Examining Assumptions And Empirical Testing

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

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

‘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.’

It would be great to live in a world where investing provided guaranteed payout with little or no risk, however, we all realize that is not the way investing works. Generally, the greater the risk, the greater potential for return or worse, loss. How we perceive and respond to risk is a very personal decision and there are several factors that go into making that decision. In this paper, I will discuss the risk of stock investing. There are two types of risk involved in investing in stock. One is diversifiable risk and is completely controlled by the investor. It means that a portfolio should be filled with stocks of varying degrees of risk. The other type of risk is market risk. The

Assumptions are important, but not in the way; many would think. The term assumption sometimes is associated with the word guess, but that’s not the meaning as it concerned statistics’ to ensure that your data. In the area of statistics ',’ the word assumption signifies completeness of the data collected (Triola, 2008) . The assumption aids the researcher in verifying the data because if the data does not meet the requirement, the researcher must, then treat the data in a different way to ensure the best interpolation of the data. Assumption is required in completing statically analyses: histograms, levenes test for homogeneity of variance, normality, normal pp-plots as well in the use of chi-square (Field, 2013; Hayes & Cai, 2007; Triola, 2008)witch use the assumption of random sampling. In the use of ANOVA method, the assumption of normality is the basis for the technique. Assumptions aid in identifying deviation of data as it concern normality. Perhaps one-way to identify or investigate deviation is to simply view a histogram from within a package such as SPSS, Minitab, SAS and Statdisk.

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.

The CAPM model can be used to analyze the performance of a portfolio of investments. The model should be calculated by comparing the return of assets (Ri) minus the return of risk-free cash (Rf) of the fund against those numbers of a known index with historical data (Rm). With least-squares regression, a straight line has to be drawn through the points to finish the model. Alpha represents the point where the graph starts and beta the slope of the regression line. Alpha is the number that represents the fact of how well the fund did against the CAPM model. A positive alpha means the fund did better than CAPM predicted and negative the opposite. R² represents the ‘fit’ of the

CAPM model builds on the model by Markowitz(1959).Markowitz assumes investors to be rational and risk averse. The model is one period model in which investor chooses portfolio at time t-1 in anticipation of stochastic return in period t. He uses mean variance criterion that states that investor will either choose highest expected return portfolio for given level of variance or lowest variance for a given level of expected returns

Even though many articles are conducted to critically study the capital asset pricing model ( CAPM ), it is widely used around financial

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 evidence gained from examination done by Nimal and Fernando (2013) concerning Tokyo Stock Exchange (TSE) and the Colombo Stock Exchange (CSE) confirmed not only that beta is a useful tool in expanding deviations in market premium, but also that there is a relation between return and beta. However, the previous research done in the Japanese market by Yonezawa and Hin, (1992) did not confirm the validity of the CAPM. In their research, they checked monthly returns from January 1952 to December 1986 and concluded that limited diversification was the main cause of CAPM failure.

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.

Capital Asset Pricing Model (CAPM) is an arithmetical theory that describes the relationship between risk and return in a balanced market. The Capital Assets Pricing Model was autonomously and simultaneously developed by William Sharpe, Jan Mossin, and John Litner. The researches of these founders were published in three different and highly respected journal articles between 1964 and 1966. Since its inception, the model has been used in various applications that range from public utility rates to corporate capital budgeting. However, the initial introduction of the model was characterized by suspicious view from the investment community. This was largely because CAPM apparently indicated that professional investment management was hugely a waste of time. Due to its implementation problems and shortcomings associated with its relation to Arbitrage Pricing Theory, Capital Asset Pricing Model has continued to face constant academic attacks.

A number of studies had provided support to the CAPM at the beginning (see King 1966, Brennan 1970, Levy 1997). However, a couple of method flaws were apparent with regard to the CAPM. First, the dependency on equity market indices as a proxy for market return. And here is where Roll (1976) argued that CAPM would not hold unless broad categories of assets are considered in the proxy. Roll’s argument implies misleading risk measurements for money managers if they apply that particular market beta. Second, the unrealistic assumption of one time period horizon of the investments decision was a critical issue. Thereafter, a major development arises when Merton (1973) relaxed that assumption by inventing the Intertemporal CAPM (ICAPM), which allows for changing portfolio components