock market, we must first understand what monetary policy is. Lam ont, Polk and Saa-Requejo (2001), Perez-Quiros and Timmerman (2000) among others use change in market interest rates or official rates as their rhythms of monetary policy. This measure of monetary policy, however, coincides with changes in business cycle conditions and other relevant economic variables. Christiano, Eichenbaum and Evans (1994) extracted monetary policy as the orthogonalized innovations from VAR models proposed by Campbell (1991) and Campbell and Ammer (1993). Research orderology based on this has shown that the response of US stocks returns to monetary policy shocks based on federal playfulness rates show that returns of large firms react less strongly than those of small firms (Thorbecke, 1997), that the overall policy for stock returns is quite low ( Patelis, 1997) and that international stock markets react to both to changes in their local monetary policies and that of the United states ( Conover, Jensen and Johnson ( 1999). Monetary policy shocks that are ext racted from structural VAR models or from changes in interest rates using monthly or every quarter selective information are likely to subject to the endogeneity problem i.e they are unlikely to be purely exogenous ( Ehrmann and Fratzscher, 2004). Another VAR-based method was used by Goto ad Valkanov (2000) to condense on the covariance between inflation and stock returns while Boyd, Jagan and Hu (2001) considered the linkages between policy and stock prices. Their analysis did not focus directly on monetary policy rather it focused on markets response to employment news (Bernanke and Kuttner, 2005).In their own research paper, Ehrmann and Fratzscher (2004) find that SP euchre shows a strong effect of monetary policy on equity returns, that the effect of monetary policy is stronger in an environment of annexd market uncertainty, that that negative surprises ( i.e monetary policy has tightened less and loosened to a greater extent than anticipate) has larger effects on the stock market than incontrovertible surprises, that small firms are react more to policy shocks than large firms, that firms with low cash flows are affected more by US monetary shocks and that firms with poor ratings are more prone to monetary policy shocks than those with good ratings. They find that firms react more strongly when no change had been expected, when there is a directional change in the monetary policy stance and during periods of high market uncertainty.There has also been cross-sectional dimensions of the effect of monetary policy on the stock markets in literature though few. Hayo and Uhlenbruck (2000), Dedola and Lippi (2000), Peersman and Smets ( 2002), Ganley and pink-orange (1997) etc are some economists who have analyzed this and overall, their findings show that the stock prices of firms in cyclical industries, capital-intensive industries and industries that are relatively open to trade are affected more strongly by monetary policy shocks (Ehrmann and Fratzscher , 2004).According to Bernanke and Kuttner (2005), changes in monetary policy are transmitted through the stock market via changes in the determine of private portfolios (wealth effect?), changes in the cost of capital and by other mechanisms. In their paper, they analyzed the stock markets response to policy actions both in the aggregative and at the level of industrys portfolios and they also tried to understand the reasons for the stock markets response. Their findings show that monetary policy is, for the most part, not directly attributable to policys effects on the real interest rate instead it seems to come either through its effects on expected future excess returns or expected future dividends.While economists commonly associate restrictive/expansive monetary policy with higher/ displace levels of economic activity, financial economists discuss various reasons why changes in the discount rate affect stock returns. (Durham, 2000) Changes in the discount rate affect the expe ctations of corporate profitability ( Waud, 1970) and discrete policy rate changes influence forecasts of market determined interest rates and the equity cost of capital ( Durham, 2000).Modigliani (1971), suggests that a decrease in interest rates boosts stock prices and therefore financial wealth and lifetime resources, which in turn raises consumption through the welfare effect. Mishkin (1977) on the other hand suggests that lower interest rates increase stock prices and therefore decrease the likelihood of financial distress, leading to change magnitude consumer durable expenditure as consumer liquidity concerns abate (Durham, 2000).Tobins q is the equity market value of a firm divided by its book value. It can also be defined as the ratio of the market value of a firms existing shares to the successor cost of the firms physical assets. Higher stock prices reduce the yield on stocks and reduce the cost of financing investment spending through equity issue (Bosworth, 1975). Tob ins q explains on e of the mechanisms through which movements in stock prices can affect the economy the wealth channel. The other channels of monetary policy transmission allow in the interest rate channel and the exchange rate channel. The wealth channel has the investment effect, wealth effects and balance sheet effects (www.oenb.at/en). Bernanke and Blinder (1992) and Kashyap, stein and Wilcox (1993) show that a tightening of monetary policy has a very strong impact on firms that highly depend on banks loans to financing their investments as banks reduce their overall supply of credit. Deteriorating market conditions affect firms by also weakening their balance sheets as the present value of collateral falls with salary increase interest rates and that this effect can be stronger for some firms than for others (Bernanke and Gertler 1989, Kiyotaki and Moore 1997). These two arguments are based on information asymmetries as firms for which more information is publically lenda ble may find it easier to collect loans when credit conditions become tighter (Gertler and Hubbard 1988, Gertler and Gilchrist 1994).Stock returns of small firms generally respond more to monetary policy than those of large firms ( Thorbecke 1997, Perez-Quiros and Timmermmann 2000).Some economists (Sprinkle (1964), Homa and Jaffee (1971), burger and Kochin (1972)) in the early 1970,s alleged that past data on money supply could be used to predict future stock returns. These finding where not in line with the efficient market hypothesis which states that all available information should be reflected in current prices (Fama, 1970) meaning that anticipated information should not have any effect on current stock prices. Most economists believe that stock prices react differently to the anticipated and unanticipated effects of monetary policy ( Maskay, 2007).The Keynesian economists lay out that there is a negative relationship between stock prices and money supply whereas real activit y theorists argue that the relationship between the two variables is verifying (Sellin, 2001). The Keynesian economists believe that a change in money supply or interest rates will affect stock prices only if the change in the money supply alters expectations about future monetary policy while the real activity economists argue that increase in money supply means that money imply is increasing in anticipation of increase in economic activity (Maskay, 2007). Another factor discussed by Sellin (2001) is the risk premium hypothesis proposed by Cornell i.e higher money supply indicates higher money demand and higher money demand suggests increased risk which leads investors to demand higher risk premiums for holding stocks making them less attractive. The real activity and risk premium hypothesis is combined by Bernanke and Kuttner (2005) who argue that the price of a stock is a function of the present value of future returns and the perceived risk in holding the stock.While advocates of the efficient market hypothesis hold that all available information is included in the price of a stock, the opponents argue otherwise and that stock prices can also be affected by unanticipated changes in money (Corrado and Jordan, 2005). The effect of anticipated and unanticipated changes in money supply on stock prices was analyzed by Sorensen (1982) who found out that unanticipated changes in money supply have a larger impact on the stock market than anticipated changes. Bernanke and Kuttner (2005) on the other hand analyze the impact of announced and unannounced changes in the federal funds rate and find that the stock market reacts more to unannounced changes than to announced changes in the federal funds rate which is also in line with the efficient market hypothesis. Studies by Husain and Mahmood (1999) have opposing results. They analyze the relationship between the money supply and changes (long run and short run) in stock market prices and find that changes in money s upply causes changes in stock prices both in the short run and long run implying that the efficient market hypothesis does not always hold.Maskay(2007) analyzes the relationship between money supply and stock prices. He also seperates money supply into anticipated and unanticipated components and adds consumer confidence, real GDP and unemployment rate as control variables. The result from his analysis shows that there is a positive relationship between changes in the money supply and the stock prices thereby supporting the real activity the theorists. The result from his analysis on the effect of anticipated and unanticipated change in the money supply on stock market prices shows that anticipated changes in money supply matters more than unanticipated changes. This supports the critics of the efficient market hypothesis.According to Cecchetti, et al. (2000), macroeconomic performance can be improved if the central bank increases the short-term nominal interest rate in response to temporary bubble shocks? that raise the stock price index above the value implied by economic fundamentals. On the other hand, Bernanke and Gertler (2001) delusive in their research that the Central Bank cannot tell whether an increase in stock prices is driven by a bubble shock or a fundamental shock.This study will analyze both exogenous and endogenous components of the relationship between monetary policy and the stock market i.e the effect of monetary policy on the stock market and the the effect if any of the stock market on monetary policy decisions. This particular analysis will be done using the federal funds rate as a representative of monetary policy. We also follow the methodology used by Maskay (2007) nigh as we try to find the effect of money supply on the stock market. Although Maskay used M2 as a measure of money supply, this study will separate money supply into M1 and M2 and analyze their relationship with the stock prices.Following from the theory and review of l iterature, this paper is aimed at answering the next questionsHow do movements in the stock market affect monetary policy decisions on federal funds rates?How does monetary policy affect stock market prices?Do stock market prices react differently to the M1 and M2 components of money supply?RESEARCH METHODOLOGYThe effect of stock market prices on monetary policy.In this section, I test for the relationship between monetary policy and stock prices using the Taylor rule. The Taylor rule is a monetary policy rule that stipulates how much the central bank would or should change the nominal interest rate in response to the divergence of positive inflation rates from channelize inflation rates and of developed GDP from potential GDP. The rule is written asit = r*t + ( t *t) + (yt t).. (1)Where it = target short-term nominal interest rate.r*t = pretended equilibrium real interest rate.t = the observed rate of inflation.*t = the desired rate of inflation.yt = the logarithm of real GD P.t = the potential production.But, to analyze the doings of monetary policy, the following lapse equation is estimatedit = + Et( t+i *t+i) +Et (yt+i+ t+i)+t ..(2)WhereEt = the expected value conditional to information available at the time.A good conduct of monetary policy should have and each equal to 0.5 as suggested by John Taylor.To conduct our study, we use the following equationit = + Et( t+i *t+i) +Et (yt+i+ t+i)+k t-k + t ..(3)Because the monetary authorities target variables other than inflation and output deviations from the target (asset prices in this case) thereby making equation (2) mis-specified. A standard Taylor rule is well specified when the monetary authorities target only inflation and output deviations from the target. The addition to this variable is the lagged change in asset prices which is added in order to determine the relationship between monetary policy and stock prices.The data for the cost-of-living index (Consumer Price Index), real GDP ( unr efined Domestic Product) and the federal funds rate are obtained from the IMF Washington website while the data for SP 500 Index are obtained from the federal official Reserve Economic Data (FRED) of the federal official Reserve Bank of St Louis website www.federalreserve.gov.The effect of monetary policy on stock market prices.In this section, we test whether movements in stock prices are sometimes aquiline on monetary policy. This test is carried out by regressing the actual change in federal funds rates upon the SP 500 index. We us the following simple model for this purposeSP500 = 1 + 2*actual change in federal funs rate + 3*real GDP + 4* unemployment rate.Real GDP and Unemployment rate are added as control variables. The data for real GDP is obtained from IMF, Washington while the data for unemployment rates in obtained from www.federalreserves.gov.We add GDP because it is an important determinant of the stock prices as most industries react to changes in the economy and do we ll as the economy does well and vice versa i.e they are procyclical in nature. When the GDP is low, the stock prices generally tend to be low, as the companys performance would be worse than before. A direct, positive relationship is expected between stock prices and the GDP.Unemployment rate is also used as a control variable in this model because it is one of the major factors that determines the demand for stocks thereby either driving the stock prices up or down. When the unemployment rate is high, demand for stock reduces as less people can reach to buy them and this subsequently drives down stock prices and vice versa. The unemployment rate is also a proxy for for overall aggregate demand in the economy ( Maskay, 2007) and when it is low, aggregate demand is high. We expect an inverse relationship between the unemployment rates and stock prices.The effect of M1 and M2 components of money supply on stock prices.In this section, we test the relationship between monetary policy and stock prices from the money supply angle of monetary policy. We use the M1 and M2 components of money supply for this analysis. This is done by first exam the relationship between the percentage change in M1 and the stock prices and then testing the relationship between M2 and the stock market.The simple empirical model used for this test isSP500 = 1 + 2*%M1 + 3*Real GDP + 4*Unemployment rate.. (1)SP500 = 1+ 2*%M2 + *3Real GDP + 4*Unemployment rate.. (2)Unemployment rate and real GDP are also used here as control variables for the kindred reasons disposed above. The data on percentage change in M1 and M2 were obtained from Federal Reserve Economic Data from the website of the Federal Reserve Bank of St. Louis. We were able to get the monthly data of M1 and M2 and then got the quarterly averages to produce the quarterly data.selective information DESCRIPTIONIn this section, we define and describe the various data used in this study. We used quarterly data from 1990 to 2009. T he variables used in this analysis includeThe Federal Funds RateThe federal funds rate is a monetary policy tool used by the Central Bank/Federal reserve of the country to regulate the economy. Economists believe it has an inverse relationship with stock prices as because when there is an upward movement in stock prices above the enviable level, the federal reserve increases (contractionary) the federal funds rate . This leads to a decrease in the amount of money demanded by individuals thereby causing a lower demand for stocks and pushing down stock prices. We obtained data on the federal funds rate from the website of the federal reserve bank of Louisiana.2. The Consumer Price IndexA consumer price index (CPI) is an index that estimates the average price of consumer goods and services purchased by households. It is used in our study to calculate inflation. We do this using the eviews software (100 (cost-of-living index cpi ( -4)). We obtained the quarterly data on CPI from the website of the International Monetary fund in washington. The CPI has an inverse relationship with monetary policy actions.3. Real Gross Domestic Product (Real GDP)This can be defined as a measure which adjusts for inflation and reflects the value of all goods and services produced in a given year, expressed in base year prices. Real GDP provides a more accurate figure as it accounts for changes in the price level. The quarterly data on Real GDP is obtained from the website of the International Monetary Fund, Washington.4. SP 500It is a capital weighted index of the prices of 500 large-cap common stocks actively traded in the United States. It is believed to have an inverse relationship with monetary policy as an expansionary (interest rate reduction) monetary policy leads to an upward movement of the sp500 index. The quarterly data for the sp500 is obtained from the federal reserve bank of Louisiana.5. Unemployment RateThe unemployment rate is used as one of the control variables. It is an important indicator of the wellbeing of an economy. The lower the unemployment rate, the higher the aggregate demand for stock thereby pushing up stock prices. The quarterly data on unemployment rate is obtained from the website of the Federal Reserve Bank of Louisiana. We get the quarterly data by finding quarterly averages from the monthly data provided.6. Monetary aggregates M1 and M2M1 is a monetary aggregate and it includes the transaction deposits of banks and cash in circulation and all other money equivalents that are easily convertible into cash while includes M1 plus short-term deposits in banks and 24-hour money market funds. Money supply has a positive relationship with stock prices because the higher the money supply, the higher the demand for stock which eventually increases stock prices. We split money supply into M1 and M2 to find out if they have the same relationship with stock prices. The quarterly data on percentage change in monetary aggregates is obta ined from the website of the federal reserve bank of Louisiana. We also had to calculate the quarterly averages of the monthly data given.DATA ANALYSIS cast 1 The Taylor ruleit = r*t + ( t *t) + (yt t)+ tDependent Variable FED_FUNDS_RATE system to the lowest degree SquaresDate 07/05/10 condemnation 2019Sample(adjusted) 19911 20094Included observations 76 after adjusting endpointsVariableCoefficientStd. Errort-StatisticProb.C3.6155131.2207832.9616340.0041INFLATION0.6842640.1562124.3803480.0000OUTPUT_GAP-1.42E-069.83E-07-1.4428030.1534R-squared0.249642 call up hooklike var3.860658 adjust R-squared0.229085S.D. dependent var1.686064S.E. of regression1.480394Akaike info criterion3.661167Sum squared resid159.9844Schwarz criterion3.753170Log likelihood-136.1244F-statistic12.14348Durbin-Watson stat0.181830Prob(F-statistic)0.000028The musical theme results areit =3.62 + 0.68( t *t) 1.42 (yt t)The coefficient associated to inflation is positive, 0.68, but is statistically significant with a p-value of 0.00. The coefficient associated with the output gap is negative (-1.42) and statistically significant. The estimated stabilizing rate of interest (c) is positive (3.61) and statistically significant. An R-squared of 0.25 means that we are only able to explain about 25% of the variability in the interest rate.The augmented taylor rule modelit = + Et( t+i *t+i) +Et (yt+i+ t+i)+1 t-1 + t one lagDependent Variable FED_FUNDS_RATEMethod Least SquaresDate 07/05/10 Time 2130Sample(adjusted) 19913 20094Included observations 74 after adjusting endpointsVariableCoefficientStd. Errort-StatisticProb.C8.2989611.2808936.4790440.0000INFLATION_F0.5489990.1811983.0298250.0034OUTPUT_GAP_F-9.10E-061.51E-06-6.0419260.0000S(-1)4.24E-057.35E-065.7757670.0000R-squared0.442430Mean dependent var3.809595Adjusted R-squared0.418534S.D. dependent var1.678852S.E. of regression1.280190Akaike info criterion3.384432Sum squared resid114.7220Schwarz criterion3.508976Log likelihood-121.2240F-statist ic18.51494Durbin-Watson stat0.214690Prob(F-statistic)0.000000InterpretationThe estimated regression isit = 8.30 + 0.55Et( t+i *t+i) -9.10Et (yt+i+ t+i)+4.24t-kThe coefficient associated to expected inflation is positive (0.55) but is statistically significant because it has a p-value of 0f 0.003, the coefficient associated with expected output gap is negative (-9.10) and is statistically significant (p-value = 0.000). The coefficient associated with the change in asset prices (lagged by 1 for better estimation) which is denoted by S (-1) is negative and it is statistically significant therefore we reject the null hypothesis. The measure of goodness of fit (R-square) is 0.44 meaning that we are able to explain about 44% of the variability in the interest rateOur model consistently overestimates the actual interest rate and the residuals do not seem to be independently and identically distributed. We therefore conduct some tests which include1. The Jacque-Bera test This is a statistic that measures the end of the skewness and kurtosis of the series with those from a normal distribution.By simply looking at the histogram, we can see that the distribution is roughly normal and the jarque-bera statistic of 0.58 shows that it is not statistically significant and we should accept the null hypothesis.The white test This is used to test whether the errors are heteroskedastic or not. In the presence of heteroskedasticity, OLS estimates are consistent but efficient. unobjectionable Heteroskedasticity TestF-statistic3.846209Probability0.000621Obs*R-squared25.97528Probability0.002062Test EquationDependent Variable RESID2Method Least SquaresDate 07/06/10 Time 0041Sample 19913 20094Included observations 74VariableCoefficientStd. Errort-StatisticProb.C-35.2896124.46199-1.4426300.1540INFLATION_F-5.4196573.008210-1.8016220.0763INFLATION_F20.3072310.2002861.5339610.1300INFLATION_F*OUTPUT_GAP_F5.95E-062.83E-062.1055860.0392INFLATION_F*S(-1)-2.78E-051.73E-05-1.6033610.1138OUTPUT_ GAP_F9.90E-055.34E-051.8525580.0686OUTPUT_GAP_F2-6.19E-112.74E-11-2.2572880.0274OUTPUT_GAP_F*S(-1)3.35E-101.43E-102.3372900.0226S(-1)-0.0003090.000140-2.2052820.0310S(-1)2-7.97E-115.33E-10-0.1496790.8815R-squared0.351017Mean dependent var1.550298Adjusted R-squared0.259754S.D. dependent var1.968439S.E. of regression1.693596Akaike info criterion4.016674Sum squared resid183.5692Schwarz criterion4.328034Log likelihood-138.6169F-statistic3.846209Durbin-Watson stat0.580160Prob(F-statistic)0.000621According to the two test statistics knotted in the regression result, we can say that the distribution is statistically significant so we can reject null hypothesis.The Durbin-Watson test This is used to test for resultant correlation. Autocorrelated residuals means that OLS is no longer best, linear, unbiased estimators and that the standard errors computed using the OLS formula are not correct. The Durbin-Watson statistic of 0.214690 shows that there is positive serial correlation as DWModel 2SP500 = 1 + 2 federal funds rate + 3real GDP + 4unemployment rate.The aim of this model is to determine if the federal funds rate has any impact on the stock market. Real GDP and unemployment rate are used as control variables for reasons given in the research methodology.Dependent Variable SP500Method Least SquaresDate 07/06/10 Time 0138Sample 19901 20094Included observations 80VariableCoefficientStd. Errort-StatisticProb.C-115.7008222.2313-0.5206320.6041FED_FUNDS_RATE0.99030112.964360.0763860.9393REAL_GDP010.1595380.01032715.449160.0000UNEMPLOYMENT_RATE-119.567417.42177-6.8631010.0000R-squared0.872734Mean dependent var924.0339Adjusted R-squared0.867710S.D. dependent var378.2205S.E. of regression137.5651Akaike info criterion12.73478Sum squared resid1438237.Schwarz criterion12.85388Log likelihood-505.3912F-statistic173.7244Durbin-Watson stat0.350064Prob(F-statistic)0.000000InterpretationThe estimated regression issp500 =-115.78 + 0.99*actual change in federal funds rate + 0.16*rea l GDP 119.57* unemployment rate.The coefficient associated with the federal funds rate is negative and is not statistically significant. The coefficient associated with the real GDP is positive and is statistically significant while the coefficient associate