Literature Review: The Fama-French Three Factor Model

Capital markets provide a function which facilitates the buying and selling of long-term financial securities to increase liquidity and their value, Watson & Head (2013). Hence, the Efficient Market Hypothesis (EMH) explains the relationship that exists with the prices of the capital market securities, where no individual can beat the market by regularly buying securities at a lower price than it should be. This means that in order to be an efficient market prices of securities will have to fairly and fully reflect all available information, Fama (1970). Consequently, Watson & Head (2013) believe that market efficiency refers to the speed and quality of how share price adjusts to new information. Nevertheless, the testing of the efficient markets has led to the recognition of three different forms of efficiency in which explains how information available is used within the market. In this essay, the EMH will be analysed; testing of EMH will show that the model does provide strong evidence to explain share behaviour but also anomalies will be discussed that refutes the EMH. Therefore, a judgment will be made to see which structure explains the efficient market and whether there are some implications with the EMH, as a whole.

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

As Chapter 10 questions, if further evidence continues to surface that capital markets do not always behave in accordance with the efficient market hypothesis, then should we reject the research that has embraced the EMH as a fundamental assumption? In this regard we can return to earlier chapters of this book in which we emphasised that theories are abstractions of reality. Capital markets are made of individuals and as such it would not (or perhaps, should not) be surprising to find that the

Harry Markowitz 1991, developed a theory of “Portfolio choice”, that allows the investors to examine the risk as per the expected returns. In modern World, this theory is known as Modern portfolio theory (MPT). It attempts to attain the best portfolio expected return for a predefined portfolio risk, or to minimise the risk for the predefined expected returns, by a careful choice of assets. Though it’s a widely used theory, still has been challenged widely. The critics question the feasibility of theory as a strategy for

In the Fama & French paper, they found that: 1) stocks with high beta did not have consistently higher returns than low-beta stocks; 2)

McCrae &Costa’s Five-Factor model of personality has become the dominant conception of personality structure (1985, 1987, and 1997). The Big Five Personality traits are said to be predictive of some kinds of behaviour such as honesty, job performance, and procrastination.

James Baron and David Kreps had given the Five-Factor model, which is based on Michael Porter’s Five Forces model of business analysis (Porter, 1980). These factors will influence the Competitive Intelligence system in any organization. These factors are External Environment, Workforce, Organizational Culture and Structure, Organizational Strategy, and Technology of Production and Organization of Work (Baron & Kreps, 1999). Lack of correspondence between any one of these factors can lead the firm’s CI practices to the failure.

The premise of an efficient market is that stock prices adjust accordingly as information is received. The speed and accuracy of the pricing changes are a reflection of the strength of the market efficiency, where in theory a perfectly efficient market will re-adjust prices immediately and precisely with new information. The efficient market hypothesis aligns with beliefs about whether technical and fundamental analyses are useful in making investment decisions or whether a passive approach is appropriate. In a perfectly efficient market, these types of analyses are not able to predict stock price trends (based on market inefficiencies or price abnormalities) which could assist in portfolio positioning or investment management. However, some investors belive that the market pricing is not precise and that there are timing windows and pricing trends that can be identified through analysis of past performance and finding price abnormalities where all information is not correctly reflected in the stock price (Hirt, Block and Basu, 2006).

‘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.’

future performances and ends with the choice of portfolio. This paper is concerned with the

Fama and French employ the one month NYSE stocks between 1926 and 1885 from the CRSP database. They rebalance ten decile portfolios based on the market value, price per share times share outstanding. One-month equal weighted portfolio returns are calculated and compounded continuously. The nominal returns ae adjusted by the CPI, and then summed on long rum returns. The estimation method for the regressions of r(t, t+T) on r(t-T, t) is the OLS.

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.

246). Samuelson’s dictum asserts that individual-firm stock price variations are dominated by genuine information about future cash flows of the firm, but they are not perfect indicators of these cash flows either. Cohen et al. (2001) used a method similar to that in Vuolteenaho (2002) to derive a decomposition of the cross-portfolio variance of the log ratio of book value to market value into three components: a component that could be justified in terms of information about future cash flow, a component related to the persistence of the value spread, and what we might call an ‘‘inefficiency component’’ that generates predictable future returns.2 They also used a longer sample period, an international data set, and some improvements in method. Their conclusions with U.S. data 1937–97 and 192,661 firmyears were that 80% of the cross-sectional variance in the log ratio of book value to market value can be justified by the first few components, only 20% by the inefficiency component that explains 15-year returns. Their conclusion with international data on 22 countries 1982–98 and 27,913 firm-years was that 82% of the cross-sectional variance of bookto-market values was explained by the first two components, and only 18% by the inefficiency component that explains five-year returns.

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

Historically, investors have proven the UIP wrong by gaining positive average returns on carry trade activities. However, these carry trades are uncertain as the returns derived reflect on a risk premium. Any risk based explanation for the returns to carry trades, requires us to identify the risk factors that contribute for the returns. Identifying the particular risk factor that causes fluctuations in returns and how it interacts with the result is to be studied. A few common traditional models that were built to understand these returns include, The Fama French three factor model, the CAPM the C-CAPM model to name a few. However these traditional models have been successful in explaining the returns to a stock market portfolio, but not the returns on carry trade. The do not provide