Are Small Cap Stocks Influenced Similarly and by the Same Economic Indicators as Large Cap Stocks - Essay Example

Your Are Small Cap Stocks Influenced Similarly and by the Same Economic Indicators as Large Cap Stocks: An Annotated Bibliography Thorbecke, W., & Coppock, L. (1995). Monetary Policy, Stock Returns, and the Role of Credit in the Transmission of Monetary Policy. Retrieved July 9, 2011, from Econpapers: http://econpapers.repec.org/paper/wpawuwpma/9902006.htm The authors Thorbecke (Resident Scholar at The Jerome Levy Economics Institute of Bard College in 1995) and Coppock (Professor, Department of Economics, Hillsdale College in 1995) conducted the study with the aim to verifying what percentage of the stock market variation can be explained by macroeconomic factors and monetary policy. The study used monthly data from 1974 to 1989 for macroeconomic indicators and for the Fed monetary policy (as independent variables) and used 39 portfolios of 10 value weighted stocks from large cap and small cap categories (as dependent variables) to study the volatility in stock return. They found that 32% of the stock market return volatility could be explained by the monetary policy which is similar to the finding of Chang, Yeung, & Yip. (2000) below that macroeconomic indicators do not fully explain the stock market movements. It was also found that 96% of the cases showed that a tightening of the monetary policy (reduced money supply) reduced stock returns. Further, the study found that while both small and large firms were harmed by the disinflationary monetary policy, only large firms benefited from expansionary monetary policy. The study illuminates the bibliographic topic by making a distinction between small and large cap stocks and the difference in effect of macroeconomic indicators on different stock categories. Chang, Yeung, & Yip. (2000). Analysis of the influence of economic indicators on stock prices using multiple regression. The authors at the time of the study were Doctoral Students at the University of Pennsylvania. They studied the impact of a set of 21 economic indicators and followed a regression analysis approach to identify whether economic indicators could explain the stock market movements from 1997 to 1999. For the stock market variable, they used S&P 500 index as the market reference. They first started with testing for correlation between the economic indicators and excluded some of them based on the statistical correlation. For the remaining indicators, they developed a multiple linear regression model to explain the stock price. They found that even after multiple regressions and excluding the insignificant variables, the resulting regression model could not fully explain the stock market movements. This finding is in line with that of Thorbecke and Coppock (1995) above. This study is of importance for the current research as I intend to use a similar methodology for multiple regression on 9 economic indicators in the US that this study found to be statistically significant in their regression model. Vygodina, A. V. (2006). Effects of size and international exposure of the US firms on the relationship between stock prices and exchange rates. Global Finance Journal 17 , 214-23. The author at the time of the study was a Professor at the Department of Finance, CBA, California State University at Sacramento. The research was aimed at studying whether the changes in exchange rates have a difference in impact on the stock prices based on the size of a firm. The methodology used was to conduct a Granger Causality test to verify the causality from large cap and small cap stocks to the exchange rate. The Granger Causality test was used in the study as it statistically tests whether one time series causes movements in another time series. It was found that while there did exist a statistically significant Granger Causality from large-caps to the exchange rate, there was no causality from small caps. The study also noted that the as both variables are significantly affected by the federal monetary policy and that the nature of relationship between stock prices and exchange rates is continuously changing too. This research is of importance for me as it takes into account a different methodology from one I intend to use (multiple regression). It would be important to compare the result of my research with the result of this research to check whether the two methodologies lead to a similar outcome. Tessaromatis. (2002). Stock Market Sensitivity to Interest rates and Inflation. Retrieved July 10, 2011, from http://mfs.rutgers.edu/MFC/MFC10/mfcindex/files/MFC-132%20Tessaromatis.pdf The author at the time of research was a researcher at the Athens Laboratory of Business Administration. The study was conducted to see the effect of interest rates and inflation on different industries and large/small cap indices in the US. It was concluded that except forestry and paper industry, all other industries, sectors and portfolios are negatively related to both nominal and real interest rates - Small caps as well as large caps respond negatively to interest rates. However, small caps are less sensitive than large caps to changes in nominal and real interest rates. This outcome is in line with the finding of Thorbecke & Coppock (1995) above. The study also found that equities are less sensitive to changes in inflationary expectations than to interest rates. The methodology used was a linear regression model derived through complex formulas to capture theoretical relationship between interest rates/inflation and stock prices. This study is important for the current research as it outlines the relationship between stock prices and inflation/interest rates. Maskay, B. (2007). Analyzing the Relationship between change in Money Supply and Stock Market Prices. Retrieved July 9, 2011, from Illinois Wesleyan University: http://digitalcommons.iwu.edu/cgi/viewcontent.cgi?article=1030&context=econ_honproj The author conducted this research as his Honors Project at the Illinois Wesleyan University. The aim of the study was to identify the relationship between stock prices, and anticipated and unanticipated money supply changes. The research was done by making a regression model comprising of change in M2 money supply, consumer confidence, Real GDP, and Unemployment rate as the independent variables to explain the dependant variable, the S&P 500 index. In his regression model, the author finds that these factors together can explain 87.3% of the S&P 500 movement. The model has all factors as statistically significant except consumer confidence. This result improves on the finding of Thorbecke and Coppock (1995) that monetary policy alone explains 32% of the stock price volatility. This research is of importance for my research as it describes the process of identifying what percentage of stock market can be explained by economic indicators. I intend to use a similar approach on both large and small cap stock indices to see which economic indicators in the regression model output explain what percentage of the large and small cap stock prices. References Chang, Yeung, & Yip. (2000). Analysis of the influence of economic indicators on stock prices using multiple regression. Maskay, B. (2007). Analyzing the Relationship between change in Money Supply and Stock Market Prices. Retrieved July 9, 2011, from Illinois Wesleyan University: http://digitalcommons.iwu.edu/cgi/viewcontent.cgi?article=1030&context=econ_honproj Tessaromatis. (2002). Stock Market Sensitivity to Interest rates and Inflation. Retrieved July 10, 2011, from http://mfs.rutgers.edu/MFC/MFC10/mfcindex/files/MFC-132%20Tessaromatis.pdf Thorbecke, W., & Coppock, L. (1995). Monetary Policy, Stock Returns, and the Role of Credit in the Transmission of Monetary Policy. Retrieved July 9, 2011, from Econpapers: http://econpapers.repec.org/paper/wpawuwpma/9902006.htm Vygodina, A. V. (2006). Effects of size and international exposure of the US firms on the relationship between stock prices and exchange rates. Global Finance Journal 17 , 214-23. Read More