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Complexity as a guide to understanding decision bias: A contribution to the favorite‐longshot bias debate
Author(s) -
Sung MingChien,
Johnson Johnnie Eric Victor,
Dror Itiel E.
Publication year - 2009
Publication title -
journal of behavioral decision making
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 76
eISSN - 1099-0771
pISSN - 0894-3257
DOI - 10.1002/bdm.629
Subject(s) - attractiveness , odds , economics , cognitive bias , cognition , financial economics , microeconomics , positive economics , econometrics , psychology , computer science , logistic regression , machine learning , neuroscience , psychoanalysis
This paper investigates the origins of a widespread decision bias in betting markets, the favorite‐longshot bias (FLB); in particular, whether it is caused by cognitive errors on the part of bettors or by the pricing policies of bookmakers. The methodology is based on previous literature, which has suggested that: (i) races, as decision tasks for bettors, can be distinguished by their degree of complexity and their attractiveness to those with access to privileged information (insiders), (ii) cognitive errors increase as complexity increases, and (iii) bookmakers set odds in a manner to protect themselves from insiders. The degree of FLB was examined in races of varying complexity and attractiveness to insiders using a dataset of 8545 races drawn from the parallel bookmaker and pari‐mutuel markets operating in the UK in 2004. The results, interpreted in the light of the cognitive error and complexity literature, suggest that neither bettors' nor bookmakers' cognitive errors are the main cause of the bias. Rather, bettors' preferences for risk and the deliberate pricing policies of bookmakers play key roles in influencing the bias in markets where bookmakers and pari‐mutuel operators coexist. Copyright © 2008 John Wiley & Sons, Ltd.