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?. Introduction

Much
of modern investment theory and practice is based on the Efficient Market Hypothesis
(EMH), the belief that it is impossible to “beat the market”, as markets fully,
accurately and instantaneously incorporate all available information into
market prices; developed by Samuelson (1965) and Fama (1965a), this investment
theory explains that stocks always trade at their impartial value on the stock
exchange, making it difficult to outperform the whole 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,
2002).

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This
led to the evolution of the Adaptive Market Hypothesis (AMH) (Lo, 2004); 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.

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 (1982/1979) 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 (1988, p.98), 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
(1982) 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 ( Fischoff and Slovic, 19800, overreaction (DeBondt and
Thaler, 1986) and loss aversion (Tversky and Kahneman, 1979).

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 (1976) & 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 (1980) 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. The reference by
Kindeberger (1989), where a number of speculative bubbles, financial panics,
maniacs and market crashes were described in detail suggests that the forces of
irrationality can overpower the forces of arbitrage capital for long periods of
time.

?.?. Implications of the EMH

After
decades of theoretical and empirical evidence for and against the EMH,
economists still have not yet reached a consensus about whether markets, mainly
financial markets are definitely efficient. The foremost result of all the literatures
studied 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 solely
not a well-defined and empirically refutable hypothesis, one must specify
additional structure or model for example investors’ preferences or information
structure. More importantly, what is of more significance is the efficiency of
a particular market relative to other markets i.e. futures vs. spot markets,
auction vs. dealer markets. From a practical point of view and in the light of
Grossman and Stiglitz (1980), the EMH is an idealization that is economically unimaginable,
but works as a useful benchmark for measuring relative efficiency.

?. A Neuroscientist view

The
battle between the proponents of the EMH and champions of behavioural fiancé
has been studied for years, to get additional insights we refer to the
literature of the cognitive neurosciences. This research led to a significant reformulation
of psychological models of decision making; which involved research tools such
as positron emission tomography (PET) and functional magnetic resonance imaging
(MRI) (Lo, 2005), where an array of images of the subject’s brain was captured
in real time as questions were being asked. The results were determined and
interpreted by the detecting the amount of blood flow in certain areas of the
brain, before, during and after the task The activation in certain parts of the
brain were linked to the performance of the task.

One
major discovery was that there is an apparent link between rational behaviour
and emotion; this shed light on financial decision-making. How? Damasio (1994)
discovered that the ability of patents who had underdone surgical removal of
brain tumours, to make rational choices suffered. A patient, code-named Elliot,
experienced a profound effect on his day-to-day activities after his emotional
faculties were removed from his brain. Damasio (1994) noticed that his flow of
work at a point in time stopped, Elliot will focus something else that was
captivating. It was as though Elliot had become irrational concerning the
larger frame of behaviour in his daily decision.

The
source of irrationality? Is it emotion? Behaviour can be viewed as the
observable manifestation of interactions among several components of the brain,
sometimes competitively and others cooperatively. Nevertheless, under other
circumstances, emotional responses can overrule more complex deliberations,
neuroscientists have shown that emotion is the first response in the sense that
individuals exhibit emotional reactions to objects and events far quicker than
they can articulate what those objects and events are (Zajonc, 1980).

As
environmental conditions change, so does the relative importance of each
component of the brain, individuals are able to adapt to new situations by
learning and implementing more advantageous behaviour and this is often
accomplished by several components of the brain acting together. As a result what
economists call ‘preferences’ are often complicated interactions among
subcomponents within each of the three parts of the brain; this perspective
implies that preferences may not be stable through time, but are likely to be
shaped by a number of factors, both internal and external to the individual,
i.e., factors related to the individual’s personality, and factors related to
specific environmental conditions in which the individual is currently
situated. This neuroscientific perspective suggests an alternative to the EMH,
one in which market forces and preferences interrelate to yield a much more
dynamic economy, one driven by competition, natural selection, and the
diversity of individual and institutional behaviour. This is the essence of the
Adaptive Markets Hypothesis.

?. The Adaptive Market Hypothesis

A
promising path is to view financial markets from a biological aspect and
specifically within an evolutionary framework in which market instruments,
institutions and investors interact and evolve dynamically according to the law
of economic selection. Under this perspective financial agents compete and
adapt, but do not necessarily do so in an optimal fashion (Farmer and Lo,
1999).

This
evolutionary approach was grossly influenced by recent advances in the emerging
discipline of evolutionary psychology, which built on research of Wilson (1975)
in applying the principles of competition, reproduction and natural selection
to social interaction, yielding convincing justification for certain kinds of
human behaviours, such as altruism, kin-selection and religion (Gigerenzer,
2000). It is due to ‘Socio-biology’ (Wilson, 19750, we can entirely reconcile
the EMH with all of its behavioural alternatives, leading to a new creation;
the Adaptive Market Hypothesis (AMH). These ideas have been exported to a
number of economic and financial studies and at least two conspicuous
practitioners have proposed Darwinian alternatives to the EMH: in a chapter
titled ‘The zoology of markets’, Niedernoffer (1997) compares financial markets
to an ecosystem with dealers as ‘herbivores, speculators as ‘carnivores’ and
floor traders and distressed investors as ‘decomposers’. Bernstein (1980) points
out that the notion of equilibrium which is central to the EMH is namely
realised in practice and that market dynamics are better explained by
evolutionary processes.

This
evolutionary perspective makes more modest claims, viewing individuals as
organisms that have been enhanced through a generation of natural selection
(Dawkins, 1970), which ensures the survival of their genetics. This perspective
implies that behaviour is not really intrinsic and exogenous, but evolves by
natural selection and depends on the particular environmental through which
selection occurs. That is, natural selection operates not only upon genetic
material but also upon social and cultural norms in Homo sapiens; hence
Wilson’s term ‘socio-biology’. To make this practical in an economics context,
Lo (2004) re-examines the idea of ‘bounded rationality’, first spoken by Simon
(1975), who suggested that individuals are hardly capable of the kind of
optimization that neoclassical economics calls for in the standard theory of
consumer choice. As an alternative, he argued that, because optimization is pricey
and humans are naturally limited in their computational capabilities, they
engage in something he called ‘satisficing’, an alternative to optimization in
which individuals make choices that are merely satisfactory, not necessarily
optimal. In other words, individuals are bounded in their degree of
rationality.

However
what determines the point at which an individual stops optimizing and reaches a
satisfactory solution? (Lo, 2004) argues that an evolutionary perspective
provides the missing ingredient in Simon’s framework; to properly answer the
question, such points are not determined analytically but through trial and
error and also natural selection. As mentioned earlier in this essay, people
make their choices based on past experiences and their ‘best guess’ as to what
might be optimal and they learn by receiving positive or negative reinforcement
from the outcomes; if these reinforcements aren’t in place, they do not learn.
To resolve this, individuals develop heuristics to solve various economic
challenges, if these challenges remain stable, the heuristics will eventually
adapt to yield just about. If however, the environment changes, then it means
that the heuristics of the old environment are not suited to the new
environment.

Compared
to the EMH, the AMH provides profound information that helps understand how
individuals behave in the face of financial decisions, it can be viewed as a
new version of the EMH, and the primary components of the AMH (Lo, 2005) shows
this reasoning and  are as follows:

§  A1: Individuals act in their own
self-interest: what constitutes self-interest is not
defined by the AMH nor does self-interest correspond to rationality. The EMH
and the AMH have a common starting point at A1 but the two paradigms part
company with A2 and A3.

§  A2: Individuals make mistakes: In
efficient markets, investors do not make mistakes, and there is not any
learning and adaptation because the market environment is stationary and always
in equilibrium.

§  A3: Individuals learn and adapt: In
the AMH framework, mistakes occur often, but individuals are capable of
learning from mistakes and adapting their behaviour accordingly.

§  A4: Competition drives application
and innovation: This suggests that adaptation does not
occur freely of market forces, but is driven by competition, i.e., the push for
survival; the survival of the richest, in this context.

§  A5: Natural selection shapes market
ecology: This implies that the existing market environment is
a product of this selection process.

§  A6: Evolution determines market
dynamics: This states that the sum total of these components; selfish
individuals, competition, adaptation, natural selection, and environmental
conditions.

?. Conclusion

The
AMH is still in its early stages, and definitely requires more research before
it becomes a practical alternative to the EMH. However, it is already clear
that an evolutionary framework such as this can reconcile many of the apparent
contradictions between efficient markets and behavioural exceptions. The former
may be viewed as the steady-state boundary of a population with constant
environmental conditions, and the latter involves specific adaptations of
certain groups that may or may not persist, depending on the particular
evolutionary paths that the economy experiences. Apart from this intellectual
reconciliation. Yet, how relevant is the AMH for the practice of investment
management? Despite the limitation of the EMH, it has assumed a means of
quantitative tools for the specialist. Part of which comes from the EMH’s much
studied literatures —behavioural models have recently begun to gain some degree
of propriety in the academic mainstream.

 It is very easy to forget that the EMH is only
but a fabrication of our imagination, meant to serve as approximations and not
really accurate ones to a far more complex reality. Unlike the law of gravity,
there is no absolute law of Nature from which the EMH can be derived. Also,
once we progress from the vastly structured framework of the EMH, there are boundless
prospects for modelling economic behaviour, one has to make sure the
mathematical embodiments of behavioural research is derived to show clarity in
the model. In particular, quantitative implications of the AMH may be derived
through a combination of deductive and inductive inference, for example,
theoretical analysis of evolutionary dynamics, empirical analysis of
evolutionary forces in financial markets, and experimental analysis of decision
making at the individual and group. But even at this formative stage, the AMH
yields several concrete applications for investment management and consulting;
hence my choice is the AMH.

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