Download I. Reconciling Psychology and Economics

TOWARDS A UNIFIED THEORY OF PSYCHOLOGY AND FINANCIAL MARKETS
by Flavia Cymbalista, Ph.D.
Based on the notion of efficient markets and a narrow definition of economic rationality,
standard financial theory is unable to explain the boom and bust patterns that characterize
real world markets as well as to serve as a basis for the development of tools to improve
decision making. Behavioral Finance has identified a number of psychological decision
attributes which do not conform with the traditional model of rational economic man and
argued that such deviations could account for the non-linear properties of observed
prices. However, the study of psychology and financial markets still lacks a unified
framework that could replace the standard view. This requires an economic theory able to
encompass psychology as well as a view of cognition compatible with it. The function of
such a framework is two-fold. First, to ensure that the empirical content gained from
examining financial decision making at the individual level is not achieved at the expense
of logical coherence and consistency. Second, to point out what the relevant
psychological questions are and thus guide the search for approaches to improve decision
making. This paper argues that a unified framework for the study of psychology and
financial markets demands a more radical departure from standard theory than Behavioral
Finance has yet shown.
Section I demonstrates that in order to fulfill the tenets of logical consistence and
coherence economic interaction has to be conceptualized in a way that is antithetical to
how standard theory explains: as an organic complex. It presents an approach grounded
on Keynesian liquidity-preference theory in which price dynamics are explained in terms
of the reflexive relationship between observed conditions and the participants perceptions
of them, allowing a reconciliation of finance and psychology within a complexity
perspective. Section II shows that the complexity perspective entails an epistemological
shift with respect not only to the way we view markets but also to the cognitive processes
that guide economic action. It requires we acknowledge both markets and their
participants not as optimal information processors – as standard theory postulates – nor as
sub-optimal information processors – as Behavioral Finance argues – but as rather more
than information processors. While the uncertainty-free setting of standard theory implies
the unconditional superiority of analysis over intuition, this is no longer the case in a
complex environment. Recent developments in cognitive research that question the
computationalist notion of rationality offer a foundation for the study of experiential
aspects of decision making. The new view of cognition as participatory – as embodied,
enacted and relational – encompasses the positive side of intuitive reasoning which has
been emphasized by practitioners all along, providing a basis from which tools to
improve the reliability of subjective judgement can be derived. .
I. Reconciling Psychology and Economics
1. Efficiency, Rationality and the Mode of Interaction
Efficient markets theory stems from an attempt to combine statistical observations of the
apparently random character of stock price changes with the Neoclassical theory of value.
Like classical economics, efficient markets theory explains prices by drawing in an
underlying substance, a fundamental value or natural price that is determined by
exogenous factors. This serves as an anchor around which market prices fluctuate.
Changes in the exogenous factors are viewed as equal to a change in fundamental value,
whereas observed price changes represent an adjustment of market prices to the change in
fundamental value. Market valuation is seen on the one hand as a passive mechanism for
the realization of pre-determined results. On the other hand, the relationship between
market prices and fundamental value is explained as in Walrasian equilibrium theory, as a
logical consequence of the optimization calculus of independent market participants. The
reactions of rational market participants to the arrival of new information leads to stock
prices reflecting the relative scarcity that results from the interplay of consumption needs,
the physical productivity of capital goods and the availability of physical resources. As in
the timeless Walrasian equilibrium price system, stock prices summarize all information
that market participants need in order to make optimal decisions. In contrast to a
Marshallian approach, which reconciles the classical theory of value with the marginal
price theory through the distinction between the short- and the long-run, efficient markets
theory assumes an immediate adjustment of prices to value. While for Marshall the longrun associated with the natural price represents a strictly abstract construct, for advocates
of the efficient markets theory a stochastic version of the timeless general equilibrium
model is seen as a good approximation of the process that generates actual, observed
prices1.
Efficient markets theory transports the timeless Walrasian construct to an
intertemporal frame by means of the rational expectations hypothesis. The rational
expectations hypothesis states that economic agents are optimal information processors
and equates their expectation formation to a statistical procedure associated with a correct
representation of an objectively given probability distribution. While in the deterministic
model results are pre-coordinated by the auctioneer, the rational expectations hypothesis
assumes away the question of the coordination of economic behavior by presenting a
stochastic form of perfect foresight: expected equilibrium prices are common
knowledge2.
Since the Walrasian equilibrium model assumes certainty, its extension to an
intertemporal frame implicitly assumes that the qualitative differences introduced by the
element of time can be ignored. Accordingly, fundamental valuation only takes into
account that category of incertitude that Knight (1921) labels as risk and distinguishes
from uncertainty which cannot be reduced to the certainty case. In case of risk, the
incertitude of the future can be comprehended by distributive probabilities: the different
possible future states can be fully listed and associated with unequivocal numerical
values, which add up to one. The totality of states is thus viewed as certain, that is,
certainty is merely distributed over the individual states. The exclusion of uncertainty
concerns on the one hand the modeling of rational choice: in expected utility theory,
which underlies standard finance, decision makers choose among “lotteries”, i.e. among
probability distributions. On the other hand, it offers the pre-requisite for the applicability
of the rational expectations hypothesis – in stochastic terms it corresponds to the
1
Thus the designation of the macroeconomic theory of rational expectations as new classical
macroeconomics.
2
See Arrow [1987], S. 210;
assumption that the processes generating prices is stationary. Lucas [1977, S. 15] states
very clearly how essential the exclusion of uncertainty is:
“[Rational Expectations] will most likely be useful in situations in which the probabilities
of interest concern a fairly well defined and recurrent event, situations of “risk” in
Knight’s terminology. In situations of risk, the hypothesis of rational behavior on the part
of agents will have usable content, so that behavior may be explainable in terms of
economic theory. In such situations, expectations are rational in Muth’s sense. In case of
uncertainty, economic reasoning will be of no value.”
The most fundamental assumption in the way standard theory explains is the view of the
economy as an atomic interacting system. In an atomic system, wholes can be reduced to
the sum of their parts. The essential characteristics of the system’s components are
independent from their relationships to other components, such that interaction does not
lead to the emergence of new properties. The atomic hypothesis permeates standard
theory at many levels. It is embedded in the assumption of pre-coordinated results of
equilibrium theory, in the notion of value as an objective category independent from the
perceptions of economic agents, in the definition of economic rationality as the
representation of this underlying reality. Further, it legitimizes the universal reducibility
of uncertainty to probabilities amenable to mathematical treatment that underlies the
standard notion of rationality as well as most of the statistical methods applied in the
empirical financial markets research. Such a reduction is only justified if the system
observed shows the limited independent variety typical of games of chance. While this is
true for atomic systems, it does not hold in case of organic interaction, where the
collective behavior of the whole is qualitatively different from that of the sum of the
individual parts.
In its questioning of market efficiency, Behavioral Finance focuses on the fact that the
standard notion of rationality does not offer a realistic description of investor behavior.
Drawing on cognitive-psychological research showing that biases in decision processes
lead to systematic violations of expected utility theory and/or the rational expectations
hypothesis, Behavioral Finance proposes to increase the empirical content of modern
finance by modifying its behavioral hypotheses3. However, Behavioral Finance does not
postulate an alternative notion of rational decision making: its “quasi-rational” economic
man is a sub-optimal information processor, a fallible version of the standard paradigm.
This means that the decision attributes on which its explanations are based cannot but be
viewed as violations of the rationality principle. There are basically two reasons why this
is unacceptable:
First, departures from the rationality principle are associated with a loss of
generality and rigor. Rationality defines the economic calculus. It is a general explanatory
principle, abstract enough to be applied to the myriad of observed phenomena, which
gives economic analysis its coherence. Without such a unifying principle, finance is left
with disparate decision attributes and explanations based on seemingly contradictory
phenomena such as loss aversion and overconfidence cannot avoid the label of
arbitrariness.
Second, departures from the rationality assumption are associated with a loss of
logical consistency. In economics, individual decision making is not interesting per se but
3
For an overview, see Olsen [1998].
always in connection with a market theory. The rationality assumption is inextricably
bound with the mechanism relating parts and wholes, with the rules that allow market
results to be derived from individual choice. Irrational behavior breaks the links between
the individual and the market level, between different markets, as well as between the
real and the financial sphere.
Behavioral Finance has searched for explanatory power in psychology, especially
behavioral decision making. Psychology has a great deal to contribute to the empirical
content of finance, yet it can’t substitute for it. An economic theory can achieve a higher
degree of realism only by decreasing the level of abstraction of its behavioral hypothesis
– and herein lies the role of psychology in a unified framework – but not by including
assumptions contradictory to its underlying notion of rationality and thus to the norms of
economic theory building4. Behavioral Finance cannot play psychological reality against
economic theory: it has to grasp psychological and economic forces as complementary,
not as contradictory to each other. Rather than taking into account ad hoc violations of
the standard decision calculus, giving finance a firm behavioral foundation demands
postulating an alternative notion of rationality.
Overcoming the dichotomy between rational and psychologically influenced valuation
requires not only an individual level decision theory but also consideration of the
complex dynamics of agents interaction. This means that a more realistic modeling of
individual behavior cannot be achieved without a simultaneous examination of the
relationship between parts and wholes.
While most of its theorists view Behavioral Finance as an extension of the
standard paradigm, acknowledging the role of cognitive factors leads to a breakdown of
its most fundamental assumption: the view of the economy as an atomic interacting
system. If market participants act the way Behavioral Finance argues they do, the rules
that govern the behavior of the system will be affected by their expectations, so that the
system will no longer show the limited independent variety typical of games of chance.
The anticipation of average opinion – an endogenous variable that cannot be reduced to
the exogenous factors which in standard theory constitute fundamental value – then
becomes a determinant of the system. With the breakdown of the atomic hypothesis,
uncertainty is no longer reducible to the risk case. This renders the standard view of
rationality and its accompanying notion of value not only descriptively false but also
theoretically, ie. normatively irrelevant. Behavioral Finance is then left without the
references from which it argues that investor and market behavior deviate. Behavioral
Finance does try to prove its point by making a distinction between the short- and the
long-run: irrationality characterizes the former, whereas in the latter prices return to their
fundamentals. However, it cannot derive such results from individual choice. Nor from
mean reversion or any other properties of observed time series: the Marshallian long-run
is a purely abstract construct that assumes ceteris paribus conditions, it cannot be
confused with either an average or a state that will come to realize itself if one just waits
long enough5. Encompassing psychology thus requires we conceptualize economic
4
See Lindenberg [1990];
Cymbalista [1998] offers an exposition of the logical inconsistencies and methodological flaws commited
by Behavioral Finance. Frankfurter/McGoun [1995] demonstrate the invalidity of its event studies.
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interaction in a way that is antithetical to how standard theory explains: as an organic
complex.
As mentioned above, in order to extend the timeless Walrasian construct into an
intertemporal frame, standard theory assumes away the question of the coordination of
economic behavior by presupposing an underlying stable stochastic process where the
parameters are common knowledge. In contrast, the complexity perspective is a paradigm
for studying systems with a history, where the end-state is not coded anywhere. It
describes processes where a myriad of highly heterogeneous and complex, mutually
constraining microbehavior gives rise to coherent macrobehavior. Unlike the linear
models based on the standard treatment of financial market valuation, complexity theory
is able to account for observed price behavior, for the phases of stability punctuated by
boom and bust patterns that characterize real world markets6. Yet complexity theory does
not render economic theory superfluous: the structure in which agents interact still have
to be explained in terms of economic categories. While the particular economic paradigm
that standard finance embraced cannot be reconciled with either psychology or
complexity, the same cannot be said for economic theory as such – i.e. with an
explanatory structure based on a notion of scarcity and able to explain market results as
the consequence of rational individual decisions. The next section presents an approach
based on Keynesian liquidity-preference theory in which economic interaction is
conceptualized as organic, rather than atomic. This offers an economic theoretical
foundation for the application of a complexity perspective to financial markets, which
will be further discussed in the second part of this paper. In the last section we will return
to the question of the empirical relevance of Behavioral Finance being compromised by
its attachment to standard theory: acknowledging uncertainty as the main feature of the
decision situation in which practitioners find themselves is a condition for fully
comprehending the role of intuitive judgement in investment decisions.
2. Rational Valuation under Fundamental Uncertainty
The belief in the irrelevance of Walrasian analysis for explaining economic processes in
time was the main force that drove Keynes to reformulate economic theory.
Correspondingly, uncertainty plays a central role in his thought, both in his early
philosophical work on probability theory and in his economic theory.
The relationship between the mode of interaction and the conceptualization of
uncertainty is one of the main themes of Keynes’ [1921] “Treatise on Probability”.
Keynes differentiates between two dimensions of a probabilistic argument: the
probability judgement proper and the degree of confidence one attaches to it (“weight of
argument”). Unlike the common definition coined by Knight [1917], in which the
dichotomy risk/uncertainty is directly related to the question of numerical measurability,
Keynes’ treatment of uncertainty is connected with the question of confidence, with the
“weight”. Examining the conditions under which the degree of belief in a hypothesis is
amenable to a mathematical calculus of probability, Keynes anticipates the limits of
expected utility theory, showing that numerical measurability presupposes an equal
6
See Arthur [1995];
degree of confidence. While this is true for atomic systems, which show the limited
independent variety typical of games of chance, it does not hold in case of organic
interaction, where the collective behavior of the whole is qualitatively different from that
of the sum of individual parts.
In his critique of Neoclassical theory, Keynes [1937] points out that the atomic
hypothesis breaks down once the qualitative differences introduced by the element of
time are considered, requiring an alternative solution to the coordination problem:
acknowledging the role of money between present and future. As soon as money – a
social convention or institution – is assigned an independent function, the atomic
hypothesis no longer applies; instead, organic complexes become an adequate metaphor
for economic reality and uncertainty is no longer reducible to the risk case. In short,
uncertainty does not make economic theory useless but mandates a monetary approach.
Based on Keynes’ “Treatise on Probability”, his thoughts on expectations as
expounded in the “General Theory” and recent developments of Keynesian value theory
known as Monetary-Keynesianism, Cymbalista [1998] formulates an approach to stock
market valuation alternative to efficient markets theory. The Keynesian approach –
described below - was shown to provide a theoretically consistent explanation of the
empirical findings which are anomalous within the market efficiency paradigm. Most
important, it offers an economic explanation for the non-linear properties of observed
prices that is able to encompass psychological processes without loss of rigor.
Keynes introduces uncertainty into economic theory by reversing the hierarchy of
markets. Neoclassical theory subordinates the credit market to the market for capital: the
credit supply function is associated with the savings function of the households,
dependent on consumption preferences, and the credit demand function is identified with
the investment function, itself dependent on the physical productivity of capital goods.
The rate of interest is determined at the capital market equilibrium where savings and
investment are equalized. Money remains only a reference quantity, a neutral link, a veil
over transactions that take place in the real sphere; its sole function – which can be
fulfilled by any divisible good - is that of a numéraire7. This means that the specific
institutional form in which a monetary economy is organized is not supposed to affect the
way the system works. The quantity of money, which is seen as exogenous, influences
only nominal prices but not value formation. In contrast, Keynes interprets the interest
rate as the price for the temporary transfer of money, determined by the supply and
demand for liquidity. Productive capital is viewed as a form of surrendering liquidity and
investment as determined not by the physical productivity of capital goods but by the
interest rate and the expected money returns. As a monetary phenomenon, it summarizes
Thereto Walras [1874, p. 289f]: “...[L]et us now suppose that savers lend...in numéraire to the
manufacturers who go in place of the savers to the market for capital goods...Nothing will be
changed...[T]he rate of interest, which is the ratio of net profit to the price of securities, manifests itself...in
the market for numéraire-capital...though actually it is determined in the capital goods market that is to say
the stock exchange....It is clearly seen now that the key to the whole theory of capital is to be found in
...eliminating capital loans in the form of numéraire so that attention is directed exclusively to the lending
of capital in kind. The market for numéraire-capital, however useful in practice, [is] nothing but a
superfoetation in theory...” The neutrality of money is of course still paradigmatic for modern capital
markets theory, where the basic model assumes an initial endowment of a homogeneous good which
functions simultaneously as wealth, consumption good and means of production.
7
the confidence of economic agents in their hypothesis about the behavior of the totality of
agents.
Monetary-Keynesian decision theory is, like Keynes’ concept of expectations,
two-dimensional. Wealth holders attempt to both increase and secure wealth8. The
prototype of a wealth holder is not a consumer but a bank, at the same time debtor and
lender. In Neoclassical theory, pre-coordinated outcomes exclude insolvency, since the
transfer of wealth between consumers and producers is guaranteed to flow continuously.
Increasing wealth is subordinated to the aim of maximizing consumption so that holding
money is never preferred to the alternative of holding an asset which yields a return. In
contrast, in a monetary economy outcomes are uncertain, because the disposition of the
totality of wealth holders – unknown for the individual at the time of decision –
determines whether producers will be able to repay the advanced liquidity. Thus, in and
of itself, money has no utility in neoclassical economics, but in Keynesianism money
provides security. In order to describe the non-pecuniary reward of money, the
opportunity cost of surrendering liquidity, Keynes coined the term “liquidity premium”.
Increasing wealth requires surrendering liquidity whereas liquidity fosters security, so
that the decision calculus of wealth holders consists of weighing up the liquidity premium
of holding money and the expected return of surrendering liquidity, i.e. the risk premium.
In addition to money, all assets are assigned liquidity premia which reflect the ease with
which they can be transformed into money. In order for a wealth holder to be willing to
surrender liquidity, the sum of the risk and liquidity premia of the asset must correspond
to the liquidity premium of money. The definition of risk and liquidity premia is
analogous to that of the probability and the ‘weight’ of argument. The risk premium is
associated with a probability judgement proper and the liquidity premium with the
‘weight’. This difference corresponds to the difference between the best estimates we can
make of probabilities and the confidence with which we make them. While the liquidity
premium of an asset doesn’t depend on the level of expected returns, a high liquidity
premium increases the willingness to take on risk, so that risk preference can be seen as a
manifestation of the state of confidence9.
The two-dimensional theory of individual decision making is abstract enough to
serve as a basis for a market theory. At the same time, it incorporates some of the more
general findings of behavioral finance. Like the descriptive models of choice drawn by
behavioral finance, the Keynesian decision calculus relaxes expected utility theory. First,
the introduction of the security goal accounts for loss aversion, which within expected
utility theory represents an irrational preference order. As behavioral finance has pointed
out, loss aversion is responsible for the fact that downward price adjustments are more
severe than their upward counterparts. Second, the assumption underlying expected
utility theory that every decision problem can be represented as a choice among lotteries
rests on the premise that expectations can be expressed as probability distributions. As
mentioned in the previous section, this has to be qualified by the degree of confidence.
Because confidence frames risk perception, the two-dimensional Keynesian calculus
captures the context dependence of risky choice both in terms of the structure of the
decision situation and the affective states that shape decision making. Most important, the
8
9
See Riese [1989];
Heering [1991] offers an analytical treatment.
ability of the individual decision theory to encompass psychological variables is
embedded in a value theory.
Keynes’ recognition of the role of money undermines the assumption of an objective,
exogenous budget constraint that underlies the notion of fundamental value. MonetaryKeynesianism points out that the macroeconomic budget constraint – i.e. the quantitative
category determining the value of productive capital – is given by the supply of liquidity.
The supply of liquidity is not exogenous but controlled by the calculus of banks, which
preside over monetary creation and destruction. In the Neoclassical approach the
possibility of consumption fluctuation due to exogenous shocks can always be
compensated by a high enough rate of return. In contrast, in a monetary economy a shift
in confidence doesn’t lead directly to higher required returns – a higher risk premium –
but to a change in willingness to dispose of liquidity. When confidence declines, wealth
holders will prefer bank deposits to equity, and banks will pay off their liabilities with the
central bank. Thus, a change in liquidity preference leads to a change in the supply of
money and in the rate of interest. The scarcity of capital can therefore be said to be
intersubjectively determined, not objectively given, meaning that capital is not scarce but
kept scarce by the rational, self –interested decisions of financial market actors10.
Viewing the macroeconomic budget constraint as intersubjectively determined –
ultimately dependent on the degree of uncertainty that agents attach to their hypothesis
about the behavior of the totality of agents - allows for the role of perceptions to be
embedded in the notion of value. Thus, we have an economic explanation of price
dynamics in terms of the reflexive relationship between observable conditions and the
participants’ perceptions of them.
While standard theory treats markets as closed systems – as systems which have run
down to a state of entropic equilibrium – monetary economies are open. The phases of
stability are far from corresponding to a general equilibrium condition but can only be
maintained by a continuous flow of liquidity in and out of the system. This has three
implications for the valuation of productive capital. First, the monetary approach does not
change the fact that in equilibrium stock prices correspond to the expected present value
of future earnings. Equilibrium is, however, a construct of theory and not a state observed
in reality: it’s neither an average which can be read out of price series nor a state which
realizes itself if one only waits long enough. It’s by definition associated with a constant
state of confidence. Second, the absence of an anchor for estimating the long-term yield
of a capital asset implies that investors have to fall back on conventions. Conventions
give rise to periods of stability but are nevertheless precarious, subject to sudden and
violent changes. At such times, liquidity-preference increases, leading to a discontinuous
10
Keynes himself treated liquidity preference as a demand category and the supply of money as exogenous.
This hindered him from formulating a long-run equilibrium alternative to the neoclassical notion, in which
the non-neutrality of money wasn’t a short run phenomena (thus the famous saying “in the long-run we’re
all dead”). By emphasizing the function of money as means of payment, treating liquidity preference as a
supply category and endogenizing the budget constraint, Monetary-Keynesianism was able to fully and
explicitly formulate a monetary theory of value. Riese (1983), the main exponent of MonetaryKeynesianism, shows that a monetary equilibrium can be defined for any given degree of uncertainty and is
always characterized by underemployment of resources.
price fall. Third, contrary to the assertion of efficient markets theory, the existence of
organized markets does not ensure that capital flows to its most productive use. Instead,
organized markets create incentives for destabilizing speculation. Anticipating average
opinion gains in importance over the evaluation of the long-term yield of an asset.
By incorporating the concept of confidence, the liquidity-preference approach is able to
account for the boom and bust patterns that characterize real-world markets at different
levels of observation. The fluctuation of returns – an anomaly within the market
efficiency paradigm - is to be expected because it corresponds to shifts in confidence.
While shifts in confidence, by affecting risk preference, lead to changes in risk premia,
psychological factors - as suggested by behavioral finance - are responsible for those
shifts. Cymbalista [1998] shows how other anomalies, such as seasonal effects, size
effects, as well as the profitability of contrarian strategies can also be explained once one
sees the portfolio decisions of equity holders as equivalent to credit decisions. In
Keynesian economics it is possible to explain price changes causing price changes
independently from the profitability of the underlying firms without violating the
rationality assumption, the economic principle par excellence. Price changes signal the
willingness of the totality of market participants to surrender liquidity to the stock
market, affecting thus the degree of uncertainty concerning the recovery of the principal.
In case of organic interaction, relying on conventions despite their flimsy foundation is an
adequate, goal-oriented behavior. The same is true for liquidation by faltering confidence.
Shifts in confidence are a psychological phenomenon, but they don’t stem from a lack of
rationality of the decision calculus of investors.
By treating economic behavior as social behavior which itself is caused by social
behavior, the liquidity-preference approach overcomes the dichotomy between rational
and psychologically influenced valuation. Because it dissociates rationality from
linearity, it provides a theoretical underpinning not only for the study of the impact of
psychological processes on financial decision making but also for the application of a
complexity perspective to financial markets valuation. The shift from an atomistic to an
organic ontology questions the standard notion of rationality not only in microeconomic
terms but also with respect to the underlying epistemology. As shown below, complexity
is not compatible with a view of markets and their participants as information-processors:
it reveals them to be more than information processors.
II. More than Information Processors
1. Markets as Observing Systems
The liquidity-preference explanation of price dynamics in terms of the reflexive
relationship between observed conditions and the market participants perceptions of them
reveals the intersubjective character of valuation. Being themselves created in the
economic process, the structural conditions of the real sphere no longer offer an objective
anchor for the prices of financial assets. Instead, valuation is conventional. The
conventions at work involve institutional arrangements, shared working models and tools,
meanings supplied by the media. Such conventions - in particular the fact that
transactions are mediated by money, itself a social convention or institution - are
mutually constraining and regulate the system, reducing its degrees of freedom. Processes
where a myriad of highly heterogeneous, mutually constraining microbehavior gives rise
to coherent macrobehavior are the subject matter of complexity theory.
The complexity perspective is a paradigm for studying systems with a history,
where the end-state is not coded anywhere. It is a framework for understanding the
spontaneous emergence of qualitatively different processes through the interaction of the
system’s components, which applies to complex systems irrespective of their material
substrate. Because the principles for the global properties of complex systems apply both
to individual components and to the patterns that arise from their combination, they can
be used to describe the mental processes underlying the decisions of market participants
as well as the price pattern that result. Complex dynamic systems tend to converge to
stable configurations, called attractors. Attractors states aren’t externally anchored but
imposed by the system itself: the interaction itself imposes constraints on macrobehavior,
reducing the degrees of freedom of the system. Further, attractor states aren’t unique or
unchangeable: under different conditions, components are free to assemble into other
behavioral modes. While complex dynamic systems are inherently variable, showing
fluctuations around the stable state, most of this variation tends to return the system to the
attractor configuration. Within a certain range, the system can be seen as acting
parametrically: local perturbations are noise, not leading to a change in the global order.
At the same time, those inherent fluctuations are the source of new forms of behavior.
With increases in variability – which arise endogenously from the system itself rather
than being the result of an exogenous influence such as the random shocks postulated by
standard theory – the system behaves non-linearly. The fluctuations become enhanced
and variability comes to dominate the system, weakening the coherence in such a way
that no stable patterns can be discerned. At such critical points, even small perturbations
are sufficient to drive the system into a new attractor state; the system then settles into a
new global order.
In a monetary economy, consensual frames present such attractor states, emerging
and stabilizing out of the interactions of the multitude of heterogeneous participants. The
consensual frame remains stable as long as it is on average expected to remain stable, and
the very process that generates stability is also responsible for change. While stability
depends on a continuous flow of liquidity in and out of the system, the supply of liquidity
depends on the average perception of transition and/or stability. Periods of stability are
negative feedback-situations, a global order, but one which is not uniquely determined.
Positive feedback-situations give rise to phase shifts; at such times, liquidity preference
increases abruptly, causing a discontinuous price fall.
Unlike the linear models based on the orthodox treatment of financial market valuation,
complexity theory is able to encompass observed price behavior. It can describe the
phases of stability punctuated by boom and bust patterns which characterize real world
markets at different levels of observation. For the same phenomena are not only present
at different markets – whether we are concerned with the behavior of the stock market as
a whole, with markets for individual stocks or industries, or with the relationship between
different asset markets; they are also manifest over varying time scales – whether we are
dealing with stability or transition depends on the metric we choose.
The mathematics of non-linear dynamics, especially of chaos theory, has received
increasing attention in the financial literature, where it has been asserted that the
properties shown by price time-series are a result of investors’ not responding to
information in a linear fashion (Peters [1996]). But this explanation is flawed because it
shares the mainstream view of information as exogenous to the system, i.e. independent
of the observers, something “out there” to be reacted to. It fails to recognize the
distinguishing feature of the complexity approach: its focus on the interdependence of
observed conditions and the observer’s perceptions of them. In a dynamic framework,
information cannot be said to exist in and of itself. It is not an inherent property of events
but a continuous process, which is created over time through the interaction as the
perceiver engages with the event. Dynamic systems theory cannot be consistently applied
to the question of financial market valuation without considering that perceptions shape
economic processes. This undermines the notion that information can serve as an
objective benchmark for either linear or non-linear responses.
Because it does not rely on the common-knowledge assumption of mainstream
economics, i.e. on homogeneous expectations and complete information, the liquidity
preference, dynamic approach is able to fully encompass Hayek’s [1945] insight on the
communication function of prices. However, the view of the price system as a
communication system, which summarizes heterogeneous expectations and thus
transmits information between decentralized decision makers, needs to be modified with
respect to the concept of information. Hayek – as a neoclassical economist an advocate of
the neutrality of money - related heterogenity to local, specialized knowledge about the
relative scarcity of physical resources. In a monetary economy, price changes do not
reflect an unbiased – nor a biased - estimation of the impact of discrete events on the
long-run yield of underlying companies. Rather, price and volume data reveal changes in
the balance of power between the participants that value assets above their current price
and those that value assets below it. But they cannot be said to have a pre-existing
content that could be specified objectively, independent from the observer.
The meaning a market participant attaches to outside events – as well as to market
behavior – is constructed by him as he engages with them. Engagement as pre-condition
for perception means that the market participant’s perception changes in relation to his
action. Events aren’t informative in themselves but only to the extent that they are
meaningful in relation to individual experience. Consensual frames increase the
probability that particular forms of information will be constructed; a large number of
market participants will not only perceive outside events in a similar way but also share
perceptions of transition or stability, thus creating, reinforcing or reversing trends.
However, the price trajectories that result from the continuous mutual adjustments of the
participants do not converge to – nor diverge from – a true representation of economic
reality. In a dynamic framework, communication cannot be conceived of as an exchange
of messages about the true state of the world. Instead, the ongoing trading itself creates
information as it unfolds.
The creative price trajectories that emerge from conventional valuation express the mind
of the market, the collective behavior of the system. Like a living being, it changes to
accommodate action, continuously modifying itself before the participants’ eyes. In that
it reproduces the feedback between perceiving and acting of the market participants, the
mind of the market can also be seen as observing itself.
Viewing markets as observing systems requires a revision of the means of
inference we use. The interdependence between observer and observed entails an
epistemological shift with respect to both the cognitive processes which guide economic
action and the way we conduct scientific research. It directs our attention to the
experiential field of market participation, both supporting and setting constraints to the
choice of psychological approaches on which we can draw in order to comprehend the
mind of the market.
2. Comprehending the Mind of the Market
In a monetary economy, financial success does not depend on a correct estimation of any
objectively given intrinsic value, but on the ability to detect communication patterns, the
formation and dissolution of consensual frames. Pattern formation does not obey a
general, timeless scheme – which is the reason why trading models based on pattern
recognition only work for a short period of time. This means that the type of intelligence
involved cannot be reduced to deductive and inductive logic. Analytical modes of
inference have to be complemented by that cognitive modality which cannot be
encompassed by the information-processing, computer model of the mind behind the
standard treatment of economic decision making: intuition.
Intuition is a way of gathering data that draws on first-hand experience, related to our
capacity to be self-aware. At the same time, it’s a way of making meaning, a wholemaking reasoning mode. Intuition is the utmost contextual phenomena: the intuitive
understanding of a focal event is inseparable from the background knowledge that frames
it and endows it with a feeling of rightness, an experience which William James [1955]
called “fringe”. While nonconscious processes are at work, these do not contradict
rationality but rather underpin it.
In contexts where evidence is insufficient, ambiguous or liable to change,
intuition mediates between the general and the particular; it is the means by which we
know that general knowledge applies to the specific instance we are experiencing, to the
givens of the particular situation in which we find ourselves. Intuition involves a leap of
logic, a type of inference the philosopher C.S. Pierce [1992] labeled abductive – as
distinguished from deductive as well as inductive reasoning. Consider the rule “all the
beans from this bag are white”, the case “these beans are from this bag” and the result
“these beans are white”. With deduction the result follows from the rule and the case,
while with induction the rule is a generalization from the case and the result; in contrast,
with abduction we have the rule “all the beans...”, the result “these beans are white” and
guess the case: “these beans are from this bag”. Such non-analytical inference based on
felt sense not only allows us to situate ourselves in a complex environment, it is also
beneath scientific breakthroughs.
The role of intuition in financial forecasting is a theme that illustrates perhaps better than
any other the gap between scientific financial research and the direct experience of
market participants. While standard theory postulates that price changes are
unpredictable, market participants often attribute their success to an understanding of
crowd psychology and an instinctive capacity to grasp its effects, i.e. to recognize trend
formation and predict trend reversal11. Early empirical studies of market efficiency
rejecting the hypothesis that price changes are autocorrelated, as it would be expected in
the presence of trends, supported the dismissal of such claims by financial decision
making research. As the increasing number of anomalous findings encouraged finance to
consider the cognitive processes used by market participants, the role of intuitive
procedures began to be acknowledged. Yet most Behavioral Finance theorists associate
intuition with mental shortcuts open to fallibility, a source of distorted expectations and
decision biases that interfere with rational, i.e. fundamental value estimation. In this
sense, intuitive procedures have been offered as an explanation – alternative to market
efficiency – for the poor performance of active investment strategies; accordingly,
statistical training has been prescribed as a means to improve decision making. However,
the current valuation paradigm is not the right background for judging the (in)accuracy
and (in)adequacy of decision processes: intuitive procedures which are biased and
inefficient in a deterministic setting aren’t necessarily so in a complex environment.
In fact, Hammond et al. [1987] provides evidence against the association of
intuition with biased judgement as well as against the unconditional superiority of
analytical methods. Postulating a continuum of modes of thought that places both
intuition and analysis in a larger category of “rationmorphic” processes, a comparison
between a person’s use of intuition and analysis in tasks with different features shows
that the correspondence of task properties and cognitive properties has an effect on
performance. The intuitive mode is shown to maximize the probability of accurate
judgement in tasks presenting characteristics such as a large number of cues, continuous
and highly variable cues, high redundancy among cues, low decomposition, low degree
of certainty, unavailability of an organizing principle and simultaneous instead of
sequential display of cues and brief time period.
Hammond et al. recommends that experts increase their awareness of the
correspondence between task and cognition, examining task features to determine
whether the form in which the data is presented is primarily intuition inducing or analysis
inducing and adapting cognitive ability to features of the task. This lends support to the
argument that poor performance is partly a result of the inadequacy of the standard
analytical framework. Not only is the notion of fundamental valuation conceptually
flawed. Having an unattainable goal – a correct estimation of intrinsic value – also
impairs decision making. It generates insecurity and reduces the reliability of intuitive
decision processes. This mismatch between the analytical and the experiential mode thus
stifles the innate mechanisms with which evolution has provided us to handle a complex
environment, interfering with processes related to pattern recognition which are indeed
appropriate for the task at hand. Because it legitimizes the role of first-hand experience,
the view of markets as observing systems presents a conceptual framework that fosters
the accuracy of the intuitive mode.
If academic research of psychology and financial markets is to contribute to
decision making in a constructive way, it needs to encompass the positive side of
intuitive reasoning. Intuition remains an elusive concept within the objectivistic
11
This is emphasized, for instance, by Soros [1995] as well as almost all the trading legends interviewed by
Schwager [1989].
epistemology that underlies both the cognitive foundations of the standard notion of
decision making and research methodology. In contrast, a theoretical foundation for the
study of experiential aspects of financial decision making can be found in recent,
transdisciplinary developments in cognitive research which question the objectivistic
world-view. These reject the computationalist notion of rationality as the logical
manipulation of symbols which mirror the structure of objective reality. Cognition is,
instead, viewed as embodied, enacted and relational.
We draw on intuition when analogy uncovers some underlying order, when the
perception of similarity leads us to infer further similarity. Similarity is a quality. The
ability to discriminate between relevant and irrelevant qualities cannot be comprehended
as long the role our bodily experience plays in shaping the structures of understanding is
disregarded. The paradigm shift in cognitive research supersedes the separation between
mental concepts and bodily percepts characteristic of the information-processing model
of the mind. At the center of the new view is the belief that meaning and rationality is
embodied: cognition emerges from our experience as bodily organisms functioning in
interaction with the environment.
Enaction is a concept exposed by Varela et al. [1991] and emphasized by scholars
that adopt a systemic perspective. It expresses the idea that knowledge does not arise with
the representation of a pre-given world but is participatory: reality is constructed by the
sensory-motor system of organisms interactively alive in their environment. Particular
mention deserve the notion of self-organizing systems proposed by the neurobiologists
Maturana and Varela [1987], the dynamic systems approach to cognition and action of
developmental psychologists Thelen and Smith [1994] and the relational approach of
developmental psychologist Fogel [1993]. Cognition is understood as resulting from the
feedback mechanism which exists between the sensory and the motor part of the nervous
system, i.e. between perception and action. This means that experience is not something
that we have or that happen to us, but something we do: in order to perceive anything we
must act in a certain way. What we see – and do not see – depends on how we see.
Moreover, perception is learned. What we see depends on prior stages of learning, on our
history of interaction with the environment, on what we’ve learned to see. Philosopher of
mind Johnson [1987] and linguist Lakoff [1987] show how embodied, sensory-motor
structures are carried into abstract realms through metaphoric projection and imagination.
While the notion of enactment defies the possibility of knowledge of an objective
reality independent from the observer, it does not subscribe to solipsistic subjectivism.
Rather, it rejects a dualism of observer and observed, denying the necessity of a choice
between objectivism and subjectivism. Mind and environmental context are no longer
seen as two inherently different and separate entities but as enfolded in a multiplicity of
ways. In the ecological approach of cognitive psychologist Rosch [1996], subjective and
objective aspects arise together as opposite poles of the same event: experience falls
between mind and world and encompasses both. This somewhat counterintuitive insight –
after all, at the conscious level, we do experience observer and observed as different and
separate - is supported by research on the neurobiology of consciousness. Neuroscientist
Damasio [1999] shows that in the act of knowing, the organism catches itself in the act of
representing its own changing state as it goes about representing something else. Whether
we are concerned with neural patterns, with mental patterns or with behavioral patterns,
knowledge cannot be seen solely in terms of two players, that which is to be known and
that to which we attribute knowledge; it has to be conceived in terms of the relationships
they hold.
What are the implications of the new view for a unified theory of psychology and
financial markets?
First, the systemic perspective suggests we view market participation as a
relational activity and focus on the interaction between the participant and the mind of the
market. Market participation cannot be reduced to either individual mental phenomena or
to information existing out there in the economic world. The appropriate unit of analysis
for a unified theory of psychology and financial markets is thus neither an isolated, selfcontained market participant nor an outside event but market participation itself.
Second, the new view hints at a starting point for the development of tools to
improve actual decision making. Market participation occurs in concrete, specific
situations, whereby the participant’s bodily sensed meaning implicitly contains the
context in which he finds himself. This inner-sense perceptiveness that allow us to
capture context is the reason why discretionary human judgement is necessary to
complement purely analytical methods and formal models. Developing intuition, the
comparative advantage which human decision makers have over trading systems,
involves a different kind of learning than the analytical competence taught at business
schools. The idea of cognition as being embodied and enacted implies the usefulness of
methods which study behavior not from the outside, from a third-person viewpoint, but
from the inside, from the first person view point. Methods that address first-hand
experience do not presuppose the mind-body dichotomy that underlies conventional
Western philosophical and scientific inquiry. Instead, they make use of the dual character
of human observation, of our capacity to be internally self-aware as well as externally
aware. With this in mind, Varela et al. [1991] have proposed the application of
meditation principles and techniques to scientific practice. In combination with a
conceptual framework for market valuation which legitimizes the role of first-hand
perception, awareness enhancing practices – whether meditation or some other modality
of self-sensing education – might offer the best basis for accessing the intuitive element
of prediction. A training of decision procedures aimed at developing the ability to
discriminate between valid intuition – i.e. resonance, attunement – and biased projections
that lead to signals such as fear and wishful thinking may seem odd given the
metaphysics of our culture. But it certainly obeys the basic tenet of good pedagogy: to
build upon what market participants are already doing.
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