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When participants assess the relationship between two variables, each with levels of presence and absence, the two most robust phenomena are that: (a) observing the joint presence of the variables has the largest impact on judgment and observing joint absence has the smallest impact, and (b) participants’ prior beliefs about the variables ’ relationship influence judgment. Both phenomena represent departures from the traditional normative model (the phi coefficient or related measures) and have therefore been interpreted as systematic errors. However, both phenomena are consistent with a Bayesian approach to the task. From a Bayesian perspective: (a) joint presence is normatively more informative than joint absence if the presence of variables is rarer than their absence, and (b) failing to incorporate prior beliefs is a normative error. Empirical evidence is reported showing that joint absence is seen as more informative than joint presence when it is clear that absence of the variables, rather than their presence, is rare.

This paper has three main parts. We first present a brief survey of the behavioral anomalies in the finance literature classified as: price and return effects, volume and volatility effects, time series patterns and other miscellaneous effects. For each category, we find that the empirical literature offers a multitude of explanations. We then develop a theoretical information-processing framework to examine the psychology of financial decision making. Many extant behavioral anomalies noted in the finance literature can be derived from this framework. The theoretical framework comprises both cognitive and motivational antecedents of bias in financial decision making. The model posits five stages at which cognitive biases may arise: perception, memory-retrieval, information integration, making a judgment, and behavior. Motivational effects are theorized as either directly affecting the manner in which information is processed, or indirectly moderating the likelihood that cognitive bias...

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Integration of contingency information underlies many cognitive tasks including causal, covariational, and probability judgments. The authors'feature-analytic approach was used to account for the findings that people differentially weight specific types of conjunctive information in causal (Experiment 1) and noncausal (Experiment 2) contingency judgments. These findings were explained in terms of positive-test and sufficiency-test biases, which were found in both judgment domains. The same biases, however, were not observed in normative conditional-probability judgments (Experiment 3). The authors argue that this discrepancy is owing to the differential clarity of normative criteria in these domains. Much of human learning and inferential thinking depends on the integration of contingency information. To test hypotheses and revise beliefs; to explain past events and predict future ones; to establish categories, form stereotypes, and develop impressions of others, humans integrate a vast amount of information about interevent contingencies. In short, the ability to discriminate contingencies in the physical

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Framing effects occur when logically equivalent redescriptions of objects or outcomes lead to different behavior, and such effects have traditionally been seen as irrational. However, recent evidence has shown that a speaker’s choice among logically equivalent attribute frames can implicitly convey (or “leak”) normatively relevant information about, among other things, the speaker’s reference point. Reinterpreting data published elsewhere, this article shows that some common effects in inference tasks (covariation assessment and hypothesis testing) can also be seen as framing effects, thereby expanding the domain of framing. It is also shown that these framing effects are normatively defensible because normatively relevant information about event rarity is leaked through the description of data and through the phrasing of hypotheses, thereby broadening the information leakage approach to explaining framing effects. Information leakage can also explain why framing effects in these inference tasks disappear under certain conditions. Framing Effects in Inference Tasks-- 3 Framing Effects in Inference Tasks – And Why They’re Normatively Defensible A trend in research on reasoning is to explain, in rational terms, behavior that has