When is market the benchmark? Reinforcement evidence from repurchase decisions

Reinforcement relative to an adaptive benchmark is a well-established model of behavior outside finance. Recently, reinforcement has been identified as an important driver of decisions to repurchase a stock. In this paper, we enrich the existing reinforcement model of repurchasing by an aspiration-based market benchmark. When choosing which stock to repurchase, investors' sources of reinforcement are weighted averages of absolute returns from previous sales and relative returns with respect to a market benchmark. The weights change according to market environments. We empirically identify the following crucial asymmetry that cannot be reconciled by simple reinforcement strategy, but is consistent with the model we propose: investors place more weight on relative returns when the market is performing well, and place more weight on absolute returns when the market is performing badly

Payoff-Based Belief Distortion

Heterogeneous beliefs often arise among people with the same information but different personally experienced payoffs. To explain this, I propose a mechanism in which experienced payoffs distort beliefs: gains lead an agent to relatively underweight negative new signals and thus to become overoptimistic, whereas losses do the opposite. I experimentally test this mechanism and find behaviour consistent with its predictions. The experiment created a setting where payoffs carried no informational value for Bayesian updating, and thus offered a strong test for the effect of payoffs on beliefs. The findings were robust, and distinct from alternative mechanisms in important ways

Adoption and Abandonment of Decision-Making Principles: Evidence from Cournot Experiments

We conducted a controlled laboratory experiment to understand how and what kind of information triggers adoption and abandonment of different decision-making principles in games. We consider three types of decision-making principles: best-response, payoff-based learning, and imitation. Our focus is on Cournot contests, where Nash equilibrium is located between social optimum and social pessimum. Subjects start in a low-information environment, where only payoff-based learning is feasible, and end up with full information, where all types of decision-making rules apply. Treatments vary with respect to the order with which information is revealed as the game is repeated. Our study is designed to address three main questions. (1) The 'marginal' effect of information: Which new bits of information trigger which principle? (2) The 'additive' effect: How does the history of previously available information affect (1)? (3) The 'substitution' effect: How are decision-making principles abandoned and adopted? Thus, we establish a novel link from micro-heuristics to various resulting macro-dynamics of play, which converge either toward Nash equilibrium or toward a socially inferior zero-profit outcome

Attention constraints and learning in categories

Many decision makers are thought to economize on attention by processing information at the simpler level of a category. We directly test whether such category focus reflects an adaptive response to attention constraints, in five preregistered experiments using an information sampling paradigm with mouse tracking. Consistent with rational principles, participants focus more on category-level information when individual differences are small, when the category contains more members, and when time constraints are more severe, though cognitive load has no effect. Participants are sensitive to the statistical structure of the category even when it must be learned from experience, and they respond to a latent shift in this structure. Beliefs about category members tend to cluster together more when category focus is high—a key element of rational inattention. However, this is counteracted by greater weight placed on salient and idiosyncratic information when the category is large. Our results broadly substantiate influential theories of categorical thinking, giving us a clearer view on the drivers and consequences of inattention

The Double-Channeled Effects of Experienced payoffs in Investment Decisions

Experiences have significant influences on subsequent decisions. This chapter demonstrates, in a controlled lab experiment of investment decision making, that subjects engaged in reinforcement learning. A further investigation of the mechanism by directly eliciting beliefs reveals that participants were more optimistic about an asset after gaining from it than after losing. This happened even though experienced payoffs contained no informational value beyond the descriptive information provided in the experiment, and there was clear tension between Bayesian and reinforcement learning. These findings suggest that double-channeled effects (belief-based and nonbelief-based) of experienced payoffs could underlie investors' reinforcement learning