The Capital Asset Prising Model

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

We use Capital Asset Pricing Model (CAPM) approach to calculate the cost of equity. The formula of CAPM is re = rf + β × (E[RMkt] – rf).

The Capital Assets Price Model (CAPM), is a model for pricing an individual security or a portfolio. Its basic function is to describe the relationship between risk and expected return, which is often used to estimate a cost of equity (Wikipedia, 2009). It serves as a model for determining the discount rate which is used in calculating net present value. The CAPM says that the expected return of a security or a portfolio equals the rate on a risk-free security plus a risk premium. The formula is:

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.

‘The Capital asset pricing model (CAPM) is a very useful model and it is used widely in the industry even though it is based on very strong assumptions. Discuss in the light of recent developments in the area.’

The capital asset pricing model can be used to determine the rate of return for an asset that is risky. This model aims at assuring that investors are compensated for the risk and the value of money. Therefore, the expected return on a security is equal to the rate of a risk-free security and the risk premium. Risk premium is the minimum amount of money expected in return of an asset that is risky. The risk premium must exceed risk-free and less risky assets.

The success of the model is attributed to Yale’s ability to combine both quantitative analysis (mean-variance analysis) with market judgments to structure its portfolio. In addition, Yale also uses statistical analysis to actively test their models with factors affecting the market, therefore understanding the sensitivity of their portfolio in response to various market changes. Yale also follows and forecasts the cash flow of private equity and real assets in its portfolio to decide the need for hedging.

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.)

There is great potential for large returns when investing in high-risk, aggressive shares, but there is no guarantee. As there are not many aggressive strategies that will work in every market, a maximum point could be selected that would lead to either the re-evaluation or liquidation of the investment when reached. Rubber Plc should also consider their investment time horizon– the longer the better when it comes to investing in aggressive shares. The preference for an extensive investment horizon is due to the fact that it will enable them to endure market fluctuations better. Since this type of investment is likely to be much more volatile, demanding more frequent alterations to adapt it to changing market condition, it requires a more active management rather than a conservative, buy-and-hold approach. The CAPM (Capital Asset Pricing Model) can be used by Rubber Plc to price the portfolio; it helps calculate risk and what type of return to be expected from the investment. The general idea behind the model is that investors should be compensated for their time value of money along with their risk. The model is described in this formula: expected return = risk free rate + Beta * (expected market return - risk free rate) If the aggressive shares have a beta of 1.5, for example, for every 10% increase in the market index return, the share return will increase by 15%. However, if the market return falls, then

Even though there are flaws in the CAPM for empirical study, the approach of the linearity of expected return and risk is readily relevant. As Fama & French (2004:20) stated “… Markowitz’s portfolio model … is nevertheless a theoretical tour de force.” It could be seen that the study of this paper may possibly justify Fama & French’s study that stated the CAPM is insufficient in interpreting the expected return with respect to risk. This is due to the failure of considering the other market factors that would affect the stock price.

Moreover, there are some cross-sectional predictable patterns, such as ¡®Value Stocks appear to provide higher rates of return than stocks with high price-to-earnings ratios¡¯ when accepting CAPM, Malkiel argues that the finding does not necessarily imply inefficiency of the financial market, it may only indicate failure of the CAPM to capture all dimensions of risk.

Over the past few decades, economists were continually developing a variety of asset pricing models. The first and the most important model is called Capital Assets Pricing Model, which was developed by William Sharpe, John Lintner and Jack Treynor (1964). It is based on the theory of composition and capitalization, which discussed the expected return and the relationship between risky assets in stock market. And now, Capital Asset Pricing Models becomes the pillar of multiple asset pricing models, and widely use in investment.

This study explores the (troubling) empirical evidence bearing on capital asset pricing theories. General formulas for the coefficient on beta and it standard error are derived, which show that the outcomes of cross-sectional tests have no causal relation to the pricing models. If a test refutes a model, this could be because the model is misspecified or because poor proxies for true expected returns and betas are used. Simulation and calibration results suggest that realized returns are a much poorer proxy than estimated betas are. The noise in realized returns typically inflates the estimated standard error, with drastic effects on the statistical power. Inferences based on ex ante returns are more powerful but suffer from a serious size problem. JEL: G12, C31, C52.

Capital asset pricing has always been an active area in the finance literature. Capital Asset Pricing Model (CAPM) is one of the economic models used to determine the market price for risk and the appropriate measure of risk for a single asset. The CAPM shows that the equilibrium rates of return on all risky assets are function of their covariance with the market portfolio. This theory helps us understand why expected returns change through time. Furthermore, this model is developed in a hypothetical world with many assumptions.