Determinants of betting market efficiency

Abstract

Previous studies of efficient markets in parimutuel betting isolated only one race characteristic, determining efficiency by comparing subjective to objective probabilities of different groupings. By incorporating regression analysis and looking at a wide range of race specific variables, this study is able to isolate various factors which influence efficiency. Using a data set of 5020 races at 18 US racetracks, a standard favourite-longshot bias was found, which diminishes for races with larger pools and more horses in a field, and increases for races with higher quality fields and maiden races. When track-specific characteristics are factored out, similar results occur and it is also found that races on grass reduce the bias.

Substitute effects between Lotto and Big Lotto in Taiwan

“…Mikesell and Zorn (1987) proposed that new games need to be added to ensure continued successful sales of existing games. Gramm and Owens (2005) found that larger pools increase the quality of the betting market. To maintain the momentum of lottery sales, Taipei Back inaugurated a new 6/49 numbers game (Big Lotto) in January 2004.…”

Issues in sports forecasting

“…The bias is diminished if either the betting pool or the number of horses in the race is increased. (Busche and Hall, 1988;Gramm and Owens, 2005).…”

Keeping a weather eye on prediction markets: The influence of environmental conditions on forecasting accuracy

“…Horseracing Factors: Previous research has indicated that the accuracy of forecasts derived from prices in horseracing markets may be influenced by race specific factors such as: number of runners (Gramm and Owens, 2005), whether the race is a handicap (Brown, 2016), the number of bends that horses encounter in the race (Johnson et al, 2010), the class of the race (Sung et al, 2012), whether the race is run at a weekend (Sung et al, 2012), whether the race is the first or last of the day at a particular racetrack (Johnson and Bruce, 1993) and the bookmaker commission charged on the race (Vaughan Williams and Paton, 1998). We include all these factors in the regression as control variables, together referred to as 'Horseracing Factors'.…”