Informational efficiency and behaviour within in-play prediction markets

Giovanni Angelini, Luca De Angelis and Carl Singleton

No em-dp2019-20, Economics Discussion Papers from Department of Economics, University of Reading

Abstract: Studies of financial market informational efficiency have proven burdensome in practice, because it is difficult to pinpoint when news breaks and is known by some or all the participants. We overcome this by designing a framework to detect mispricing, test informational efficiency and evaluate the behavioural biases within high-frequency prediction markets. We demonstrate this using betting exchange data for association football, exploiting the moment when the first goal is scored in a match as major news that breaks cleanly. There are pre-match and in-play mispricing and inefficiency in these markets, explained by reverse favourite-longshot bias (favourite bias). The mispricing tends to increase when the major news is a surprise, such as a goal scored by a longshot team late in a match, with the market underestimating their chances of going on to win. These results suggest that, even in prediction markets with large crowds of participants trading state-contingent claims, significant informational inefficiency and behavioural biases can be reflected in prices.

Keywords: Market efficiency; Favourite-longshot bias; Mispricing; Sports forecasting; Probability forecasting; Behavioural bias; Betting strategy (search for similar items in EconPapers)
JEL-codes: C58 D01 G14 G41 L83 Z2 (search for similar items in EconPapers)
Pages: 43 pages
Date: 2019-12-19, Revised 2021-04-01
New Economics Papers: this item is included in nep-ore and nep-spo
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Published in International Journal of Forecasting, 2022, 38(1): 282-299, https://doi.org/10.1016/j.ijforecast.2021.05.012

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http://www.reading.ac.uk/web/FILES/economics/emdp201920.pdf Revised version, 2021 (application/pdf)

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Journal Article: Informational efficiency and behaviour within in-play prediction markets (2022)
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