Exchange vs. Dealers: A High-Frequency Analysis of In-Play Betting Prices

Transcription

1 Exchange vs. Dealers: A High-Frequency Analysis of In-Play Betting Prices Department of Economics, Lancaster University October Karen Croxson Oxford-Man Institute and University of Oxford J. James Reade Department of Economics, University of Birmingham

2 Introduction Technology has transformed the betting industry: Betting exchanges (e.g. Betfair). Betting exchanges are prediction markets (Wolfers and Zitzewitz, 2004): 1 : Participants trade contracts with pay-out contingent on some event occurring. Resulting dual-structure to betting industry: Exchanges and bookmakers (bookies). Similarity with financial markets: Auction and dealership mechanisms. Exchanges offer better prices but bookmakers continue to grow: Why? Punters can now bet during sports event. We exploit high-liquidity, high-frequency dataset from Euro 2008: Both bookies (William Hill, Ladbrokes) and exchange (Betfair) data. First high-frequency, in-running investigation of market structure. 1 Wolfers, J. and Zitzewitz, E., 2004, Prediction Markets, Journal of Economic Perspectives, 18(2). j.j.reade@bham.ac.uk kcroxson@gmail.com 2

3 Betting Market as Lens to Investigate Financial Markets? Both markets: Agents with different beliefs trade to make profit. Advantages: True price of gamble revealed in long run. Time frame short: No need to discount. Sports easy to understand, widely broadcast, incentives clear. Disadvantages: Non-profit-driven trading: Bet on favourite team. Lack of liquidity, absence of underlying allocation of capital. On balance: Fantastic opportunity to study characteristics of markets: E.g. Efficient markets hypothesis. Gil and Levitt (2008), Croxson and Reade (2010). 3

4 Outline of Talk 1. Introduce bookies and exchange betting. 2. Compare markets and consider accuracy. 3. Investigate punter behaviour: When should they switch? 4. Conclude. 4

5 Framework for Analysis Sports match has N events spanning event space. Bookmakers have traditionally offered odds for event i, O i, i = 1,..., N. If bettor stakes x at O i gets x(o i + 1) if event i happens. Online exchanges typically quote in decimal odds DO i = O i + 1. If bettor stakes x at DO i gets xdo i if event i happens. Inverse of DO i can be interpreted as probability of i offered by betting firm: Offered Prob i : P i = 1/DO i. (1) j.j.reade@bham.ac.uk kcroxson@gmail.com 5

6 Switching Point Punter should switch when for bet size D, rx j < r j b. Bookies can offer more liquidity than exchange: Reason why bookies have continued to grow despite existence of exchanges? Odds (decimal) mean (2%) median (2%) mean (5%) median (5%) William Hill mean (2.86) Ladbrokes mean (2.82) William Hill and Ladbrokes median (2.25) D Ozgit finds about $100, we get about $ (mean), $ (median). j.j.reade@bham.ac.uk kcroxson@gmail.com 26

7 Liquidity Provision? Switching bet size very large: Potentially larger than bookies will practically accept frequently? These results question sustained growth of bookies: Betfair marginally more accurate, offers better returns, high liquidity. 6 Betfair William Hill Ladbrokes j.j.reade@bham.ac.uk kcroxson@gmail.com 27

8 Continued Growth of Bookmakers Bookies growing but losing market share? Hard to examine... Online interface necessary? More complicated set-up? Betfair ok on laptop at home but at the stadium? Fails to explain online use of bookies though... Bookies punters relatively unsophisticated? Is trading metaphor offputting? 28

9 Conclusions and Future Work First high-frequency comparison of bookmakers and betting exchanges. Insight into structure of financial markets using lens of sport. Exchange (slightly) more accurate, offers better odds and sufficient liquidity. Begs question (for football at least): Why are bookies still growing? Future work: Cointegration analysis: Which firm leads price/odds discovery? How is information processed on Betfair? 29