The behavioural components of risk aversion

Davies, Greg B.; Satchell, Stephen

doi:10.1016/j.jmp.2006.10.003

Cited by 29 publications

(15 citation statements)

References 27 publications

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“…The current heuristic cannot be predicated solely on avoiding risk, because otherwise individuals would always select guaranteed pay-offs by sharing the points with the two opponents. Understanding the components of risk aversion and how this affects decision-making constitutes a complex problem (Davies & Satchell 2007). An oftenused index of risk is the 'risk premium', the amount by which the expected value (EV ) of a gamble exceeds a guaranteed pay-off.…”

Section: Discussionmentioning

confidence: 99%

Strength determines coalitional strategies in humans

et al. 2009

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Coalitions enhance survival and reproductive success in many social species, yet they generate contradictory impulses. Whereas a coalition increases the probability of successfully obtaining rewards for its members, it typically requires a division of rewards among members, thereby diminishing individual benefits. Non-human primate data indicate that coalition formation is more likely when an individual's probability of success is low when competing alone. No comparable studies exist for humans. Here we show using a computerized competitive game that humans exhibit a systematic, intuitive strategy for coalition formation based on their own and others' levels of perceived strength, a pattern that resembles coalition formation in chimpanzees, Pan troglodytes. Despite equal expected pay-offs for all strategies, subjects were more likely to form coalitions as their own level of perceived strength waned. Those chosen as coalition partners tended to be stronger individuals or arbitrarily designated 'friends'. Results suggest a heuristic for human coalitionary decisions that rests on the perception of relative power rather than on the assessment of pay-offs.

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Section: Discussionmentioning

confidence: 99%

Strength determines coalitional strategies in humans

et al. 2009

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“…For example, Galanter (1962) found a concave shape by asking participants to judge how much money would make them twice as happy as a reference amount. Other theories place risk aversion elsewhere (see Davies & Satchell, 2007, for a recent discussion).…”

Section: Descriptive Models Of Risky Decision Makingmentioning

confidence: 99%

EPS Prize Lecture: Decision by sampling: The role of the decision environment in risky choice

Stewart

2009

Quarterly Journal of Experimental Psychology

102

123

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Decision by sampling (DbS) is a theory about how our environment shapes the decisions that we make. Here, I review the application of DbS to risky decision making. According to classical theories of risky decision making, people make stable transformations between outcomes and probabilities and their subjective counterparts using fixed psychoeconomic functions. DbS offers a quite different account. In DbS, the subjective value of an outcome or probability is derived from a series of binary, ordinal comparisons with a sample of other outcomes or probabilities from the decision environment. In this way, the distribution of attribute values in the environment determines the subjective valuations of outcomes and probabilities. I show how DbS interacts with the real-world distributions of gains, losses, and probabilities to produce the classical psychoeconomic functions. I extend DbS to account for preferences in benchmark data sets. Finally, in a challenge to the classical notion of stable subjective valuations, I review evidence that manipulating the distribution of attribute values in the environment changes our subjective valuations just as DbS predicts.

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“…In accordance with Davies and Satchell (2007), we examine the characteristics of π v for sufficiently small risks by taking a first-order Taylor approximation around the reference point on the left-hand side (LHS) of the above equation:…”

Section: First-order Risk Aversion Loss Aversion and Local Risk Attmentioning

confidence: 99%

Risk Aversion, Loss Aversion, and the Demand for Insurance

Eeckhoudt

Fiori

Gianin

2018

Risks

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Abstract:In this paper we analyze insurance demand when the utility function depends both upon final wealth and the level of losses or gains relative to a reference point. Besides some comparative statics results, we discuss the links with first-order risk aversion, with the Omega measure, and with a tendency to over-insure modest risks that has been been extensively documented in real insurance markets.

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The behavioural components of risk aversion

Cited by 29 publications

References 27 publications

Strength determines coalitional strategies in humans

Strength determines coalitional strategies in humans

EPS Prize Lecture: Decision by sampling: The role of the decision environment in risky choice

Risk Aversion, Loss Aversion, and the Demand for Insurance

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