Proper Application of CAPM Model - Essay Example

? Finance proposal Introduction 1 Setting In the modern world with growing complexities in the financial markets, the agents associated in the market face continuous difficulties in investment decisions and returns associated with them. Every individual in the business world are guided by the motive of profit maximization along with minimization of risks associated with the investments they make. The professionals engaged in the financial markets are always in a spree to develop appropriate financial models for helping the investors realize actual profits. One such common method used by the financial managers is Capital Asset Pricing Model (CAPM). The model is basically represented in a mathematical equation which is equated with the “expected rate of return on a stock to risk free rate plus a risk premium for the stock’s systematic risk” (Keown, 1998, p.242). Risk premium for a particular security is basically defined as the required return after deducting the risk free rate existing in the market. Total risk which is calculated as a standard deviation of return is generally fragmented into two parts. They are unsystematic and risk systematic risk, Beta () (Strong, 2008, p.168). The investors are rewarded bearing through this risk only and is very crucial. The equation for CAPM can be given as follows: ……….. (1) The above equation is a CAPM equation and it is also known as the security market line. In this equation, is the expected return, is the risk free return, is the required return for a particular market portfolio. , measure the systematic risk (Keown, 1998, p.242). 1.2 Application The model provides a logical approach for analyzing the return that an investor should receive from an investment. More interestingly, the model is applied in a wide spectrum in the field of modern finance for the purpose of estimating the cost of equity and the performance of a company. Evaluating performance of companies in a particular industrial area is of great importance as it reflects the economic functioning of the area and further decides the strength of investor’s attraction in that particular area (Armitage, 2005, p.278). 2. Research Aims and Objectives The rationale thus created is that the CAPM model helps to calculate expected return of an investor and evaluate the performance of the companies. The concentration in this paper will be on the later trajectory i.e. performance of the companies. The aim of the paper is to find proper application of CAPM model in a real world scenario. The objective of the paper is centered on finding out the intensity of the companies creating value for their shareholders with data on ten US companies listed in the New York Stock Exchange. 4. Research questions The research questions that will be discussed in this paper are discussed below: 1. What is the importance of CAPM model in corporate finance? 2. What are the fields where the model is applicable and what important results it yield? 3. What decision criterion the model generates that drives the financial managers to take important business decisions? 3. Research hypothesis The research hypothesis that will be tested in this paper can be represented in a tabular format as given below: H0: The companies selected are not performing strongly to create value for the shareholders H1: The companies selected are performing strongly to create value for the shareholders H0 is the null hypothesis which will be tested against the alternative hypothesis H1. The data and testing procedure will be explained in a detailed manner in the methodology section. Now, the subsequent section will focus on a brief literature review on this particular financial model i.e. CAPM. 4. Literature Review Rigorous testing has been employed with CAPM model in the last three decades. Studies of Jensen and Scholes in 1972, Blume and Friend in 1973, Reinganum in 1981, Banz in 1981 founded that there exist a positive correlation between the realized return and as well as that between risk and return is a linear function. Through the special prediction made by Sharp and Linter stated the portfolio independent with market possess market return which is equal to the risk free rate of return which is equal to risk free rate of interest is not a good predictor. The average return on zero Beta portfolios is basically greater than the risk free return. Majority of the early tests of CAPM have included first of calculating the Betas. After that, time series regression followed with a cross section of the regression has been used to test hypothesis as exhibited by the CAPM model. With respect to the test on the CAPM portfolios the classic test performed by Fama and Macbeth in 1973 included the time series and cross sectional analysis for the purpose of investigating the risk premiums of the factors in the second pass regression are non zero. Through the formation of twenty portfolios of assets, the researchers estimated the Beta coefficients and found that the beta was insignificant statistically with small values for various sub periods. Linter found out that there is an independent relation between the residual risk and security returns. However the findings revealed that the intercept term exceeded the risk free rates and also suggested that CAPM might not hold its validity. From the studies of Black and Jensen in 1972, testing CAPM with the help of time series regression analysis show that the intercept term is widely different from zero. They found that when the Beta is greater than 1, then the intercept term is negative and when the value of Beta is less than 1 then the intercept is positive. Their findings violate the CAPM. For the purpose of testing market efficiency studies of Fama in 1970 and 1991 holds significance. From the market efficiency hypothesis, the security prices reflect fully the available information. For CAPM, the asset prices must be the efficient prices. Thus in rejecting CAPM model, it sometimes becomes difficult in forecasting whether the risk return relation exhibited by this model is incorrect or directs towards market inefficiency. In the year 1992, the studies of Sauer and Murphy with the help of the German stock market stated that the CAPM model was the best model describing the stock returns (Javed, n.d., pp. 16-29). From the studies of Sharpe in 1964 and Linter in 1965 made a large number of assumptions and they theoretically extended the Markowitz’s mean variance model for the purpose of developing a synthesis expected returns which is the calculation made from deducting the risk free rate from return. The returns which they calculated were equated with the return of a security with return on excess market portfolio multiplied by Beta which is the measure of risk in the analysis. Majority of the tests of the CAPM have been executed through estimation by cross sectional relation among average return on the assets over their measure of systematic risk. This is over some interval of time and also directed towards comparing the estimated relationships delivered by the CAPM (Theriou et al, pp.3-4). Although through the studies it can be revealed that quite a few researchers have questioned its validity but it helps in the explanation of the common variability with respect to a single factor generating return for individual assets through linear relationship. The systematic risk of the model helps in the realizing the volatility of the stock and also imparts a good potential in testability. 5. Methodology The cost of equity will be a prime parameter in this paper while carrying out the data analysis and generate inferences. The cost of equity is calculated with the help of CAPM model which determines the economic value added (Savarese, 2000, p. 12). This helps in measuring whether the company is successful in creating value for the shareholders during the time frame chosen. A five year span from the year 2006 to 2011 is chosen. Ten US companies listed in the NYSE is taken. The list of the ten companies is shown in a tabular representation below: Serial no. Name of the companies 1. Actuant Corporation 2. Accenture plc 3. Acorn International, Inc. 4. Bally Technologies, Inc. 5. Bank of America Corporation 6. Target Corporation 7. Valley National Bancorp Warrants 8. Questar Corporation 9. Rackspace Hosting, Inc. 10. Ralph Lauren Corporation Table 1. Names of ten companies that will be used (Listing Directory, 2012) The companies in the above table are taken within the time span of five years starting from 2006 to 2011. The monthly ending price of the companies traded is incorporated as a market proxy. All the data are collected from the financial accounts of the company with prior consents from the officials in charge in the company. For the purpose of estimating the Beta of each firm simple linear regression is applied. Beta for the companies for each period is calculated through the application of regression modeling with dependent variable as the historical return of the stock of the companies and the independent variable as the return on the market at the corresponding period. The regression equation can be stated as follows: In the above equation, Y is historical return of the stock at any period and X is the return on the market at that period. is the stochastic parameter which follows all the assumptions of normal distribution. After estimating the systematic risk of the companies the cost of equity is calculated from the CAPM equation. Now the magnitude of cost of equity is calculated. If the magnitude of the cost of equity is positive then the company’s value addition is depicted on a positive angle and if the cost of equity is showing negative magnitudes then the value addition of the company is on a pessimistic dimension. Again the prime target of the paper is to analyze the performance of the companies. For this purpose another useful statistic was chosen which is known as the Jensen’s alpha. It is calculated from the CAPM equation. The statistic used basically captures the difference between a fund’s actual return and all those which can be made on a benchmark portfolio attached with the systematic risk. Jensen’s alpha helps in measuring the ability of the active management in increasing the returns (Sharpe, Treynor and Jenson’s ratios, n.d.). Now, the decision will be made on the basis of the magnitude of the Jensen alpha. If the magnitude of the Jensen alpha turns out be negative then it can be concluded that performance of the shares of the companies are not up to the mark. If the magnitude turns out to be positive then the companies are performing well. The Jensen’s alpha is given by the formula, Jensen’s alpha= (Jensen’s Alpha with Excel, n.d) 6. Expected Outcomes The study will highlight market performance of the companies. This will allow us to make a brief idea about the ways in which the companies are being able to manage the investments and creating value for their shareholders. Expected outcomes cannot be said in advance that whether the companies are performing well or not. This requires testing through the statistical models prescribed in the methodology section. The systematic risks of the companies calculated will be also important as it will be able to determine the volatility of the stocks. Higher the value of Beta it can be said that more volatile will the stock and vice versa (Understanding Risk, n.d.). 7. Potential Problems, Limitations and /or Ethical Issues Majority of the critiques have not expressed special emphasis on the CAPM model and has questioned its validity. However the systematic risk calculation of the model is of high significance and thus finds its validity and applicability. In the collection of data the officials from whom extraction of data have been executed, their names have been kept confidential. Same data are collected for all the companies. After the research paper is over the data will be destructed and will not be used up for any future references. 8. Timescale A Gannt chart can be appropriate to show the work plan of the project in a dynamic framework. This is shown in the following graph. Fig.1. Gantt chart The Gantt chart provided in the above figure represents the days required to complete the whole research process. The chart also helps in realizing the thorough schedule of the research process and plan with data on individual segments. References 1. Armitage, S, (2005), The Cost of Capital: Intermediate Theory, Volume 10, Cambridge University Press 2. Jensen’s Alpha with Excel, (n.d). Available at, http://investexcel.net/528/jensens-alpha-excel/ (accessed on December 12, 2012 3. Javed, A, Y, ( n.d.), Alternative Capital Asset Pricing Models: A Review of Theory and Evidence. Available at, http://www.pide.org.pk/research/report179.pdf (accessed on December 12, 2012). 4. Keown, A, T, (1998), Financial Fundamentals: financial management logic and practice, Tsinghua University Press Ltd. 5. Listing Directory, (2012). Available at, http://www.nyse.com/about/listed/lc_ny_name_R.html?ListedComp=All (accessed on December 12, 2012). 6. Savarese, C, (2000), Economic Value Added: The Practitioner's Guide to a Measurement and Management Framework, Allen & Unwin 7. Strong, R, A, (2008), Portfolio Construction, Management, and Protection: With Stock-trak Couponp., Cengage Learning 8. Theriou et al, (n.d.), Empirical Testing of Capital Asset Pricing Model. Available at, http://abd.teikav.edu.gr/articles_th/capital_asset_pricing_model.pdf (accessed on December 12, 2012). 9. Understanding Risk, (n.d.). Available at, http://www.tddirectinvesting.co.uk/get-started/understanding-risk/risk-and-return/ (accessed on December 12, 2012). Read More