Introduction This paper aims to analyze the validity of the CAPM model of predicting returns for stocks by empirically testing the model with past financial data. The CAPM model is defined as R_i=r_f+ β_i (R_m-r_f). R_i represents the return on stock i, and is what the CAPM model attempts to define or predict. r_f represents the risk free rate available at the time the model is being analyzed, a figure that’s important for understanding both minimum return figures and the return premium offered by the market. β_i represents the Beta of stock i and is a measure of a given company’s volatility relative to the market they are in. If β_i is one, then the company is at market risk, if it is lower than one then it is below market risk, and if it is higher than one then it is above market risk. The only stock that would have a Beta of 0 would be a risk free stock, or whatever security you are using for your risk free rate. β_i is calculated as (COVARIANCE(r_i-r_f,〖 r〗_m-r_f))/(VARIANCE(〖 r〗_m-r_f)).(R_m-r_f) represents the Market Risk Premium, or the level of return an average stock in the market would return in excess of the risk free rate. Essentially CAPM attempts to study the amount of return generated by a company’s systematic, or market specific, risk, which is a type of risk that is undiversifiable. This means that CAPM tests for the amount of risk that a security has as compared to the market, which is a baseline level of risk that any firm that is publicly traded is
Fama and French’s three factor model attempts to explain the variation of stock prices through a multifactor model that includes a size factor and BE/ME factor in addition to the beta risk factor. Fama-French model essentially extended the CAPM (which breaks up cause of variation of stock price into systematic risk which is non-diversifiable and idiosyncratic risk which is diversifiable) by introducing these two additional factors. Fama and French find that stocks with high beta didn’t have consistently higher returns than stocks with low beta and this indicates that beta was not a useful measure under their model. Their model is based on research findings that sensitivity of movements of the size and BE/ME factor constituted risk, and
Here we choose VW NYSE, AMEX, and NASDAQ data as market returns, because it’s value weighted and more reliable. The results show CSC’s equity beta = 2.27, QRG’s equity beta = 1.79.
CAPM is a model that describes the relationship between risk and expected return, and the formula itself measures the expected return of the portfolio. Mathematically, when beta is higher, meaning the portfolio has more systematic risk (in comparison to the market portfolio), the formula yields a higher expected return for the portfolio (since it is multiplied by the risk premium and is added to the risk free interest rate). This makes sense because the portfolio needs to
The CAPM is a single factor model because it based on the hypothesis that required rate of return can be predicted using one factor that being systematic risk. It looks at risk and rates of returns, compares then to the stock market providing a usable measure of risk to help investors determine what return they will get for risking their money in an investment. There are a lot of assumptions and drawbacks of CAPM that lead to the conclusion that those investors utilizing this
Utilizing the fundamental concepts of the Capital Asset Pricing Model (CAPM), the expected return for Wal-Mart stock is 7.01% [E(R)]. This is a result of a risk-free rate (Rf) of 3.68%, which was the provided 10-year government bond yield to use as a proxy for the risk-free rate. The beta (β ) of Wal-Mart was 0.66 according to the provided Bloomberg beta estimate. Additional data was provided on the U.S. market risk premium [E(RM) – Rf] of 5.05%. In following the general concepts of CAPM, there are some general assumptions: no transaction costs, all assets are publicly traded,
CAPM results can be compared to the best expected rate of return that investor can possibly earn in other investments with similar risks, which is the cost of capital. Under the CAPM, the market portfolio is a well-diversified, efficient portfolio representing the non-diversifiable risk in the economy. Therefore, investments have similar risk if they have the same sensitivity to market risk, as measured by their beta with the market portfolio.
Investors hold diversified portfolios : One of the assumptions of CAPM model is that investors are holding only portfolios which are subjected to systematic risk , the unsystematic risk can be ignored , therefore the unsystematic risk has been ignored (Lakonishok & Shapiro , 1986)
CAPM on the other hand is based on microeconomic ideas such as concave utilities and costless diversification. Macroeconomic events mentioned include interest rates or the cost of labor, causes the systematic risk that affects the returns of all stocks. On the other hand the firm-specific events are the unexpected microeconomic events that affect the returns of specific firms for example the death of key people that would affects the firm, but would have a insignificant effect on the
In order to test the validity of the CAPM, we have applied the two-step testing procedure for asset pricing model as proposed by Fama and Macbeth (1973) in their seminal paper.
As indicated by the case study S&P 500 index was use as a measure of the total return for the stock market. Our standard deviation of the total return was used as a one measure of the risk of an individual stock. Also betas for individual stocks are determined by simple linear regression. The variables were: total return for the stock as the dependent variable and independent variable is the total return for the stock. Since the descriptive statistics were a lot, only the necessary data was selected (below table.)
Capital asset pricing model – is a statistical test that measures the difference between risk and reward. The main idea behind the test is that an investor should be compensated either by the amount of time money is invested or by its risk.
Richard Roll, and University and Auburn, University of Washington, and University of Chicago educated economist, began his career researching the effect of major events of stock prices. This experience likely helped him reach the two conclusions he makes in his 1977 “A Critique Of The Asset Pricing Theory’s Tests”, one of the earliest and most influential arguments against CAPM. In the paper, Roll makes two major claims: that CAPM is actually a redundant equation that just further proves the concept of mean-variance efficiency, and that it is impossible to conclusively prove CAPM. His first claim relates to mean-variance efficiency: the idea that mathematically one must be able to create a portfolio that offers the most return for a given amount of risk. Roll claims that all CAPM is doing is testing a portfolio’s mean variance efficiency, and not actually modeling out projected future returns. The second claim in the paper is that there is not enough data about market returns for CAPM to ever prove conclusive. Even if modern technologies could help alleviate some of the burden of testing market returns for publicly traded equities, there is still no way to account for the returns of less liquid markets, where there is less public information. This means it is impossible for
CAPM is a hugely popular model used in some capacity by virtually all major firms. The CAPM formula basically says that the expected rate of return on an asset is proportional to how much risk it contributes to the market portfolio. CAPM is represented by the formula: ri = rf + β(rm − rf), where ri is the required rate of return, rf is the risk free rate and β is the asset’s systematic risk. It says that the expected return of a security or a portfolio equals the rate on a risk-free security plus a risk premium. This figure essentially represents the cost of capital for a firm. It is an extremely popular model due to its simplicity and the ease with which it can be applied. There is however an increasing body of thought that the CAPM approach is in fact outdated and not a reliable model with which to evaluate cost of capital. Some of the chief arguments against CAPM are that it only holds under very unrealistic assumptions and another huge issue with CAPM is what is now known as the size effect.
The main purpose of this study is to investigate the ability of two alternative models in finance, Capital Asset Pricing Model (CAPM) and Arbitrage Pricing Theory (APT), to explain the excess return of a portfolio of stocks in Saudi Stock Exchange (TADAWUL). The regression analyses were conducted on the portfolio, which consists of 54 listed and actively traded stocks in TADAWUL. Comprising the ex-ante sample from the period of January 2000 and December 2005 and the ex-post sample from the period of January 2006 and December 2008, this study shows that none of the conditions of the validity of the CAPM was satisfied as