On Ignorance, Intuition, and Investing: A Bear Market Test of the Recognition Heuristic

Boyd, Michael

doi:10.1207/s15327760jpfm0203_4

Cited by 53 publications

(34 citation statements)

References 5 publications

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“…In contrast, Boyd (2001) found no such advantage when he used college students' recognition of stocks rather than that of the general public. It is imperative to understand why and under what conditions this simple heuristic can survive in financial markets without making a systematic market analysis.…”

Section: Investmentmentioning

confidence: 88%

Heuristic Decision Making

Martignon

Gaissmaier

2011

Annu. Rev. Psychol.

2,894

1,740

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As reflected in the amount of controversy, few areas in psychology have undergone such dramatic conceptual changes in the past decade as the emerging science of heuristics. Heuristics are efficient cognitive processes, conscious or unconscious, that ignore part of the information. Because using heuristics saves effort, the classical view has been that heuristic decisions imply greater errors than do "rational" decisions as defined by logic or statistical models. However, for many decisions, the assumptions of rational models are not met, and it is an empirical rather than an a priori issue how well cognitive heuristics function in an uncertain world. To answer both the descriptive question ("Which heuristics do people use in which situations?") and the prescriptive question ("When should people rely on a given heuristic rather than a complex strategy to make better judgments?"), formal models are indispensable. We review research that tests formal models of heuristic inference, including in business organizations, health care, and legal institutions. This research indicates that (a) individuals and organizations often rely on simple heuristics in an adaptive way, and (b) ignoring part of the information can lead to more accurate judgments than weighting and adding all information, for instance for low predictability and small samples. The big future challenge is to develop a systematic theory of the building blocks of heuristics as well as the core capacities and environmental structures these exploit.

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Section: Investmentmentioning

confidence: 88%

Heuristic Decision Making

Martignon

Gaissmaier

2011

Annu. Rev. Psychol.

2,894

1,740

View full text Add to dashboard Cite

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“…Borges, Goldstein, Ortmann, and Gigerenzer (1999) make much of the finding that a portfolio of stocks recognized by over 90% of Munich pedestrians beat portfolios selected by experts and those of two benchmark mutual funds during the period December 1996 -June 1997. However, as Boyd (2001) suggested, this effect may simply have been a big-firm effect. High capitalization and high recognition tend to go together (Over, 2000b), and in the strong "bull market" of those months, the high capitalization stocks of the big firms tended to do very well.…”

Section: On the Adaptivity Of Recognitionmentioning

confidence: 95%

On the Role of Recognition in Decision Making.

Newell

Shanks

2004

Journal of Experimental Psychology: Learning, Memory, and Cogni

101

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In 2 experiments, the authors sought to distinguish between the claim that recognition of an object is treated simply as a cue among others for the purposes of decision making in a cue-learning task from the claim that recognition is attributed a special status with fundamental, noncompensatory properties. Results of both experiments supported the former interpretation. When recognition had a high predictive validity, it was relied on (solely) by the majority of participants; however, when other cues in the environment had higher validity, recognition was ignored, and these other cues were used. The results provide insight into when, where, and why recognition is used in decision making and also question the elevated status assigned to recognition in some frameworks (e.g., D. G. Goldstein & G. Gigerenzer, 2002).

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“…For example, recognition of company names was a good predictor of stock performance in the study of Borges et al (1999), but it completely failed in a different market situation (Boyd, 2001). Hence, before praising partial ignorance as the silver bullet in tennis prediction, one has to show that Serwe and Fring's results are systematic.…”

Section: The Recognition Heuristicmentioning

confidence: 97%

Predicting Wimbledon 2005 tennis results by mere player name recognition

Scheibehenne

Bröder

2007

International Journal of Forecasting

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The outcomes of matches in the 2005 Wimbledon Gentlemen's tennis competition were predicted by mere player name recognition. In a field study, amateur tennis players (n = 79) and laypeople (n = 105) indicated players' names they recognized, and predicted match outcomes. Predictions based on recognition rankings aggregated over all participants correctly predicted 70% of all matches. These recognition predictions were equal to or better than predictions based on official ATP rankings and the seedings of Wimbledon experts, while online betting odds led to more accurate forecasts. When applicable, individual amateurs and laypeople made accurate predictions by relying on individual name recognition. However, for cases in which individuals did not recognize either of the two players, their average prediction accuracy across all matches was low. The study shows that simple heuristics that rely on a few valid cues can lead to highly accurate forecasts.

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On Ignorance, Intuition, and Investing: A Bear Market Test of the Recognition Heuristic

Cited by 53 publications

References 5 publications

Heuristic Decision Making

Heuristic Decision Making

On the Role of Recognition in Decision Making.

Predicting Wimbledon 2005 tennis results by mere player name recognition

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