The Efficient Market Hypothesis and Michael Jensen Arguments - Essay Example

1.0Introduction The efficient market hypothesis indicates that since market prices reflect all available information, containing information about the future, the only difference between the stock prices at time t and time t + 1 are phenomenon that can not possibly be predicted. Hence, in an efficient market, prices can be statistically tested and investigated for the random-walk hypothesis. Fama (1991) describes market efficiency as: A market in which firms can make production-investment decisions, and investors can choose among the securities that represents ownership of firms' activities under the assumption that security prices at any time "fully reflect" all available information (Fama, 1991, p. 383) This part of the paper seeks to analyse the Jensen argument in 1978, quoted by Pike& Neale that the efficient market hypothesis is the "best established fact in all of social science". Whilst Neale & McElroy (2004) were less categorical "sometimes stock market valuations may look irrational. But in the longer term the markets are efficient processors of information and get valuation about right" Numerous papers have demonstrated that early identification of new information can provide substantial profits. Insiders who trade on the basis of privileged information can therefore make excess returns, violating the strong form of the efficient market hypothesis. Even the earliest studies by Cowles (1933,1944), however, make it clear that investment professionals do not beat the market. It has already been stated that an efficient market is one where the prices of securities fully reflect all available information, but then what are the sufficient conditions for capital market efficiency In an idealized world, such conditions would be No transaction costs in trading securities. All available information is available without cost to all market participants. All agree on the implications of current information for the current price and distributions of future prices of each security. Michael Jensen (1978) arguments were built on the above assumptions which today, many researchers have raised eyebrows to the validity of this statement. In this direction, the debate about market efficiency has resulted in thousands of empirical studies and literature attempting to determine whether particular markets are in fact 'efficient', and if so to what degree. In fact, the majority of studies and researches of technical theories have gone to the result that it is difficult to predict prices. No wonder, Neale & McElroy (2004) were less categorical, and stated that "sometimes stock market valuations may look irrational. But in the longer term the markets are efficient processors of information and get valuation about right" In addition, the random walk theory indicates that price movements will not follow any trends and so by knowing the past price movements it's not possible to predict the future price movements. All these state that markets are in fact efficient. However, researchers have also exposed many stock market anomalies that seem to be inconsistent with the efficient market hypothesis. Conclusion This section attempts an analysis of Michael Jensen 1978 arguments on the efficient market hypothesis. An attempt was also made to reconcile this statement with Neale & McElroy 2004 statement. From the above analysis, one can gently conclude that trading strategies seem to be widespread among fund managers and there is little evidence that they would generate excess returns in practice (Malkiel, 2003). Researchers have also exposed many stock market anomalies that seem to be inconsistent with the efficient market hypothesis. The end of the year effect, small firm effect is all good examples to this effect. The efficient market hypothesis has been challenged by numerous studies on the grounds that there are often underrreactions or overreaction of stock markets to information. (Baberies et al, 1998; Daniel et al, 1998; Hong and Stein, 1999). Accordingly, in a variety of markets, sophisticated investors can earn superior or riskless profits by taking advantage of market imperfections (underreaction or overreaction). 2.0Introduction The capital asset pricing model (CAPM) is a model that establishes the equilibrium relationship between the risk and return on a risky asset. (Bodie et al., 2005). The model has often been used by corporations during capital budgeting decisions to establish the appropriate discount rate for evaluating investments. In this paper, an explanation of how the CAPM can be used to determine the rate of return or discount rate to be used in evaluating an investment will be given. In addition considering that the theory of the CAPM is based on a number of underlying assumptions, this paper also seeks to explain how the model is sensitive to these assumptions that have generated heated debates in the press. The rest of the paper is organized as follows: This part of the paper attempts an analysis of Lungby & Jones (2003) argument that, although the CAPM is not a perfect and complete representation of the real world, it appears to be a fairly good representation of the real world and is, in many ways the best tool available to us" Understanding how to price risky assets or otherwise determining the cost of capital for risky investments has been a prominent problem in finance. (Furman and Zitikis, 2008). This has led to the development of a number of capital asset pricing models. (CAPMs) (Furman and Zitikis, 2008). The most frequently used of these CAPMs is that of Sharpe (1964), Lintner (1965) and Black (1972). The CAPM relates the expected return on an asset to the expected return on the market portfolio of all assets in the market. The CAPM states that "the expected excess return of any asset is linear in its covariance with the expected return on the market portfolio". (Hogson et al., 2001: p. 2). If we assume that Ri and Rm are random variables that represent the return on security i and the return on the market portfolio m, respectively, then under specific assumptions such as 1. the investor's utility functions are either quadratic or logarithmic, or 2. the pair (Ri, Rm) posseses the bivariate normal or elliptical distributions, The CAPM has been criticized as not a perfect complete representation of the real world based on the following underlying assumptions. Using first pass and second pass to test the CAPM as shown above have been criticized for a number of reasons. To begin with, the CAPM assumes that all investors can borrow at the risk free rate, secondly, it assumes that the market index included in the model is the true market portfolio and thirdly, the estimation of beta based on averaging returns has been blamed for a number of reasons. In addition, the Betas used from the first pass regression as inputs to the second pass regression are assumed to be constant through time. (Bodie et al., 2005). However, all these are casting doubts on using the CAPM to as a means of determining the discount rate to be used for evaluating investments. Today, however the CAPM appears to be a fair representation of the real world and in many ways the best available to us, because of its salient features over other models as the Arbitrage pricing model. For example, it is assumed that an investor will invest a negative proportion in the risk-free asset and a greater than one proportion in the risky asset. Such an investor will invest in security A as shown in the security market line (SML) in figure 1 below. Figure 1. The Security Market Line Source: (Ross et al., 2008) As can be seen, the less risk adverse investor bears more systematic, which is measured by the standard deviation (WM Stdev (RM)) of the portfolio. As we can see, this security has a higher return (RA). The variance of this portfolio is calculated by squaring the standard deviation, that is, WM2Var(RM) which is higher than the variance on the market portfolio. (Var2(RM)) since WM2 is greater than one. The expected return on portfolio A is greater than the expected return on portfolio M because the systematic risk component in portfolio A is higher than that for portfolio M. As earlier mentioned, this risk component is measured by beta and is calculated as shown in equation (2) above. Beta in equation 2 above measures the systematic risk of asset i relative to the overall risk in the market, given by the variance of the market portfolio. Thus, CAPM has been applauded because of its advantages over other models like arbitrage model. It remains the unique method of establishing a risk return relationship. However, it fails to adequately explain the variation in stock return, previous studies have proven that low beta stocks might offer higher return, and its assumption of the variance as an adequate measurement of risk. BIBLIOGRAPHY Bodie Z., Kane A., Marcus A. J. (2005). Investments. Sixth Edition. McGraw-Hill. Furman, Edward and Zitikis, Ricardas (2008). "General Stein-Type Decompositions of Covariances: Revisiting the Capital Asset Pricing Model". Available at SSRN: http://ssrn.com/abstract=1103333 Hodgson, Douglas J., Linton, Oliver B. and Vorkink, Keith (2001). "Testing the Capital Asset Pricing Model Efficiently Under Elliptical Symmetry: A Semiparametric Approach". Available at SSRN: http://ssrn.com/abstract=283364 or DOI:10.2139/ssrn.283364 Hong H., Stein J.C. (1999). A Unified Theory of Undereaction, Momentum Trading, and Overreaction in Asset Markets. Journal of Finance. Vol. 6, pp 2143-2184 Barberies N., Shleifer A., Vishny R. (1998). A model of investor sentiment. Journal of Financial Economics Vol 49, pp 307-343. Fama, E. F. (1991) Efficient Capital Markets: II. Journal of Finance, Vol. 46 Issue 5, p1575-1617. Fama, E. F. (1998) Market Efficiency, Long-term returns, and behavioural finance. Journal of Financial Economics. Vol. 49 pp 283-306. Myers S. C. Brealey R. (2002). Principles of Corporate Finance. Seventh Edition. McGraw-Hill Irwin. Ross, Westerfield, Jaffe & Jordan. (2008). Modern Financial Management", (authors), McGraw-Hill International Edition, 8th Edition, ISBN: 978-0-07-128652-7 Read More