There are many different asset pricing and portfolio management models available to assist us in the estimation and evaluation of a stock’s return. The Fama-French Model (“FFM”) is one of those models. Kenneth French and Eugene Fama who were professors at the University of Chicago Booth School of Business designed the FFM. Kenneth French and Eugene Fama observed that historically, the Capital Asset Pricing Model (“CAPM”), which was predominantly used, was inaccurate as it often resulted in high alpha values which meant that a huge portion of excess returns were left unexplained. They also observed that companies with smaller market caps would outperform companies with higher market caps and companies with higher book-to-market (“B/E”) …show more content…
This would form the excess returns that small firms have over larger firms and the firm specific beta will be assigned to it to formulate the value of SMB, accounting for the size risk factor. This is based on the assumption that smaller firms tend to experience higher excess returns. Accordingly, if β_SMB is larger than 0, it means that the portfolio would have higher expected returns signifying that it consist mostly of small companies and vice versa. This assumption is in line with the fact that smaller companies are riskier than larger companies. As the general rule that the higher the risk the higher the returns, it is only fitting that companies with smaller market caps thus higher risk would bring in higher returns. This occurs because the smaller firms are usually not very popular hence; there are not many investors that are interested in the stock consequently, the share price would be relatively low, giving it room to perform better. On the other hand, firms with larger market cap are traded often due to investor’s interest, causing their share price to be high. Evidence of this can be found in a report issued by a research company Duff and Phelps (2013). It shows that in a 30 year period, small companies has out performed large companies 92% of the time, further proving that size factor plays a huge part in evaluating the returns of a
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This paper was especially important, because it took all the research that had been done in the last 30 years and combined it into one formula, now known as the Fama-French Three Factor Model. What Fama and French did was using the old CAPM and then adding much of the critique explained in the above text. This gave some very interesting results. One of the first things they discovered was that the relation between the beta and the return was not quite true. Because of the (negative) correlation between company size and beta, beta and return only seemed to have a relation but when Fama and French adjusted for this correlation, the relation between beta and return pretty much vanishes. Because of this result, Fama and French decided to look for other variables that might explain the average returns. After some calculation, they tested whether size, E/P, leverage, Book to Market and beta, again following the findings that researchers had done before them. A few very important conclusions of their research are: 1) If variation in B that is unrelated to size is allowed, there is no reliable relation between B and average return. 2) The opposite roles of market leverage and book leverage in average returns are captured well by book to market equity. 3) The relation between E/P and average return seems to be absorbed by the combination of size and market to book equity. The latter means that there is no need to include E/P in the model, because the effect of E/P is already reflected by Size and Book to Market equity. With these findings, Fama and French completed their new model. This new Fama-French Three Factor Model was a severe blow for everybody that still believed in the power of the CAPM and it is not surprising that many scientists wanted to prove them wrong. In 1993 Fama and French extended on their paper from 1992 in three ways; they expanded the set of asset returns to be explained. The assets that
(a) Fama and French argued that value stocks outperformed growth stocks because they were risker. The outperformance is explained by the excess risk that value stocks face as a result of their higher cost of capital and greater business risk.
According to this Fama & French three factors model, there are two more variable added into the regression model. They are SML factor (the return of small cap companies minus the the return of large cap companies) and HML factor (the
Hence, Fama & French’s three factor model flourished when considering the market book value and the size of business. Additionally, in Fama and French’s (1996) paper, they concluded Sharpe – Lintner’s CAPM has never been an empirical success. According to the current study, the factors that affected the Beta are serious enough to invalidate most applications of the CAPM
While the CAPM uses the β largely as an adjusting factor, the FFM, mainly uses the two introductory factors for adjustments as their models reflect little to no adjustments to β causing a disconnection between the two models. If sensitivity to market risk as captured by β in CAPM does not motivate investors, it is, on the face of it, difficult to envisage how the book-to-market equity and firm size variables in the FFM can be expected to motivate them (Dempsey,
A lot of criticism on the CAPM has arisen over the last decades. One finding by Basu in 1977 is often used by opponents of the model in order to take down the foundation of the CAPM. Basu found that stocks with a low price –earnings ratio, called value stocks, tend to outperform stocks with a high price-earnings ratio, named growth stocks. As the CAPM only allows for fundamental risk to explain excess returns on stocks, the finding that stocks from companies with high fundamentals (earnings, sales, dividends) relative to price outperformed growth stocks was in contradiction with the classical CAPM.
Firm has a range of projects to be invested in or finance in to increase the value of the company. However, to increase the value of the company, firm need to choose the worth pursuing project. In this case, firm need to evaluate the projects which the evaluation of a project can be done by cash flow method.
Empirical studies show that these factors have exhibited excess returns above the market. For instance, the seminal Fama and French (1992) study found that the average small cap portfolio (averaged across all sorted book-to-market portfolios) earned monthly returns of 1.47% in contrast to the average large cap portfolio’s returns of 0.90% from July 1962 to December 1990.
Capital market has deep developed this century, more and more investors go into this market. Which security is better? How to invest? Investors need numeric index to make decision. There are some theories to help investors: portfolio theory, capital asset pricing model (CAPM), option pricing model and so on. This essay will explain portfolio theory firstly. Secondly, this essay will explain CAPM and discuss the importance of the assumptions of CAPM. Thirdly, this essay will explain arbitrage pricing theory (APT) and factors model. Finally, this essay will compare CAPM with APT and factors model.
This thesis paper compares the in and out of sample predicative accuracy of 3 CAPM based models, “The Capital Asset Prising model” Sharpe (1964), “The Three Factor Fama-French Model” Fama-French (1993), “The Fama-French Five Factor Model” Fama-French (2013). The relationship of in-sample model strength to out-of-sample predictive accuracy is to be determined, by dividing each models portfolio into four segments, High Adjusted R2 , Medium Adjusted R2, Low Adjusted R2, and a random mixture as the control. The research uses the S&P500 as the “market” portfolio. Using ten years of monthly data from the period between 1st January 2004 to the 31st November 2014, as in sample data. The portfolio returns were then monitored for an
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
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.
The Efficient Markets theory has been a source of much controversy within both the academic and financial worlds. Eugene Fama first defined an “efficient” market as “a market where, given the available information, actual prices…represent very good estimates of intrinsic values” (1965, p.90). After Harry Roberts (1967) formed the “Efficient Market Hypothesis(EMH)”, Fama then went on to publish results that concluded the stock markets are efficient. Thus it is impossible to achieve consistent abnormal returns. However, investors daily are seeking to defy the EMH and therefore the hypothesis is under constant audit 252 days a year.
Asset pricing takes a vital role in the literature of finance. It forms a cornerstone for participants trying to manifest intrinsic/predicted values/prices for assets. Since 1965, when Sharpe introduced his CAPM formula, the field of asset pricing had shifted to a new paradigm. The model of Sharpe suggested that market beta as a variable is sufficient to explain stock returns. Sharpe’s work was preceded by Markowitz (1959) portfolio theory, where the lack of computer power at that time makes the calculations of huge set of covariance between stocks an inflexible approach. From this perspective, accompanied with simple and strong theoretical grounds, the CAPM gained high credit.