The University of Southampton
University of Southampton Institutional Repository

Complexity as a guide to understanding decision bias: A contribution to the favorite-longshot bias debate

Complexity as a guide to understanding decision bias: A contribution to the favorite-longshot bias debate
Complexity as a guide to understanding decision bias: A contribution to the favorite-longshot bias debate
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 8,545 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 co-exist.
complexity, favorite-longshot bias, betting markets, probability judgments
0894-3257
318-337
Sung, M.
2114f823-bc7f-4306-a775-67aee413aa03
Johnson, J.E.V.
6d9f1a51-38a8-4011-a792-bfc82040fac4
Dror, I.
3babcfd3-c7a5-45a3-a204-64213b6d907b
Sung, M.
2114f823-bc7f-4306-a775-67aee413aa03
Johnson, J.E.V.
6d9f1a51-38a8-4011-a792-bfc82040fac4
Dror, I.
3babcfd3-c7a5-45a3-a204-64213b6d907b

Sung, M., Johnson, J.E.V. and Dror, I. (2009) Complexity as a guide to understanding decision bias: A contribution to the favorite-longshot bias debate. The Journal of Behavioural Decision Making, 22 (3), 318-337. (doi:10.1002/bdm.629).

Record type: Article

Abstract

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 8,545 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 co-exist.

Text
101002bdm629.pdf - Other
Download (563kB)

More information

Published date: 2009
Keywords: complexity, favorite-longshot bias, betting markets, probability judgments
Organisations: Management, Cognition

Identifiers

Local EPrints ID: 63545
URI: http://eprints.soton.ac.uk/id/eprint/63545
ISSN: 0894-3257
PURE UUID: bd5db460-d4f9-4b69-8c77-2e38af969d73
ORCID for M. Sung: ORCID iD orcid.org/0000-0002-2278-6185

Catalogue record

Date deposited: 15 Oct 2008
Last modified: 16 Mar 2024 03:39

Export record

Altmetrics

Contributors

Author: M. Sung ORCID iD
Author: J.E.V. Johnson
Author: I. Dror

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×