مدارک و شواهد برای آموزش زیست محیطی و حوزه اختصاصی در قیمت گذاری منطقی دارایی و کارایی بازار

This article is interested in how efficiently individuals can use available information, and if this will translate into efficient outcomes at the market level. Our use of available information in markets is further specified by evolutionary psychology and behavioral ecology, which extend core theory and evidence in behavioral finance throughout the reviewed literature. The survey of the social, biological and physical literature is integrative, and demonstrates how evolved design at the individual level can interact with a market environment that evolves as a complex adaptive system. In general, the analysis also highlights the central importance of complex systems in the study of rational and efficient markets.

The norm of rationality is often criticized as an abstract ideal. Yet, without it in consumption and investment decisions, the modern economy that one takes for granted would indeed be a figment of the imagination. Take, for instance, the interaction between the finance, product, and labor markets. A rational financial market will allocate capital into profitable enterprise, where an efficient asset price quickly and fully reflects all available relevant information as to the fundamental value of a firm (Fama, 1970). Over a longer time scale, the profitability of enterprise in the product market will allocate goods and services by demand, and interact with the labor market to allocate the labor demanded (Swann and McEachern, 2006). Ongoing interaction between these markets will cause feedback between the price level and output (Blanchard and Sheen, 2009), a system dynamic that is driven by interdependence between a network of networks (Gao et al., 2011), but is also prone to collapse (Buldyrev et al., 2010). Over the long term, however, growth would appear robust. Through specialization and innovation in profitable goods and services, rational consumption and investment thereby leads to increasing comparative advantage and interaction by trade in an evolutionary process of real growth (Ridley, 2010), and as a result, a greater amount of capital to invest in profitable activity. If the investment of capital does not fully reflect the fundamental value of an asset, limited resources will be less efficiently allocated, and therein rests the unavoidable relevance of a rational and efficient financial market in prosperity. Although models of bounded rationality assume a less sophisticated decision process than rational models, acting on limited information with a limited cognitive capacity is efficient enough if price can approximate the fundamental value. For example, there is evidence that simple decision rules such as satisficing are adaptations to exploit the structure of available information, and lead to accurate decisions in a wide range of ecologically valid contexts where information is limited (Gigerenzer, 2007). The economic utility of an accurate decision, on the other hand, may not necessarily correspond to utility in evolutionary fitness, particularly in uncertain conditions (Haselton et al., 2009). To further complicate the market effects of individual decisions, market-level rationality and efficiency can emerge from diverse behavior at the individual level (Arthur, 1996, Chen and Yeh, 2002 and Bao et al., 2012), where efficiency can naturally emerge in a market that evolves as a complex adaptive system (Lo, 2004 and Mauboussin, 2005). Despite some irreducibility in emergent and complex economic patterns, it is shown to be a matter of degree (Harper and Endres, 2011), in which case individual behavior can still scale up and aggregate into market behavior to some extent. Even if market behavior only partially reflects the behavior of participants, system-level outcomes will depend on how well we are designed to interact with evolving and increasing socioeconomic complexity, something that is undergoing recent and rapid change from our evolutionary past (Dunbar, 2012). That said, the goal of this article is not weigh into a debate on these particular issues, but to review evidence in the social, biological and physical literature that further explains rational and efficient interaction between an evolving market environment and its participants, where rational asset pricing is essential for the efficient allocation of investment capital. The motivation, ultimately, is that behavioral finance models do imply natural constraints, by assuming a lower level of rationality than the rational expectations hypothesis and efficient markets hypothesis. Although behavioral finance is mainly concerned with how people and markets actually behave, not the fundamental reasons why as such, the regular and sometimes catastrophic failure of markets provide many compelling reasons to look deeper at more elusive aspects of the forces at work. At an individual and ecological level, investor–market interaction is a prime candidate for behavioral ecology and evolutionary psychology. Both fields extend core theory and evidence in behavioral finance throughout the reviewed literature, and information theory complements this integrative approach. In general, two issues in modern markets are highlighted: the dissemination of misinformation in a signal-rich environment, and a rate of information change that exceeds our ability to make rational decisions. The surveyed works establish the importance of these concerns, and justify interdisciplinary effort. To this effect, the aim is to encourage a more intensive examination of the diverse target literature. As a conceptual reference point throughout the discussion, Section 2 contrasts performance in using more or less information when interacting with complex systems. In Section 3, developments in information theory further specify the ecological contexts of personal and social information in learning the environment, and relate to evidence for interaction with the market environment as a complex adaptive system. In Section 4, evolutionary-recurrent features of socioeconomic organization in complex adaptive systems imply discrete adaptations to aspects of modern markets. This premise of domain-specificity in evolutionary psychology is seen in loss aversion and the endowment effect, and can provide insight into their adaptive contexts. In particular, evolutionary psychology also explains the ideal conditions in which life-like properties can emerge in market behavior, as defined by Arthur (1996). Section 5 concludes with a discussion of key points in the literature to be taken into consideration, and suggests directions for future work. 2. Performance in simple versus complex expectations At the individual level, rational expectations are model-consistent. Rational expectations may not necessarily be correct, but cannot be improved by any available information (Black, 2003). At the market level, a rational and efficient asset price needs to quickly and accurately reflect all available information that is relevant to fundamental value (Jones et al., 2007). Behavioral finance does not consider the rational expectations hypothesis to be entirely realistic, and instead assumes less rationality in actual decisions and market outcomes. It is reasonable to assume a limited capacity for rational judgment. The market value of an asset does not always reflect all available information as to its intrinsic economic value, and regularly deviates from the rational price for current and expected future returns (Petty et al., 2009). These issues point to several problems with defining limits in rational expectations and strong-form efficiency. As a starting point, we should be interested in how the availability of all fundamental information is physically limited, and how quickly and accurately can human cognition model all relevant determinants of asset price. Asset value is determined by a very large number of interrelated variables at the micro and macro level (Viney, 2009 and Jones et al., 2007), so our ability to model complexity can be viewed as a key aspect of rational investment. This demand on cognitive performance is not only influenced by fundamentals. Market value can also be affected by factors irrelevant to fundamental value, such as the psychology of investors (Blanchard and Watson, 1982) in a complex expectations ecology of mutually reinforcing and mutually competing hypotheses (Arthur, 1996). All features of any complex system are rarely, if ever, completely visible to active observation (Dorner, 1996), therefore our interest in rational performance should begin with our ability to accurately model a system, in relation to the physical aspects of information availability.

Behavioral ecology and evolutionary psychology both extend behavioral finance in the reviewed literature. However, the discussion has not attempted to reconcile the theoretical contradictions between learning strategies for dual-inheritance and domain-specific adaptation. Learning to alternate the use of complex reasoning and simple rules may be adaptive when interacting with complex systems. Personal information will likely have more ecological validity in high entropy market conditions, and social information will likely have more ecological validity in low entropy market conditions. Coding effort and ambiguity in referential systems specify the trade-off between attention and information availability. Dual-phase evolution implies that model uncertainty will increase if a market or economy is in a perturbation phase, and decrease in a growth phase. Dual-phase evolution and evolutionary games in scale-free interaction networks also lend weight to core theory in evolutionary psychology, as they describe the evolutionary-recurrent organization of status and wealth dynamics. Despite theoretical differences, behavioral ecology and evolutionary psychology lend insight into the interaction between individuals, financial markets, and economic evolution. The emergent properties of this dynamic may both impede and enhance rational and efficient market outcomes, where the main relevance of a financial market is the efficient allocation of investment capital in economic growth. Several issues warrant attention in applying evolutionary theory to behavioral finance, and invariably relate to the statistical mechanics of complex systems. First and foremost are our cognitive limits when interacting with a very large system that evolves of its own accord. Secondly, the intransparence of a complex system will make investment risk uncertain, so a representation of certain risk in an experiment may not have ecological validity, or reflect the actual outcomes of financial decisions. Most importantly, what is conspicuous throughout this discussion is the pervasiveness of core theory in behavioral finance, such as the availability heuristic, the endowment effect, and the certainty effect. While an assumption of economic irrationality in ambiguity may not necessarily be supported, evolutionary theory does extend their relevance in the finance and economics literature. As demonstrated at length, it is important to note that this does not just involve evolutionary theory alone. In any case, this article hopes to have encouraged more interdisciplinary effort and interest in the positive nature of behavioral finance, as classical theory is rife with normative prescriptions that may not necessarily reflect the actual dynamics and socioeconomic outcomes in the real world. That said, the observations made in this discussion can be readily inferred simply by comparing the surveyed literature, and a more intensive enquiry of the reviewed works should be the rational conclusion. In general, however, one observation is quite prominent, and that is the policy implications of research by Barber and Odean (2011). Even if rational and efficient pricing can naturally emerge in markets, this discussion has not ruled out the likelihood that participation by less-informed traders will aggregate in the inefficient allocation of investment capital over different time scales. In light of such concern, regulators should seriously consider an educational effort that is marketed toward retail traders, and entertain the possibility of private licensing programs to filter such participation. A number of perhaps ambitious directions for future research can therefore be suggested. At an artificial level, computer simulations may want to examine the cumulative effect of socioeconomic evolution on available information, and the demands this may place on information-processing and performance in artificial agents. The ecological validity of bias in sentiment may be empirically tested with people, by structuring less-informed and more-informed participants in experimental markets designed to simulate evolution and change in the fundamental state. In particular, it would be interesting to see the related effects on adaptive learning such as reinforcement learning and adaptive expectations (Abbink et al., 2001, Evans and Honkapohja, 2003, March, 1996 and Denrell and March, 2001), and how this can impact on variation in intuitive expertise and operative intelligence between participants. To conclude, real growth should be the primary motivation behind research in rational and efficient markets, even though complexity in comparative advantage and the availability of resources may have increasing ecological novelty with time. Resource accumulation has the effect of lowering fertility rates as an adaptive response (Hill and Reeve, 2005), and innovation in the evolutionary process of real growth leads to a more efficient output from available inputs (Ridley, 2010). Economic growth is therefore something that cuts both ways: it may be more unwieldy with time, but it can also reduce population growth and our impact on the planet. The role of financial markets is crucial in this process. As rational and efficient pricing will reflect neither an over-investment or under-investment of limited capital in profitable activity, we should be very interested in understanding how evolved design can affect rational performance in financial decisions, and impact on market outcomes.