Introduction
“Capital Asset Pricing Model”(CAPM) is a model created by Sharpe (1964), Lintner (1965), and Black (1972). According to Bhatnagar (n.d), “CAPM is regarded as being among the basic contributions to the finance area. It assumes that the equilibrium rates of return on all risky assets are a linear function of their covariance with the market portfolio” (Bhatnagar, n.d: 1). The work that was carried out in recent times by Fama and French (1996) and Fama and French (2006) brings in a “Three factor Model” which questions the application of the Capital Asset Pricing Model in the real world as well as the ability of this model to explain the stock returns and also the ability to give an explanation to the effects of a value premium in the US market.
This paper is going to discuss the issue that CAPM is a useful model and it is used widely in the industry even though it is based on very strong assumptions. The assumptions on which the CAPM model are based are going to be considered keenly and this will be followed by a discussion about arguments that have been presented against the applicability of the CAPM and particularly, a comparison is going to be carried out between CAPM and Fama and French’s “Three-Factor Model” and there is going to be defending of the continual use of the CAPM.
The Capital Asset Pricing Model
CAPM was “developed by Sharpe (1964), Lintner (1965), and Black (1972)” (Bhatnagar, n.d: 2). The impact of this model in the course of time has made several researchers such as Fama and French (2004) to come up with the suggestion that “the development of the CAPM marks the birth of Asset Pricing Models” (Fama and French 2004: 25).
Assumptions
This model is a one-period model. The major prediction carried out by this model is that “the market portfolio of invested wealth is mean-variance efficient resulting in a linear cross-sectional relationship between mean excess returns and exposures to the market factor” (Fama and French 1992: 433). CAPM is given by the equation;
“E(Ri) = Rf + Bi[E(Rm) – Rf] in this formula E(Ri) is the expected return of stock I, Rf is the risk-free rate of return, E(Rm) is the expected return of the market and Bi is COV (Ri, Rm) divided by VAR (Rm)” (Bhatnagar, n.d: 2).
To illustrate the applicability of this formula, Taking Rf to be 0.10, E(Rm) to be 0.14, and Beta to be 0.85, calculation of E(Ri) can be calculated as follows;
E(Ri) = 0.10 +.85(0.14 – 0.10) = 0.10 + 0.58 × 0.04 = 0.134
Thus in this case the expected return of stock i = 0.134
Assuming that the estimated return of stock was given by such a value as 0.125 or any other value below 0.134, the evaluation will indicate that the stock was overvalued and if the estimation is believed to be appropriate, then it would be recommended that this stock be sold. On the other hand, in the case where the estimated value is higher than 0.134, in this case, it would be said that the stock was undervalued and therefore it would be appropriate to buy this stock.
According to Bhatnagar (n.d) ‘the CAPM model assumes a linear relationship between expected return in a risky asset and its beta and also that beta is an applicable and sufficient measure of risks that capture the cross-section of average returns” (page 2). The average returns are driven by beta and this is for the reason that beta measures the amount of “additional stock” to a diversified portfolio that brings up the level of the “inherent risk” as well as the level of volatility of the portfolio.
As on one hand, the relationships given a description to by the CAPM have been the framework of several empirical types of research carried out by several researchers, on the other hand, the use of the model in the current applications by the finance managers and in the curricula concerning finance offers a chance to consider the importance of the model. Fama and French (2004) sums up the CAPM attractiveness when they point out that “the attraction of the CAPM is that it offers powerful and intuitively pleasing predictions about how to measure risk and the relationship between expected return and risk” (page 35) These authors as well provide the opinion they have in regard to the relevance of the CAPM model where they state that “unfortunately the empirical record of the model is poor – poor enough to invalidate the way it is used in applications” (Fama and French 2004: 37).
According to Bhatnagar (n.d), in the course of the 1980s, a number of researches carried out identification of extra factors which offer explanatory power apart from beta for “average stock returns”. Those variables which do not possess “special standing in asset pricing theory were shown to have reliable power in explaining across-section of returns”( Bhatnagar, n.d, 2). According to the findings of Banz (1981), the market equity I ME makes an addition to the “cross-section of expected returns” given out by the market beta.
According to the findings of Basu (1983), “low earnings-price ratios stocks help explain the cross-section of US stock returns while high earnings – price ratio experiencing lower returns” (page 143). The findings presented by DeBondt and Thaler (1985) show that the stocks having low long-term returns that are not normally going through “high long-term future returns” are not normal and vice versa.
Arguments against CAPM
Among the main empirical arguments that are made not in favor of the CAPM model is of Fama and French (1992). They come up with findings that show that cross-section of average equity returns in the US market shows a little statistical relation to the betas of the original CAPM model” (Fama and French 1992: 447). These researchers examined combined tasks carried out by the beta (market beta) the size of the firm, the earnings-price ratio the BE/ME within the “cross of average returns” on the NYSE,, AMEX and NASDAQ stocks. They establish that there is capturing of the BE/ME variables as well as the size of the “cross-sectional in average stock returns” that are linked and they come up with a conclusion that this goes against CAPM in the prediction as cross sectional association that exist between average surplus returns and contacts with the market factor.
Basing on the findings of Fama and French (1993), 5 general risk factors give an explanation to returns in bonds as well as stocks. In carrying out the evaluation of the association of stocks returns and risk factors, Fama and French (1993) make use of the “time series regression model” presented by Black, Jensen and Scholes (1972) to make out these factors. In their findings, they establish that 2 factors which are the BE/ME portfolio and the size of the firm give an explanation to those disparities that exist among the “average cross section returns of stocks”.
In their study carried out later, Fama and French (1996) make an observation that the trends of asset returns that were not normal which were seen in the course of the 1980s as well as in the 1990s could not be described by employing CAPM but are still owing to lack of specification in the “expected returns model”. They established that 2 other variables give an explanation of the important return trends. The two variables are SMB and HML. The resulting model is being thought out in the literature of Fama and French’s “Three Factor Model”
From more observation, Fama and French (1998) conclude that there is outperforming of the growth stocks by the value stocks in 12 main global markets out of 13 in the course of the period that started from the year 1975 up to the year 1995. The evidence they present give a suggestion that there is contradiction of CAPM ground rules in regions not within the US market.
From Fama and French’s (1993 and 1996) “Three Factor Model” conclusions have brought about arguments in the academic field. According to Miller 1999) “withstanding more than thirty years of intense econometric investigation, there is an agreement among academics that a single factor, as defined as beta, is insufficient to describe the cross section of expected returns” (Page 97).
Re-examination is carried out by Kothari, Shanken and Sloan (1995) of the findings given out by Fama and French (1993) by looking for a way to carry out the determination of whether or not beta gives description of the “cross sectional variation” in mean returns as well as whether or not there is capturing by BE/ME of the “cross sectional variation” in mean returns in the US market. These authors employ substitute source of data beginning the year 1947 up to the year 1987 to establish the fact that there is weak relationship between the mean stock returns and BE/ME.
They make identification of an important selection partiality brought in for BE/ME as well as the size of the firm selected portfolios because a large number of stocks having low ME as well as high ratios of BE/ME do not live on; they are eliminated away from basic records. They came to a conclusion that there is a likelihood that the findings obtained by Fama and French (1993) are under the influence of joint “survivorship bias in the COMPUSTAT database” (Page 21). More so, a suggestion is given by Black (1993) as well as by Mackinlay (1995) that the findings given out by Fama and French (1993) and Fama and French (1996) model will be realized in the most appropriate way by employing time periods that are not similar of observing and various countries.
A powerful association is found by Chan, Hamao and Lakonishok (1991) of average return BE/ME in the stock market of Japan. More so, empirical examination of the application of the Three Factor Model in the market of India was obtained by Connor and Sehgal (2001).
These authors as well establish confirmation of all-encompassing market and support the “Three factor Model”. A comparison between the CAPM performance and the performance of the Three factor Model was carried out by Drew, Tony and Veeraragavan (2005) for those equities that are listed in the stock exchange of Shanghai and influence of unpredictability. They came up with the results that showed that the size of the firm, factor market, BE/ME and the characteristic unpredictability are valued risk factors. The results they came up with are in line with those results that were obtained by Fama and French (1996).
Basing on the most recent research, Levy (2009) argues that the CAPM is still valid. He points out that “the CAPM can not be rejected on the empirical ground when ex ante rather than ex post parameter are employed.” (Page 43) According to him, there can be no obtaining of ex ante parameters empirically but experimentally instead. He further points out that “not only that CAPM is not refuted in behavioral economic framework; it gets strong support within this framework” (Page 71).
He goes on and points out that it is of great consideration to find out that the CAPM are “robust under wide possible frameworks, even when the empirical distributions of rates of return are not normal” (Levy, 2009: 43). He end s by saying that there can be continued utilization of the CAPM in the area of “academic research” as well as in practice for the reason of the CAPM not being rejected and even “strongly supported with ex ante parameters” (levy, 2009: 50). He appreciates that the issue that “it is is quite hard is to carry out estimation of the ex ante parameters but points out that there can not be counting of this as being a disadvantage of the capital asset pricing model because virtually all theoretical models encounter this issue” (Page 71).
Conclusion
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. It was “developed by Sharpe (1964), Lintner (1965), and Black (1972)” (Bhatnagar, n.d: 2). The impact of this model in the course of time has made several researchers Fama and French (2004) being among them to come up with a suggestion that “the development of the CAPM marks the birth of Asset Pricing Models” (Fama and French 2004: 25). There is no confining of the impact of this model on academic research. There is reliance by practitioners as well on the “Sharpe ratio” on a frequent basis which is dependent on “M-V model” and makes use of beta that is “derived from the CAPM as the risk index”.
However, the CAPM has been under great attack from the recent times which still goes on. Among the attacks are those that come up from “empirical studies in finance and economics, which reveal that the CAPM does not fit empirical asset pricing well” (Levy, 2009: 43).
The work that was carried out in the recent times by Fama and French (1996) and Fama and French (2006) bringing in TFM which questions the application of the Capital Asset Pricing Model in the real world as well as the ability of this model to give an explanation to the stock returns and also the ability to give explanation to the effects of value premium in the U.S market. Following this, several authors have come up with findings in regard to this in the area of finance which are of great importance in coming up with developments in the area. Levy (2009) is among the researchers that defend the continual use of the CAPM.
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