2016CORTISPhD.pdf (1.61 MB)
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Betting Markets: Defining odds restrictions, exploring market inefficiencies and measuring bookmaker solvency

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posted on 17.06.2016, 10:02 by Dominic Cortis
Betting markets have been of great interest to researchers as they represent a simpler set-up of financial markets. With an estimated Gross Gambling Revenue of 45bn yearly on betting on outcomes alone (excluding other gambling markets such as Casino, Poker and Lottery), these markets deserve attention on their own merit. This thesis provides simple mathematical derivation of a number of key statements in setting odds. It estimates the expected bookmaker profit as a function of wagers placed and bookmaker margin. Moreover it shows that odds set by bookmakers should have implied probabilities that add up to at least one. Bookmakers do not require the exact probability of an outcome to have positive expected profits. They can increase profitability by having more accurate odds and offering more multiples/accumulators. Bookmakers can lower variation in payouts by maintaining the ratio of wagers and implied probability per outcome. While bookmakers face significant regulatory pressures as well as increased taxes and levies, there is no standard industry model that can be applied to evaluate the minimum reserves for a bookmaker. Hence a bookmaker may be under/over-reserving funds required to conduct business. A solvency regime for bookmakers is presented in this work. Furthermore a model is proposed to forecast soccer results – this focuses on goal differences in contrast to traditional models that predict outcome or goals scored per team. Significant investigations are made on the inefficiencies of betting markets. The likelihood of Brazil reaching different stages of the 2014 World Cup, as perceived by odds, is compared to events on and outside the pitch to imply bias. An analysis of over 136,000 odds for European soccer matches shows evidence of the longshot bias. Finally this work investigates how it is possible to profit from market inefficiencies on betting exchanges during short tournaments by using a Monte Carlo simulation method as a quasi-arbitrage model.



Levesley, Jeremy

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Department of Mathematics

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University of Leicester

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