Much the Adaptive Market Hypothesis (AMH) (Lo, 2005); it

Much
of modern investment theory and practice is based on the Efficient Market Hypothesis
(EMH), the belief that it is impossible to manipulate the market, as markets
fully, accurately and instantaneously incorporate all available information
into market prices; established by Samuelson and Fama (1965), this investment
theory explains that stocks always trade at their impartial value on the stock
exchange, making it difficult to outperform the entire market through skilled
stock selection or market timing. The only way an investor can have higher
returns is by acquiring riskier investments. Underlying this idea is the
assumption that market participants are rational economic individuals, always
acting in their own self-interest and making decision in an optimal fashion by
trading off costs and benefits weighted by the statistically correct
probabilities and marginal utilities. These assumptions of rationality and its
corresponding implications for market efficiency were criticised by various
studies, especially psychologists and experimental economists (Lo, 2005); with
the opponents stating that the EMH revolves around the preferences and
behaviour of market participants. To a large extent, this criticism is a
reflection of the differences between economics and psychology (Rabin, 1998).

This
led to the evolution of the Adaptive Market Hypothesis (AMH) (Lo, 2005); it
became obvious that an alternative to the traditional logical approach of
neoclassical economics may be necessary to reconcile the EMH with its
behavioural critics. The AMH combines the principles of behavioural finance
with the principles of the EMH; it suggests that the degree of market
efficiency is related to environmental factors, characterising market ecology
such as the number of competitors in the market, the level of profit
opportunities presented and adaptability of the market members. It suggests
that investors’ behaviour such as loss aversion, overconfidence, overreaction
and other behavioural biases (Lo, 2005) are constant with evolutionary models
of human behaviour such as natural selection. Within this criterion,
behavioural biases are simply heuristics that have been taken out of context,
not certainly counter examples to rationality. Given enough time and competitive
drive, any counterproductive heuristic can be reformed to suit the current
environment. The dynamics of natural selection and evolution produce a combining
set of principles from which all behavioural biases can be derived.

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In
this essay, I analyse the strengths and weaknesses of the EMH, whilst also
reviewing a modern framework; the AMH. Making sure to state the main
characteristics and evaluating the implications of both investment theories in
Section ?, to better understand and contrast which is more relatable an
accurate to  modern investment and
finance. I present some recent results from the cognitive neuroscience literature
that shed new light on both rationality and behaviour in Section ?. In Section
?, I review the AMH and its primary components.  And then conclude in Section ? stating which
theory better appeals to me and the reasons behind my decision.

?. Main characteristics on the EMH

To
illustrate the conflict between the EMH and behavioural finance, consider the
following example which involves an aspect of probability assessment in which
individuals assign probabilities to events not according to the basic axioms of
probability theory, but according to how representative those events were of
the general class of phenomenon under consideration. Two psychologists, Tversky
and Kahneman (1981) posed the following question to a sample of 86 subjects
(Lo, 2005):

“Linda
is 31 years old, single, outspoken and very bright. She majored in Philosophy.
As a student she was deeply concerned with the issues of discrimination and
social justice, and also participated in anti-nuclear demonstrations. Please
click off the most likely alternative”

                       

                       

Despite
the fact that the ‘bank teller’ is in no way less probable than ‘bank teller
and feminist’, 90% of the subjects being tested, chose the second alternative because
the latter classifies a more restrictive subset of the former. Tversky and
Kahneman (1981), established that as the amount of detail in a scenario rises,
its probability can only fall steadily, but its representatives and hence its
apparent likelihood may increase. This behavioural bias is particularly
relevant for the risk-management practice of “scenario analysis” in which the
performance of portfolios is simulated for specific market scenarios such as
the stock market crash of October 19, 1987. While adding detail in
the form of a specific scenario to a risk-management simulation makes it more
palpable and intuitive in Tversky and Kahneman’s (1981) context, more
“representativeness” decreases the likelihood of occurrence. Therefore,
decisions based largely on scenario analysis could overvalue the likelihood of
those scenarios and, as a result, undervalue the likelihood of more relevant
outcomes.

This
illustrates the most enduring critique of the EMH, individuals do not always
behave rationally. In particular, the traditional approach to modelling
behaviour in economics and finance is to asset that investors optimize additive
time separable expected utility function from certain parametric families e.g.
constant relative risk aversion. This was the starting point for many
quantitative models of modern finance including mean-variance portfolio theory
and the Sharpe-Lintner Capital Asset Pricing model. However, a number of
studies have shown that human decision making does not seem to conform to
rationality and market efficiency but displays certain behavioural biases such
as overconfidence, overreaction, 1986) and loss aversion (Tversky and Kahneman,
1981).

For
these reasons, behavioural economists conclude that investors are often, if not
always irrational, exhibiting predictable and financially ruinous behaviour
that 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 gathering
information, in which case there would be little or no reason to trade and
markets would eventually collapse. Instead, the degree of market efficiency
determines the effort investors are willing to disburse to gather and trade on
information, hence a non-depraved market equilibrium will arise only when there
are sufficient profit opportunities. The profit earned by these observant
investors can be viewed as ‘economic rents’ that accumulate to those willing to
engage in these activities. Black (1986) suggests that these “noise traders”
are the providers of these economics rents, they trade on what they consider to
be information but it’s just noise.

The
proponents of the EMH responded to these challenges by arguing that, behavioural
biases and corresponding inefficiencies definitely exist from time to time, but
there is a limit to their occurrence and impact because of opposing forces committed
to exploiting these opportunities (Lo, 2007). This conclusion relies on the
assumption that these market forces are adequately potent to withhold any type
of behavioural bias or equivalently that irrational beliefs are not pervasive enough
to overpower the capacity of arbitrage capital committed to taking advantage of
such irrationalities.