?. other behavioural biases (Lo, 2005) are consistent

?. Introduction Much
of modern investment theory and practice is predicated on the Efficient Market
Hypothesis (EMH), the notion 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 fair value on the stock
exchange, making it impossible to outperform the overall market through expert
stock selection or market timing. The only way an investor can possibly have higher
returns is by purchasing riskier investments. Underlying this far reaching idea
is the assumption that market participants are rational economic beings, 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 came under attack 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. This criticism is to a large extent a
reflection of the differences between economics and psychology (Rabin, 1998, 2002).This
led to the evolution of the Adaptive Market Hypothesis (AMH) (Lo, 2004); it
became apparent that an alternative to the traditional deductive 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 magnitude of profit opportunities available and
adaptability of the market participants. It proposes that investors’ behaviour
such as loss aversion, overconfidence, overreaction and other behavioural
biases (Lo, 2005) are consistent with evolutionary models of human behaviour
such as natural selection. Within this paradigm, behavioural biases are simply
heuristics that have been taken out of context, not necessarily counter examples
to rationality. Given enough time and competitive drive, any counterproductive
heuristic will be reshaped to suit the current environment. The dynamics of
natural selection and evolution yield a unifying set of principles from which all
behavioural biases may 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 EMHTo
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 tested, chose the second alternative because
the later categorises a more restrictive subset of the former. Tversky and
Kahneman (1988, p.98), concluded by saying that as the amount of detail in a
scenario increases, its probability can only decrease 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 may
overestimate the likelihood of those scenarios and, as a result, underestimate
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 exhibits 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. Alternatively, the degree of
market efficiency determines the effort investors are willing to expend to
gather and trade on information, hence a non-degenerate market equilibrium will
arise only when there are sufficient profit opportunities. The profit earned by
these attentive investors may be viewed as ‘economic rents’ that accrue to
those willing to engage in such activities. Black (1980) states that “noise traders”
are the providers of these economics rents, they trade on what they believe to
be information but in fact it’s just noise.The
supporters of the EMH have responded to these challenges by arguing that, while
behavioural biases and corresponding inefficiencies definitely exist from time
to time, there is a limit to their prevalence and impact because of opposing
forces dedicated to exploiting such opportunities (Lo, 2007. This conclusion
relies on the assumption that these market forces re sufficiently powerful to
overcome any type of behavioural bias or equivalently that irrational beliefs
are not so pervasive as to overwhelm the capacity of arbitrage capital
dedicated to taking advantage of such irrationalities. The classic reference by
Kindeberger (1989), where a number of speculative bubbles, financial panics,
maniacs and market crashes are described I detail suggests that the forces of
irrationality can overwhelm the forces of arbitrage capital for long periods of
time.?.?. Implications of the EMHAfter
several decades of theoretical and empirical evidence for and against the EMH economist
have not yet reached a consensus about whether markets, particularly financial
markets are in fact efficient. The main result of all the studies and literatures
studied was to solidify the resolve of the proponents of each side of the
debate. One of the reasons for this state of affairs is in fact 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 consequence 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
unrealizable, but serves 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 sequences 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 detection of the amount of blood flow in certain regions 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 other cooperatively. However 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 interact 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 HypothesisA
particular promising direction 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 the survival of research
of Wilson (1975) in applying the principles of competition, reproduction and
natural selection to social interaction, yielding compelling explanation 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 fully reconcile
the EMH with all of its behavioural alternatives, leading to a new synthesis;
the Adaptive Market Hypothesis (AMH). These ideas have been exported to a
number of economic and financial contexts and at least two prominent
practitioners have proposed Darwinian alternatives to the EMH: in a chapter
titled ‘The zoology of markets’, Niedernoffer (1997) likens financial markets
to an ecosystem with dealers as ‘herbivores, speculators as ‘carnivores’ and
floor traders and distressed investors as ‘decomposers’. Bernstein (19980) points
out that the notion of equilibrium which is central to the EMH is namely
realised inn 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 honed through a generation of natural selection
(Dawkins, 1970), which ensures survival of their genetic material. This perspective
implies that behaviour is not necessarily 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 viable in an economics context, Lo (2004)
revisits 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.
Instead, he argued that, because optimization is costly and humans are
naturally limited in their computational abilities, 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 determined not analytically but through trial and error and
also natural selection. As mentioned earlier in this essay, individuals 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 approximately. If however, the environment changes, then it
means that the heuristics of the old environment are no necessarily 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, nor is there 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 frequently, but individuals are capable of
learning from mistakes and adapting their behaviour accordingly.§  A4: Competition drives application
and innovation: This states that adaptation does not occur
independently 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 current 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.?. ConclusionThe
AMH is still in its early stages, and definitely needs more research before it
becomes a practical alternative to the EMH. However, it is already clear that
an evolutionary framework 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 given rise to 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

 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 proceed from the highly structured framework of the EMH, there are
endless 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.

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