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FRANK ABELLA JR

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85-year-old Investment Professional with extensive experience in wealth management, discovering the essential elements that make for effective decision-making.

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Papers by FRANK ABELLA JR

The Framing of Decisions and the Psychology of Choice

Ecxplanations and predictions of people's choices, in everyday life as well as in the social scie... more Ecxplanations and predictions of people's choices, in everyday life as well as in the social sciences, are often founded on the assumption of human rationality. The definition of rationality has been much debated, but there is general agreement that rational choices should satisfy some elementary requirements of consistency and coherence. In this article

$Fig. 1. A hypothetical value function. The majority choice in decision (i) is risk averse: a riskless prospect is pre- ferred to a risky prospect of equal or greater expected value. In contrast, the majority choice in decision (ii) is risk tak- ing: a risky prospect is preferred to a riskless prospect of equal expected val- ue. This pattern of risk aversion in choices involving gains and risk seeking in choices involving losses is attributable to the properties of v and 77. Because the value function is S-shaped, the value as- sociated with a gain of $240 is greater than 24 percent of the value associated with a gain of $1000, and the (negative) value associated with a loss of $750 is smaller than 75 percent of the value asso- ciated with a loss of $1000. Thus the shape of the value function contributes to risk aversion in decision (i) and to risk seeking in decision (ii). Moreover, the underweighting of moderate and high probabilities contributes to the relative attractiveness of the sure gain in (i) and to the relative aversiveness of the sure loss in (ii). The same analysis applies to problems 1 and 2. has the following properties. First, im- possible events are discarded, that is, ar(0) = 0, and the scale is normalized so that (1) = 1, but the function is not well behaved near the endpoints. Second, for low probabilities mp) >p, but mp) + 71 — p) = 1. Thus low proba- bilities are overweighted, moderate and high probabilities are underweighted, and the latter effect is more pronounced than the former. Third, m(pq)/7(p) < a(pqr\/a(pr) for allO <p,q,r = 1. That is, for any fixed probability ratio g, the ratio of decision weights is closer to unity when the probabilities are low than when they are high, for example, a(.1)/77(.2) > a(.4)/77(.8). A hypothetical weighting function which satisfies these properties is shown in Fig. 2. The major qualitative properties of decision weights can be extended to cases in which the probabilities of outcomes are subjective- ly assessed rather than explicitly given. In these situations, however, decision weights may also be affected by other characteristics of an event, such as am- biguity or vagueness (9). So ee a abo we wees ll ee a? en LS |$

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