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Efficiency of online football betting markets

Citations

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Cited by:

  1. Dagaev, Dmitry & Stoyan, Egor, 2020. "Parimutuel betting on the eSports duels: Evidence of the reverse favourite-longshot bias," Journal of Economic Psychology, Elsevier, vol. 81(C).
  2. Raphael Flepp & Oliver Merz & Egon Franck, 2024. "When the league table lies: Does outcome bias lead to informationally inefficient markets?," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 414-429, January.
  3. J Reade & C Singleton & L Vaughan Williams, 2020. "Betting Markets for English Premier League Results and Scorelines: Evaluating a Simple Forecasting Model," Economic Issues Journal Articles, Economic Issues, vol. 25(1), pages 87-106, March.
  4. Luca De Angelis & J. James Reade, 2022. "Home advantage and mispricing in indoor sports’ ghost games: the case of European basketball," Economics Discussion Papers em-dp2022-01, Department of Economics, University of Reading.
  5. Oliver Merz & Raphael Flepp & Egon Franck, 2021. "Underestimating randomness: Outcome bias in betting exchange markets," Working Papers 390, University of Zurich, Department of Business Administration (IBW).
  6. Whelan, Karl & Hegarty, Tadgh, 2023. "Forecasting Soccer Matches With Betting Odds: A Tale of Two Markets," MPRA Paper 116925, University Library of Munich, Germany.
  7. Hegarty, Tadgh & Whelan, Karl, 2023. "Do Gamblers Understand Complex Bets? Evidence From Asian Handicap Betting on Soccer," MPRA Paper 117244, University Library of Munich, Germany.
  8. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  9. Kai Fischer & Justus Haucap, 2020. "Betting Market Efficiency in the Presence of Unfamiliar Shocks: The Case of Ghost Games during the Covid-19 Pandemic," CESifo Working Paper Series 8526, CESifo.
  10. J. James Reade & Carl Singleton & Alasdair Brown, 2021. "Evaluating strange forecasts: The curious case of football match scorelines," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(2), pages 261-285, May.
  11. Merz, Oliver & Flepp, Raphael & Franck, Egon, 2021. "Sonic Thunder vs. Brian the Snail: Are people affected by uninformative racehorse names?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 93(C).
  12. Guy Elaad, 2020. "Home-field advantage and biased prediction markets in English soccer," Applied Economics Letters, Taylor & Francis Journals, vol. 27(14), pages 1170-1174, July.
  13. Kai Fischer & Justus Haucap, 2022. "Home advantage in professional soccer and betting market efficiency: The role of spectator crowds," Kyklos, Wiley Blackwell, vol. 75(2), pages 294-316, May.
  14. David Winkelmann & Christian Deutscher & Marius Ötting, 2021. "Bookmakers’ mispricing of the disappeared home advantage in the German Bundesliga after the COVID-19 break," Applied Economics, Taylor & Francis Journals, vol. 53(26), pages 3054-3064, June.
  15. Elaad, Guy & Reade, J. James & Singleton, Carl, 2020. "Information, prices and efficiency in an online betting market," Finance Research Letters, Elsevier, vol. 35(C).
  16. Dmitry Dagaev & Egor Stoyan, 2019. "Parimutuel Betting On The Esports Duels: Reverse Favourite-Longshot Bias And Its Determinants," HSE Working papers WP BRP 216/EC/2019, National Research University Higher School of Economics.
  17. Angelini, Giovanni & De Angelis, Luca & Singleton, Carl, 2022. "Informational efficiency and behaviour within in-play prediction markets," International Journal of Forecasting, Elsevier, vol. 38(1), pages 282-299.
  18. Marius Otting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2022. "Gambling on Momentum," Papers 2211.06052, arXiv.org.
  19. Marius Ötting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2023. "Gambling on Momentum in Contests," Economics Discussion Papers em-dp2023-08, Department of Economics, University of Reading.
  20. Saidjon Shiralievich Tavarov & Alexander Sidorov & Zsolt Čonka & Murodbek Safaraliev & Pavel Matrenin & Mihail Senyuk & Svetlana Beryozkina & Inga Zicmane, 2023. "Control of Operational Modes of an Urban Distribution Grid under Conditions of Uncertainty," Energies, MDPI, vol. 16(8), pages 1-18, April.
  21. He, Xue-Zhong & Treich, Nicolas, 2017. "Prediction market prices under risk aversion and heterogeneous beliefs," Journal of Mathematical Economics, Elsevier, vol. 70(C), pages 105-114.
  22. Pascal Flurin Meier & Raphael Flepp & Egon Franck, 2021. "Are sports betting markets semistrong efficient? Evidence from the COVID-19 pandemic," Working Papers 387, University of Zurich, Department of Business Administration (IBW).
  23. Goto, Shingo & Yamada, Toru, 2023. "What drives biased odds in sports betting markets: Bettors’ irrationality and the role of bookmakers," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 252-270.
  24. David Winkelmann & Marius Ötting & Christian Deutscher & Tomasz Makarewicz, 2024. "Are Betting Markets Inefficient? Evidence From Simulations and Real Data," Journal of Sports Economics, , vol. 25(1), pages 54-97, January.
  25. da Costa, Igor Barbosa & Marinho, Leandro Balby & Pires, Carlos Eduardo Santos, 2022. "Forecasting football results and exploiting betting markets: The case of “both teams to score”," International Journal of Forecasting, Elsevier, vol. 38(3), pages 895-909.
  26. Marc Garnica-Caparrós & Daniel Memmert & Fabian Wunderlich, 2022. "Artificial data in sports forecasting: a simulation framework for analysing predictive models in sports," Information Systems and e-Business Management, Springer, vol. 20(3), pages 551-580, September.
  27. Wunderlich, Fabian & Memmert, Daniel, 2020. "Are betting returns a useful measure of accuracy in (sports) forecasting?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 713-722.
  28. Ramirez, Philip & Reade, J. James & Singleton, Carl, 2023. "Betting on a buzz: Mispricing and inefficiency in online sportsbooks," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1413-1423.
  29. Ruud H. Koning & Renske Zijm, 2023. "Betting market efficiency and prediction in binary choice models," Annals of Operations Research, Springer, vol. 325(1), pages 135-148, June.
  30. Vaughan Williams Leighton & Liu Chunping & Dixon Lerato & Gerrard Hannah, 2021. "How well do Elo-based ratings predict professional tennis matches?," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(2), pages 91-105, June.
  31. Tadgh Hegarty, 2021. "Information and price efficiency in the absence of home crowd advantage," Applied Economics Letters, Taylor & Francis Journals, vol. 28(21), pages 1902-1907, December.
  32. Salvatore Caruso & Giuseppe Pernagallo, 2021. "On the efficiency of online soccer betting markets: a new methodology based on symbolic series," Economics Bulletin, AccessEcon, vol. 41(3), pages 1451-1460.
  33. Fry, John & Serbera, Jean-Philippe & Wilson, Rob, 2021. "Managing performance expectations in association football," Journal of Business Research, Elsevier, vol. 135(C), pages 445-453.
  34. Luca De Angelis & J. James Reade, 2023. "Home advantage and mispricing in indoor sports’ ghost games: the case of European basketball," Annals of Operations Research, Springer, vol. 325(1), pages 391-418, June.
  35. Whelan, Karl & Hegarty, Tadgh, 2023. "Disagreement and Market Structure in Betting Markets: Theory and Evidence from European Soccer," CEPR Discussion Papers 18144, C.E.P.R. Discussion Papers.
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