The effect of behavioral biases on financial decisions

Financial management decisions are made by people, and people, in all instances, are shaped by their behavioral traits. Here we provide extensive insight on the theoretical and empirical analysis made on cognitive biases and their influence on financial decisions. To provide a systematic exposition, we set three broad categories: heuristics and biases, choices (including framing and preferences) and social factors. We then describe the main biases within each category and provide an extensive revision of the main theoretical and empirical developments about their impact on financial decisions.Las decisiones de gestión financiera las toman las personas, y las personas, en todos los casos, están determinadas por sus rasgos de comportamiento. Aquí proporcionamos una visión amplia del análisis teórico y empírico realizado sobre los sesgos cognitivos y su influencia en las decisiones financieras. Para proporcionar una exposición sistemática, establecemos tres categorías amplias: heurísticas y sesgos, elecciones (incluidos encuadres y preferencias) y factores sociales. A continuación, describimos los principales sesgos dentro de cada categoría y proporcionamos una revisión exhaustiva de los principales desarrollos teóricos y empíricos sobre su impacto en las decisiones financieras

Measuring time preferences

We review research that measures time preferences—i.e., preferences over intertemporal tradeoffs. We distinguish between studies using financial flows, which we call “money earlier or later” (MEL) decisions and studies that use time-dated consumption/effort. Under different structural models, we show how to translate what MEL experiments directly measure (required rates of return for financial flows) into a discount function over utils. We summarize empirical regularities found in MEL studies and the predictive power of those studies. We explain why MEL choices are driven in part by some factors that are distinct from underlying time preferences.National Institutes of Health (NIA R01AG021650 and P01AG005842) and the Pershing Square Fund for Research in the Foundations of Human Behavior

Proposition structure in framed decision problems: A formal representation.

Framing effects, which may induce decision-makers to demonstrate preference description invariance violation for logically equivalent options varying in semantic emphasis, are an economically significant decision bias and an active area of research. Framing is an issue inter alia for the way in which options are presented in stated-choice studies where (often inadvertent) semantic emphasis may impact on preference responses. While research into both espoused preference effects and its cognitive substrate is highly active, interpretation and explanation of preference anomalies is beset by variation in the underlying structure of problems and latitude for decision-maker elaboration. A formal, general scheme for making transparent the parameter and proposition structure of framed decision stimuli is described. Interpretive and cognitive explanations for framing effects are reviewed. The formalism’s potential for describing extant, generating new stimulus tasks, detailing decision-maker task elaboration. The approach also provides a means of formalising stated-choice response stimuli and provides a metric of decision stimuli complexity. An immediate application is in the structuring of stated-choice test instruments

An inclusive taxonomy of behavioral biases

This paper overviews the theoretical and empirical research on behavioral biases and their influence in the literature. To provide a systematic exposition, we present a unified framework that takes the reader through an original taxonomy, based on the reviews of relevant authors in the field. In particular, we establish three broad categories that may be distinguished: heuristics and biases; choices, values and frames; and social factors. We then describe the main biases within each category, and revise the main theoretical and empirical developments, linking each bias with other biases and anomalies that are related to them, according to the literature

Rationality and choices in economics: behavioral and evolutionary approaches

The paper critically discusses the issue of rationality and choices in economics in both the behavioural and evolutionary approaches. Our study aims, on the one hand, to highlight the scientific contributions of psychology in economics, since psychology, and with it the theoretical approach of the behavioral economics, has made more complex and problematic the analysis of economic choices, showing the limits of rationality. On the other hand, the work offers a reinterpretation of the theory of Alfred Marshall in a biologicalevolutionary perspective. The reinterpretation of Marshall's theory in a evolutionary perspective aims to show that, historically, economics has not been a discipline aligned in a homogenous way to a single and undifferentiated thought, locked into the idea of perfect rationality, but, on the opposite, is a discipline that has enriched itself and continually is enriching by contributions and significant contaminations with other research fields.rationality; choices; behavioral economics; evolutionary theories; biology;

Modeling the Psychology of Consumer and Firm Behavior with Behavioral Economics

Marketing is an applied science that tries to explain and influence how firms and consumers actually behave in markets. Marketing models are usually applications of economic theories. These theories are general and produce precise predictions, but they rely on strong assumptions of rationality of consumers and firms. Theories based on rationality limits could prove similarly general and precise, while grounding theories in psychological plausibility and explaining facts which are puzzles for the standard approach. Behavioral economics explores the implications of limits of rationality. The goal is to make economic theories more plausible while maintaining formal power and accurate prediction of field data. This review focuses selectively on six types of models used in behavioral economics that can be applied to marketing. Three of the models generalize consumer preference to allow (1) sensitivity to reference points (and loss-aversion); (2) social preferences toward outcomes of others; and (3) preference for instant gratification (quasi-hyperbolic discounting). The three models are applied to industrial channel bargaining, salesforce compensation, and pricing of virtuous goods such as gym memberships. The other three models generalize the concept of gametheoretic equilibrium, allowing decision makers to make mistakes (quantal response equilibrium), encounter limits on the depth of strategic thinking (cognitive hierarchy), and equilibrate by learning from feedback (self-tuning EWA). These are applied to marketing strategy problems involving differentiated products, competitive entry into large and small markets, and low-price guarantees. The main goal of this selected review is to encourage marketing researchers of all kinds to apply these tools to marketing. Understanding the models and applying them is a technical challenge for marketing modelers, which also requires thoughtful input from psychologists studying details of consumer behavior. As a result, models like these could create a common language for modelers who prize formality and psychologists who prize realism

Myopic Loss Aversion and the Equity Premium Puzzle

The equity premium puzzle, first documented by Mehra and Prescott, refers to the empirical fact that stocks have greatly outperformed bonds over the last century. As Mehra and Prescott point out, it appears difficult to explain the magnitude of the equity premium within the usual economics paradigm because the level of risk aversion necessary to justify such a large premium is implausibly large. We offer a new explanation based on Kahneman and Tversky's 'prospect theory'. The explanation has two components. First, investors are assumed to be 'loss averse' meaning they are distinctly more sensitive to losses than to gains. Second, investors are assumed to evaluate their portfolios frequently, even if they have long-term investment goals such as saving for retirement or managing a pension plan. We dub this combination 'myopic loss aversion'. Using simulations we find that the size of the equity premium is consistent with the previously estimated parameters of prospect theory if investors evaluate their portfolios annually. That is, investors appear to choose portfolios as if they were operating with a time horizon of about one year. The same approach is then used to study the size effect. Preliminary results suggest that myopic loss aversion may also have some explanatory power for this anomaly.

Spatial Dynamic Modeling and Urban Land Use Transformation:

Assessing the economic impacts of urban land use transformation has become complex and acrimonious. Although community planners are beginning to comprehend the economic trade-offs inherent in transforming the urban fringe, they find it increasingly difficult to analyze and assess the trade-offs expediently and in ways that can influence local decisionmaking. New and sophisticated spatial modeling techniques are now being applied to urban systems that can quickly assess the probable spatial outcomes of given communal policies. Applying an economic impact assessment to the probable spatial patterns can provide to planners the tools needed to quickly assess scenarios for policy formation that will ultimately help inform decision makers. This paper focuses on the theoretical underpinnings and practical application of an economic impact analysis submodel developed within the Land use Evolution and Impact Assessment Modeling (LEAM) environment. The conceptual framework of LEAM is described, followed by an application of the model to the assessment of the cost of urban sprawl in Kane County, Illinois. The results show the effectiveness of spatially explicit modeling from a theoretical and a practical point of view. The agent-based approach of spatial dynamic modeling with a high spatial resolution allows for discerning the macro-level implications of micro-level behaviors. These phenomena are highlighted in the economic submodel in the discussion of the implications of land use change decisions on individual and communal costs; low-density development patterns favoring individual behaviors at the expense of the broader community.

Measuring and Modeling the Construction of Preferences in Decision Making under Risk

When people are asked whether they like to take risks, their responses are typically consistent over time and predictive of real-world behavior. Hence, risk attitude can be regarded as a stable psychological trait (Frey et al., 2017). Yet, in behavioral risky choice tasks used in psychological and economic research—such as choices between lotteries, abstractly described in terms of outcomes and probabilities—behavior often varies considerably across measurement time-points and formats of the task (Frey et al., 2017; Pedroni et al., 2017). It seems paradoxical that decisions in these situations—which try to condense the problem of decision making under risk to its essential parts—are rarely an expressions of a person’s stable, latent risk attitude. This dissertation examines why experimental risky choice behavior can be notoriously hard to predict, and how the methodological and theoretical apparatus with which we approach the study of risk preferences shapes the inferences we can make. In the first chapter I introduce major theoretical perspectives on decision making under risk and the methods their proponents rely on. The notion of constructed preferences (Lichtenstein & Slovic, 2006; Slovic, 1995) is introduced as a general framework for understanding the lack of temporal stability and convergent validity of behavioral measures of risk attitude. According to this framework, behavioral risk preferences may be constructed on the spot, in the light of available cues and processing capacities. Hence, features of the choice environment—which have nothing to do with risk itself—and psychological characteristics of the decision maker—besides dispositional risk attitude—may profoundly shape the process and output of preference construction. In the subsequent chapters I investigate how surface features of stimulus materials, and individual differences in psychological characteristics, as well as their interplay, shape risky choice behavior. I also use different approaches of computational modeling to describe and explain these changes in risky choice and the underlying cognitive processes. In chapter 2 I demonstrate that in choices between a risky and a safe option, apparent age differences in risk attitude crucially depend on whether the options differ in complexity, rather than on age differences in latent risk attitude. In chapter 3 I investigate whether differences in option complexity also shape (age differences in) tasks used to measure framing effects, loss aversion, and delay discounting. This experiment identifies boundary conditions for the effects of option complexity. In chapter 4 I turn from focusing predominantly on behavior and its dependence on the anatomy of the task towards underlying cognitive processes. I demonstrate that risky choice behavior is shaped by differences between younger and older adults in the ability to implement selective attention. In chapter 5 I demonstrate why it may be useful to view risky choice through the lens of different formal theories—both economic and psychological ones—by identifying systematic signatures of attentional biases simulated in the attentional drift diffusion model in the parameters of cumulative prospect theory. Overall, this dissertation shows why decision making under risk cannot be comprehensively understood in terms of latent risk attitude alone. It identifies specific contextual (option complexity) and psychological (selective attention) determinants of risky choice behavior which need to be taken into account as well, and explains how they affect the underlying process of preference construction, using computational modeling. Moreover, this work underlines the merits of theoretical and methodological pluralism for studying the variable, context-sensitive aspects of risky choice behavior and individual differences therein