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When referring to this work, full bibliographic details including the author, title, awarding institution and date of the thesis must be given e.g. AUTHOR (year of submission) "Full thesis title", University of Southampton, name of the University School or Department, PhD Thesis, pagination http://eprints.soton.ac.uk UNIVERSITY OF SOUTHAMPTON FACULTY OF BUSINESS AND LAW SCHOOL OF MANAGEMENT WEAK FORM EFFICIENCY AND PRICING DYNAMICS IN A COMPETITIVE GLOBALISED MARKET SETTING Anastasios Oikonomidis Thesis for the degree of Doctor of Philosophy (Management) 2 3 September 2013 UNIVERSITY OF SOUTHAMPTON ABSTRACT FACULTY OF BUSINESS AND LAW Management Doctor of Philosophy WEAK FORM EFFICIENCY AND PRICING DYNAMICS IN A COMPETITIVE GLOBALISEDMARKET SETTING by Anastasios Oikonomidis Employing data from the football betting market, we explore the impact of institutional structure on price-setting in speculative markets and the extent to which the biases induced by such factors might cause prices to deviate from fundamental values. In Chapter 1, we review the literature on football betting markets with regards to the Efficient Market Hypothesis (EMH) and find that despite sporadic evidence of pricing anomalies, more consistent and persistent evidence of exploitable betting opportunities is required for the EMH to be rejected. In Chapter 2, we investigate the favourite-longshot bias in the bookmaker market and find that the bias is persistent over a long period of time and related to the parity of the league. A traditional price-setting bookmaker is willing to pay a premium to stimulate overall bettor demand in a competitive market, by setting generous odds on favourites to attract customers. In leagues with more parity among teams, the apparent bias is reduced as the market requires less intervention on the part of the bookmaker. Heterogeneity in bookmaker operations and price-setting is the focus of Chapter 3. We categorize bookmakers as either position-takers or book-balancers. Position-takers operate a high-margin, low-turnover business model, rarely adjust their odds, and actively eschew informed traders. Book-balancers frequently change their prices, and operate under the alternative, high-turnover, low-margin strategy. Sophisticated traders are not restricted at book-balancing bookmakers, and as such, odds movements at position-takers lag converge in the direction of the odds at book- balancers. We conclude that the sophisticated traders aid the price discovery process at the book-balancing bookmakers, which leads the market to efficiency. Finally, in Chapter 4 we examine instances of significant dispersion between the two types of bookmakers and show that the generation of positive returns is theoretically possible. However, closer investigation of these finding reveals that market-makers’ odds are efficient predictors of event outcomes and therefore, the opportunity to generate profit is provided by biases in position-takers’ pricing. Such biases could either be intentional for the purpose of attracting customers or the result of such bookmakers’ odds lagging behind in reflecting upcoming information. In all cases, such bookmakers are very likely to pose restrictions successful traders and therefore, the exploitation of the documented anomaly is probably infeasible. 4 5 Table of Contents List of Tables and Figures 9 Declaration of Authorship 11 Acknowledgements 12 Introduction 13 Chapter 1: Who Can Beat the Odds? The Case of Football Betting Reviewed 22 1.1. Historical Development of Football Betting Markets 22 1.2. Weak Form Efficiency 24 1.2.1. Introduction 24 1.2.2. Odds as Predictors 25 1.2.3. Odds Biases 26 1.2.4. Market Variation 28 1.2.5. Arbitrage 29 1.2.6. Signals from Variation of Odds 30 1.2.7. Summary 31 1.3. Semi-Strong Form Efficiency 31 1.3.1. Introduction 31 1.3.2. Forecasting Methods 32 1.3.3. Home Advantage 32 1.3.4. Performance Measuring Models 33 1.3.5. Behavioural Biases 35 1.3.6. Subjective Estimations 36 1.3.7. Betting In-Running 38 1.3.8. Summary 39 1.4. Strong Form Efficiency 39 1.4.1. How Are Matches Fixed? 40 1.4.2. Identifying Potentially Fixed Games 41 1.4.3. Summary 42 6 1.5. Conclusions 42 Chapter 2: Bias and Efficiency in European Markets for State Contingent Claims 51 2.1. Introduction 52 2.2. Weak form efficiency in betting markets: the literature 54 2.2.1. Horserace betting markets 54 2.2.2. American football betting markets 55 2.2.3. Other sports betting markets 55 2.2.4. Soccer betting markets 56 2.3. The fixed-odds soccer betting market 56 2.4. Data and methodology 58 2.4.1. Data 58 2.4.2. Methods 59 2.4.2.1. Exploring Homogeneity: Efficiency in European fixed odds soccer betting markets 59 2.4.2.2. Exploring the causes of efficiency differentials 62 2.5. Results 66 2.5.1. Variations in returns across odds categories 66 2.5.2. Modelling winning probabilities to assess FLB 69 2.5.3. Investigating the roots of cross-market differences in efficiency 74 2.6. Discussion 80 Chapter 3: Bettors vs. Bookmakers: 1-0! Examining the Origins of Information in Football Betting Markets 87 3.1. Introduction 88 3.2. Literature Review 91 3.2.1. Bookmakers – Theory and Evidence 91 3.2.2. The Population of Bettors 95 3.3. Hypotheses Development 99 3.4. Data and Methodology 105 7 3.4.1. Data 105 3.4.2. Identifying characteristics to distinguish the type of bookmaker 106 3.4.3. Methodology 112 3.4.3.1. Differences between bookmakers 112 3.4.3.2. Transmission of Information within the Market 113 3.4.3.3. The Efficiency of Odds-Based Estimates 118 3.5. Results 119 3.5.1. Differences between Bookmakers 119 3.5.2. Transmission of Information from Bettors to Bookmakers 124 3.5.3. The Relative Efficiency of Odds-Based Forecasts 131 3.6. Discussion 137 Chapter 4: Arbitrage Mirage: Exploring the Extent to Which Apparent Inefficiency in Betting Markets is an Illusion 144 4.1. Introduction 145 4.2. Literature Review 147 4.2.1. Information Efficiency 147 4.2.2. Arbitrage 148 4.2.3. The Bookmaker Market 150 4.3. Hypotheses Development 155 4.4. Data and Methodology 159 4.4.1. Data 159 4.4.2. Methodology 163 4.4.2.1 Exploring the occurrence of apparent arbitrage opportunities 163 4.4.2.2. Exploring the source of apparent arbitrage opportunities 168 4.4.2.3. Exploring which group of bookmakers is more likely to be responsible for the generation of the arbitrage opportunity 169 4.5. Results 173 4.5.1. Investigating Arbitrage Opportunities 173 4.5.2. The Parties in the Arbitrage-Mirage 177 5.4.3. “Winners” and “Losers” from Apparent Arbitrage Opportunities 180 8 4.6. Discussion 184 5. Conclusion 191 9 List of Tables and Figures Table 2.1. Betting returns for different level of odds 67 2.2. Betting returns for different level of odds (Spain II v Italy I) 68 2.3. The Favourite Longshot Bias across different leagues. Conditional Logit estimation 71 2.4. Transaction costs vs Favourite Longshot Bias. Conditional Logit estimation, part I 75 2.5. Transaction costs vs Favourite Longshot Bias. Conditional Logit estimation, part II 77 2.6. Favourite Longshot Bias vs League Competitiveness 79 3.1. Key distinguishing features of Position-takers and Book-balancers 111 3.2. Relative Frequency of Odds Moves (Ladbrokes & Sbobet) 122 3.3. Summary Statistics of Odds Moves (Ladbrokes & Sbobet) 123 3.4. Average Over-round by bookmaker in Lead up to Kick-Off (Ladbrokes & Sbobet) 123 3.5. Fisher-Type Unit-Root test statistics (Ladbrokes & Sbobet) 124 3.6. Model Selection Statisics (Sbobet and Ladbrokes) 125 3.7. Random-Effects Model Results (Ladbrokes) 128 3.8a. Random-Effects Model Results, when Odds Move (Ladbrokes) 129 3.8b. Random-Effects Model Results, when Odds Move (Ladbrokes), focusing on the lagged difference to SBO 130 3.9. Predicting Closing Odds (Ladbrokes) from Early Odds (Ladbrokes & Sbobet) 132 10 3.10. Predicting Closing Odds (Sbobet) from Early Odds (Ladbrokes & Sbobet) 133 3.11. Predicting Closing Odds (Ladbrokes) from Early Odds (Ladbrokes) 134 3.12. Predicting results from Odds (Ladbrokes & Sbobet) 136 4.1. Liquidity, Sbobet v Betfair 160 4.2. Gross Returns by Betting Offer 164 4.3. Example of an "Risk-Free" Portfolio 167 4.4. Correlation between Bookmakers' odds 174 4.5. Arbitrage by League 176 4.6. Arbitrage by Bookmaker 176 4.7. The Arbitrage Portfolios Analysed 179 4.8. Football Outcomes Predictions Based on Odds (Multiple Bookmakers) 183 Figure 3.1. Screenshot of SBOBet’s trading window 110 3.2. Odds Trends: Sunderland v Stoke, 6/5/2013 120 3.3. Odds Trends: Dortmund v Freiburg, 16/3/2013 121 3.4. Odds Trends: Tottenham v Everton, 7/4/2013 121 3.5. Odds Trends: Fiorentina v Inter, 17/2/2013 122 11 Declaration of Authorship This PhD thesis is the result of work conducted wholly or mainly by Anastasios Oikonomidis whilst in registered candidature. None of the material presented has been submitted for another degree. Minor aspects of the thesis have been developed from work conducted jointly with other persons who have assisted in supervisory or advisory roles.