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Order book microstructure and fair price estimation on betting exchanges
Smutný, Josef ; Fanta, Nicolas (advisor) ; Kukačka, Jiří (referee)
The aim of this paper is to predict the fair price as accurately as possible from the microstructure of the orderbook on Betfair, the world's largest betting exchange. In particular, the work focuses on the analysis of the effect of disproportionately large quotes on the fair price of the market. It also addresses their theoretical monetization in practice in the case of market inefficiency. The results show that, from the data examined, traded markets are relatively efficient and the factors that can be inferred from the microstructure of the orderbook are, in the vast majority of cases, not statistically significant for predicting the fair price of a given event. However, the data do show exceptions where, in particular types of markets, these quotes are statistically significant and have the expected impact on the model's prediction in the form of increasing the probability of the selection they want to trade. Thus, the model prediction can in some cases be used as a fair price indicator by which one could theoretically trade profitably on Betfair or even on other platforms, assuming they offered a better price. Keywords Betting exchange, Fair price, Quotes, Betting odds, Back, Lay, Spread Title Order book microstructure and fair price estimation on betting exchanges
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