Toillustrate the conflict between the EMH and behavioural finance, consider thefollowing example which involves an aspect of probability assessment in whichindividuals assign probabilities to events not according to the basic axioms ofprobability theory, but according to how representative those events were ofthe general class of phenomenon under consideration.
Two psychologists, Tverskyand Kahneman (1981) posed the following question to a sample of 86 subjects(Lo, 2005):”Lindais 31 years old, single, outspoken and very bright. She majored in Philosophy.As a student she was deeply concerned with the issues of discrimination andsocial justice, and also participated in anti-nuclear demonstrations. Pleaseclick off the most likely alternative” Despitethe fact that the ‘bank teller’ is in no way less probable than ‘bank tellerand feminist’, 90% of the subjects being tested, chose the second alternativebecause the latter classifies a more restrictive subset of the former. Tverskyand Kahneman (1981), established that as the amount of detail in a scenario rises,its probability can only fall steadily, but its representatives and hence itsapparent likelihood may increase. This behavioural bias is particularlyrelevant for the risk-management practice of “scenario analysis” in which theperformance of portfolios is simulated for specific market scenarios such asthe stock market crash of October 19, 1987. While adding detail inthe form of a specific scenario to a risk-management simulation makes it morepalpable and intuitive in Tversky and Kahneman’s (1981) context, more”representativeness” decreases the likelihood of occurrence. Therefore, decisionsbased largely on scenario analysis could overvalue the likelihood of thosescenarios and, as a result, undervalue the likelihood of more relevantoutcomes.
Thisillustrates the most enduring critique of the EMH, individuals do not alwaysbehave rationally. In particular, the traditional approach to modellingbehaviour in economics and finance is to asset that investors optimize additivetime separable expected utility function from certain parametric families e.g.constant relative risk aversion. This was the starting point for manyquantitative models of modern finance including mean-variance portfolio theoryand the Sharpe-Lintner Capital Asset Pricing model. However, a number ofstudies have shown that human decision making does not seem to conform torationality and market efficiency but displays certain behavioural biases suchas overconfidence, overreaction, 1986) and loss aversion (Tversky and Kahneman,1981). Forthese reasons, behavioural economists conclude that investors are often, if notalways irrational, exhibiting predictable and financially ruinous behaviourthat would unlikely yield efficient markets.
Grossman and Stiglitz (1980)further argue that perfectly informationally efficient markets are impossible;if markets are perfectly efficient, there will be no profits to gatheringinformation, in which case there would be little or no reason to trade andmarkets would eventually collapse. Instead, the degree of market efficiencydetermines the effort investors are willing to disburse to gather and trade oninformation, hence a non-depraved market equilibrium will arise only when thereare sufficient profit opportunities. The profit earned by these observantinvestors can be viewed as ‘economic rents’ that accumulate to those willing toengage in these activities. Black (1986) suggests that these “noise traders”are the providers of these economics rents, they trade on what they consider tobe information but it’s just noise.Theproponents of the EMH responded to these challenges by arguing that,behavioural biases and corresponding inefficiencies definitely exist from timeto time, but there is a limit to their occurrence and impact because ofopposing forces committed to exploiting these opportunities (Lo, 2007).
Thisconclusion relies on the assumption that these market forces are adequately potentto withhold any type of behavioural bias or equivalently that irrationalbeliefs are not pervasive enough to overpower the capacity of arbitrage capitalcommitted to taking advantage of such irrationalities. ?.?. Implications of the EMHAfterdecades of theoretical and empirical evidence for and against the EMH,economists still have not yet reached a consensus about whether markets, mainlyfinancial markets are definitely efficient. The result of all the literaturesstudied solidifies the resolve of the proponents of each side of the debate.One of the explanations for this state of affairs is that the EMH, is solelynot a well-defined and empirically refutable hypothesis, one must specifyadditional structure, for example investors’ preferences. More importantly,what is more significant is the efficiency of a particular market relative toanother i.
e. futures vs. spot markets. From a practical point of view and inthe light of Grossman and Stiglitz (1980), the EMH is an idealization that iseconomically unimaginable, but works as a useful standard for measuringrelative efficiency.