A Review On Asset Pricing Literature

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

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.”

Nearly all investors look to beta as a way of feeling out the risk of a stock or fund. Put simply, beta measures volatility, or the tendency to swing up and down, as compared to a benchmark. Fund managers that take a bullish stance on the short-term horizon may actively stock up on high-beta equities to drive up returns. Controlling beta becomes an obsession for managers; and after they get the balance just right, they feel confident and reassured in their risk profile. Menchero, Nagy, and Singh concentrate on three estimates of beta to test the accuracy of the measure overall. The first, naive beta, makes a gross simplification that all stocks have a beta of 1. Second, the historical beta can be computed by comparing stock

The standard deviation provides an estimation of how far above or below the expected value the stock will be compared to the expected return, and the beta is the contribution of the stock to risk to a portfolio. In comparing the beta and standard deviation for the firms, we see correlation in some of the findings. CPB has the lowest standard deviation and a low beta from our calculations suggesting that the stock is

This document is authorized for use only by Yen Ting Chen in FInancial Markets and Institutions taught by Nawal Ahmed Boston University from September 2014 to December 2014.

Financial theory accepts the belief that a share’s return should be proportional to the risk received by its holder. There is a need of a risk-return equilibrium model. Since the nativity of the efficient market hypothesis (EMH), an equilibrium model was only the Capital Asset Pricing Model (CAPM). The CAPM constitutes of two types of returns, the risk free rate of returns of the Treasury bills and beta times the return on the market portfolio. The following equation is the basis of this model:

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.’

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].

Using time series regression on the monthly returns we have estimated the beta coefficient for each stock. Using the market model of CAPM i.e., regressing each stock’s monthly returns against the market index (Nifty100) we have estimated individual stock beta’s.

According to the CAPM model:R_i=α+βR_m+ε, α represent the abnormal return gained by the portfolio. If the market is efficiency, the α has to be zero.

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.)

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.

According to investment glossaries, a risk is a future probability of loss inherent in any investment (Investopedia Financial Dictionary, 2016). To this day, the positive correlation between risk and return continues to be the cornerstone of financial theory. The basic capital asset pricing model (CAPM) formula is built on this relationship. CAPM provides the required return based on the level of systematic risk of an investment. The risk associated with an investment is taken to lie along a scale. On the low-risk end of the scale, there are low yielding government bonds and securities. At the middle of the spectrum are medium performing investments – such as high yielding loan notes, and rental property. At the far end of the scale – high-risk – are futures, options, and equity investments. However, the positive relationship between risk and return does not guarantee that taking a greater risk will result in higher returns. Rather, a higher risk may lead to the loss of a greater amount of capital. This paper seeks to examine the risk and return relationship and how investors can determine the optimal trade-off.

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