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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. 5 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. 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