Testing the Capital Asset Pricing Model And the Fama-French Three-Factor Model By Jiaxin Ling (Cindy) March 19, 2013 Key words: Asset Pricing, Statistical Methods, CAPM, Fama-French Three-Factor Model Abstract: This paper examines the Capital Asset Pricing Model(CAPM) and the Fama-French three-factor model(FF) and the Fama-MacBeth model(FM) for the 201211 CRSP database using monthly returns from 25 portfolios for 2 periods ---July 1931 to June 2012 and July 1631 to June 2012. The theory’s prediction is that the intercept should equal to zero the slope should be the excess return on the market portfolio. The findings of this study are not substantiating the theory’s claim for the fact that in some portfolios the alpha is …show more content…
3) One may observe that the data in period two is a sub period of period one and the beta is not stable over time for more portfolios have less than unit value beta in period two and some portfolios tend to be more volatile in the whole period (July 1931 to June 2012) but in sub period (July 1963 to June 2012) is less volatile than market level, take portfolio 24 as an example: its beta is 1.14 in period one and in period two its beta is 0.83. 2. The OLS cross-sectional test of the CAPM The CAPM states that the securities plot on the Security Market Line (SML) in equilibrium. We do cross-sectional test is to identify whether the above statement is true with our two data set and whether or not it rejects the hypothesis that the slope is zero. In the equation 3, the gamma 0 is the excess return on a zero beta portfolio and gamma 1 (the slope of the regression) is the market portfolio's average risk premium. [pic] (3) We perform the OLS cross-sectional test of equation (3) for both two periods. The results have shown in Table 3that gamma1 in time period 1 is positive (0.55) and it is statistically significant for its p value is 0.05, which implies that it rejects the null hypothesis of zero slope of the model. The gamma0 is also positive (0.26) which suggests that the cross-sectional return of 25 sample portfolios during July 1931
1. True or False: According to the CAPM, a stock's expected return is positively related to its beta.
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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.
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
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.
To find the asset Beta (βa), we need to find the weighted average β of equity and the weighted average β of debt. We consider the β of debt to be 0, as debt has no relationship with market risk and it is evident from the balance sheet that Ameritrade had no interest bearing debt in 1997[1].
To justify whether it works, we first ran a regression on the Three-Factor Fama French Model (Market Excess Return, SMB and HML) from Jan 1972 to Dec 2012 respectively for the High-, 5-, Low-, and High-Minus-Low Portfolio. Then, we added momentum into the model to create a four-factor model (Momentum, Market Excess Return, SMB and HML) for the same period on a monthly basis. (See Exhibit 2).
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9. (10 points) You are provided with the following monthly expected returns, each of which is represented by E(Ri), and betas for the following stocks. Please estimate the capital asset pricing model and draw conclusions about the significance and realism of the results. (Note: Please use conventional tests of the R-squared and coefficients.) On the basis of your results, please name at least three of the stocks that you would recommend as “buys.”
For estimation of betas, the above equation was run for the period from Jan, 2003 to Dec, 2006. Based on the estimated betas we have divided the sample of 63 stocks into 10 portfolios each comprising of 6 stocks except portfolio no.1, 5 and 10 having seven stocks each. The first portfolio 1 has the 7 lowest beta stocks and the last portfolio 10 has the 7 highest beta stocks. The rationale for forming portfolios is to reduce measurement error in the betas.
The extracted data used includes monthly returns from January 1972 to July 2011. The assets are selected so that the portfolio contains the largest, most liquid, and most tradable assets. The choice of such a variety of assets across several markets was used in order to generate a large cross sectional dispersion in average return. It helped to reveal new factor exposure and define a general framework of the correlated value and momentum effects in various asset classes.
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
The betas (slope of estimated regression equation) for the individual stocks can be obtained from the regression
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