Informational efficiency and behaviour within in-play prediction markets

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.

Home advantage in professional soccer and betting market efficiency: The role of spectator crowds

“…This is to some extent what Choi and Hui (2014) refer to as conservatism and overreliance on prior expectations. Still, literature on in-game betting (Angelini et al, 2022;Choi & Hui, 2014;Croxson & Reade, 2014;Gil & Levitt, 2007) finds an adaptation process to in-game exogenous shocks such as goals over time which we hardly observe. 10…”

“…Especially the favorite‐longshot bias, namely that bets on clear favorites are more profitable than bets on underdogs, has attracted much attention (Angelini & De Angelis, 2019; Cain et al, 2000, 2003; Deschamps & Gergand, 2007; Oikonomidis et al, 2015; Reade et al, 2020). However, there is also evidence of markets without any, with only a weak, or even with a reversed longshot pattern (Angelini et al, 2022; Angelini & De Angelis, 2019; Elaad et al, 2020; Forrest & Simmons, 2008; Franck et al, 2011; Goddard & Asimakopoulos, 2004; Kuypers, 2000; Oikonomidis et al, 2015). Potential reasons for the longshot bias can be risk‐hedging pricing strategies of betting providers against insider trading (Cain et al, 2003; Shin, 1991, 1992, 1993), bettors' overconfidence or image effects (Direr, 2011; Golec & Tamarkin, 1995; Sauer, 1998; Vaughan Williams, 1999) and odd salience.…”

“…Especially the favorite-longshot bias, namely that bets on clear favorites are more profitable than bets on underdogs, has attracted much attention (Angelini & De Angelis, 2019;Cain et al, 2000Cain et al, , 2003Deschamps & Gergand, 2007;Oikonomidis et al, 2015;Reade et al, 2020). However, there is also evidence of markets without any, with only a weak, or even with a reversed longshot pattern (Angelini et al, 2022;Angelini & De Angelis, 2019;Elaad et al, 2020;Forrest & Simmons, 2008;Franck et al, 2011;Goddard & Asimakopoulos, 2004;Kuypers, 2000;Oikonomidis et al, 2015).…”

“…To analyze this approach to efficiency, the literature has mainly focused on within-match news and their immediate or delayed effects in within-match betting. Angelini et al (2022), Choi and Hui (2014), Croxson andReade (2014), andGil andLevitt (2007) find that odd changes during matches are driven by how unexpected an event is, e.g., very unexpected goals. Less surprising goals, on the other hand, even tend to be underpriced at the beginning with an improving accuracy throughout the following minutes.…”

A Market for Trading Forecasts: A Wagering Mechanism

“…Prediction markets can suffer from informational inefficiency as well and consequently, behavioural biases can get reflected in prices (Angelini et al, 2022). Furthermore, if a trader has the same belief about a particular stock price as it is in the prediction market, they simply have no incentive to participate (Lambert et al, 2008).…”