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Sonic Thunder vs Brian the Snail: Fast-sounding racehorse names and prediction accuracy in betting exchange markets

Oliver Merz (), Raphael Flepp () and Egon Franck ()
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Oliver Merz: Department of Business Administration, University of Zurich
Raphael Flepp: Department of Business Administration, University of Zurich
Egon Franck: Department of Business Administration, University of Zurich

No 384, Working Papers from University of Zurich, Department of Business Administration (IBW)

Abstract: This paper examines the influence of objectively irrelevant information on prediction accuracy in horse-racing betting exchange markets. In horse racing, the name of a horse does not depend on the horse’s performance and is thus uninformative. We investigate the impact of fast-sounding horse names on prediction market price accuracy and betting returns. Using over 3 million horse bets, we find evidence that the winning probabilities of bets on horses with fast-sounding names are overstated, which impairs the prediction accuracy of such bets. This finding implies that the prices in betting exchange markets are not efficient, as prices become distorted by incorporating the misleading information from a horse’s fast-sounding name. This bias translates into significantly lower betting returns for horses classified as fast-sounding compared to the returns of all other horses.

Keywords: Market efficiency; Sports forecasting; Prediction markets; Betting industry; Horse Racing (search for similar items in EconPapers)
JEL-codes: D40 G40 C53 L83 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-for, nep-ore and nep-spo
Date: 2019-10
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