A progress report on the training of probability assessors

Alpert, Marc; Raiffa, Howard

doi:10.1017/cbo9780511809477.022

Cited by 592 publications

(361 citation statements)

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“…and then have participants estimate 90% confidence intervals around their answers. Results show that these confidence intervals are too narrow, suggesting that people are too sure they know the correct answer; 90% confidence intervals contain the correct answer less than 50% of the time (Alpert & Raiffa, 1969Klayman, Soll, Gonzalez-Vallejo, & Barlas, 1999;Soll & Klayman, 2004).…”

Section: Trouble With Overconfidencementioning

confidence: 96%

The trouble with overconfidence.

Moore

Healy

2008

Psychological Review

1,852

1,414

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The authors present a reconciliation of 3 distinct ways in which the research literature has defined overconfidence: (a) overestimation of one's actual performance, (b) overplacement of one's performance relative to others, and (c) excessive precision in one's beliefs. Experimental evidence shows that reversals of the first 2 (apparent underconfidence), when they occur, tend to be on different types of tasks. On difficult tasks, people overestimate their actual performances but also mistakenly believe that they are worse than others; on easy tasks, people underestimate their actual performances but mistakenly believe they are better than others. The authors offer a straightforward theory that can explain these inconsistencies. Overprecision appears to be more persistent than either of the other 2 types of overconfidence, but its presence reduces the magnitude of both overestimation and overplacement.

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Section: Trouble With Overconfidencementioning

confidence: 96%

The trouble with overconfidence.

Moore

Healy

2008

Psychological Review

1,852

1,414

View full text Add to dashboard Cite

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“…On the other hand, if the trader is not rational, then his or her subjective belief is parameterized by K j = K , where K is a nonnegative misperception parameter such that K = 1. Furthermore, a nonrational trader is overconfident if his or her subjective distribution is too tight, i.e., 0 ≤ K < 1, or underconfident if it is too loose, i.e., K > 1 (Oskamp (1965), Alpert and Raiffa (1959), Einhorn and Hogarth (1978)). …”

Section: Overconfidence In a Pairwise Contestmentioning

confidence: 99%

Overconfidence, Investor Sentiment, and Evolution

Wang¹

2001

Journal of Financial Intermediation

124

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We examine the survival of nonrational investors in an evolutionary game model with a population dynamic for a large economy. The dynamic indicates that the growth rate of wealth accumulation drives the evolutionary process. We focus our analysis on the survival of overconfidence and investor sentiment. We find that underconfidence or pessimism cannot survive, but moderate overconfidence or optimism can survive and even dominate, particularly when the fundamental risk is large. These findings provide new empirical implications for the survivability of active fund management. Our results lend support to the relevance of the psychology of investors in studying financial markets. Journal of Economic Literature Classification Numbers: G10, G14. C 2001 Academic Press

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“…The elicitation of lower and upper quantiles for a bounded uncertain quantity adheres to the prevailing view that lower and upper bounds of an uncertain phenomenon as a rule fall outside of the accumulated experience of a substantive expert (see, e.g., Selvidge (1980), Davidson and Cooper (1980), Alpert and Raiffa (1982), Keefer and Verdini (1993)) Forcing a substantive expert in such a .…”

Section: Indirect Elicitation Of Tail Parameters and Lower And Upper mentioning

confidence: 89%