IDEAS home Printed from https://ideas.repec.org/r/ucp/jpolec/v87y1979i1p75-88.html
   My bibliography  Save this item

Subjective Information and Market Efficiency in a Betting Market

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


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. José Miguel Melo, 2011. "Estratégia Militar e Gestão de Activos: Uma Visão Heurística," Working Papers de Gestão (Management Working Papers) 01, Católica Porto Business School, Universidade Católica Portuguesa.
  3. Smith, Michael A. & Paton, David & Williams, Leighton Vaughan, 2009. "Do bookmakers possess superior skills to bettors in predicting outcomes?," Journal of Economic Behavior & Organization, Elsevier, vol. 71(2), pages 539-549, August.
  4. Peter A. Bebbington & Julius Bonart, 2016. "Order statistics of horse racing and the randomly broken stick," Papers 1612.02567, arXiv.org.
  5. repec:zbw:bofism:2006_035 is not listed on IDEAS
  6. Dash, Saumya Ranjan & Maitra, Debasish, 2019. "The relationship between emerging and developed market sentiment: A wavelet-based time-frequency analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 135-150.
  7. Jakobsson, Robin & Karlsson, Niklas, 2007. "Testing Market Efficiency in a Fixed Odds Betting Market," Working Papers 2007:12, Örebro University, School of Business.
  8. Taipalus, Katja, 2012. "Detecting asset price bubbles with time-series methods," Scientific Monographs, Bank of Finland, number 2012_047.
  9. Bhootra, Ajay & Hur, Jungshik, 2012. "On the relationship between concentration of prospect theory/mental accounting investors, cointegration, and momentum," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1266-1275.
  10. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
  11. Russell Sobel & S. Travis Raines, 2003. "An examination of the empirical derivatives of the favourite-longshot bias in racetrack betting," Applied Economics, Taylor & Francis Journals, vol. 35(4), pages 371-385.
  12. Adi Schnytzer & Yuval Shilony, 2007. "The Optimality and Statistical Detection of Price Rigging in Betting Markets," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 1(1), pages 13-29, February.
  13. repec:zbw:bofism:2012_047 is not listed on IDEAS
  14. William Mallios, 2012. "Forecasting National Football League Game Outcomes Relative to Betting Spreads," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 6(3), pages 1-16, December.
  15. Taipalus, Katja, 2012. "Detecting asset price bubbles with time-series methods," Bank of Finland Scientific Monographs, Bank of Finland, volume 0, number sm2012_047.
  16. Lessmann, Stefan & Sung, Ming-Chien & Johnson, Johnnie E.V., 2009. "Identifying winners of competitive events: A SVM-based classification model for horserace prediction," European Journal of Operational Research, Elsevier, vol. 196(2), pages 569-577, July.
  17. Tim Kuypers, 2000. "Information and efficiency: an empirical study of a fixed odds betting market," Applied Economics, Taylor & Francis Journals, vol. 32(11), pages 1353-1363.
  18. Reitz, Stefan & Taylor, Mark P., 2008. "The coordination channel of foreign exchange intervention: A nonlinear microstructural analysis," European Economic Review, Elsevier, vol. 52(1), pages 55-76, January.
  19. Johnson, Johnnie E. V. & Bruce, Alistair C., 2001. "Calibration of Subjective Probability Judgments in a Naturalistic Setting," Organizational Behavior and Human Decision Processes, Elsevier, vol. 85(2), pages 265-290, July.
  20. Raymond Sauer, 2005. "The state of research on markets for sports betting and suggested future directions," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 29(3), pages 416-426, September.
  21. Bin-Tzong Chie & Chih-Hwa Yang, 2021. "Efficiency of the Experimental Prediction Market: Public Information, Belief Evolution, and Personality Traits," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(4), pages 1-3.
  22. Bruce, Alistair C. & Johnson, Johnnie E.V., 2005. "Market ecology and decision behaviour in state-contingent claims markets," Journal of Economic Behavior & Organization, Elsevier, vol. 56(2), pages 199-217, February.
  23. Stefan Reitz & Mark Taylor, 2012. "FX intervention in the Yen-US dollar market: a coordination channel perspective," International Economics and Economic Policy, Springer, vol. 9(2), pages 111-128, June.
  24. Alessandro Innocenti & Tommaso Nannicini & Roberto Ricciuti, 2021. "The Importance of Betting Early," Risks, MDPI, vol. 9(4), pages 1-15, April.
  25. Zuber, Richard A & Gandar, John M & Bowers, Benny D, 1985. "Beating the Spread: Testing the Efficiency of the Gambling Market for National Football League Games," Journal of Political Economy, University of Chicago Press, vol. 93(4), pages 800-806, August.
  26. Tedeschi, Gabriele & Iori, Giulia & Gallegati, Mauro, 2012. "Herding effects in order driven markets: The rise and fall of gurus," Journal of Economic Behavior & Organization, Elsevier, vol. 81(1), pages 82-96.
  27. Alistair C. Bruce & Johnnie E. V. Johnson & John D. Peirson & Jiejun Yu, 2009. "An Examination of the Determinants of Biased Behaviour in a Market for State Contingent Claims," Economica, London School of Economics and Political Science, vol. 76(302), pages 282-303, April.
  28. Quitzau, Jörn, 2005. "Faktor Zufall als Spielverderber: zur Prognostizierbarkeit von Fußballergebnissen – Wettmärkte als effizienter Informationslieferant," Research Notes 18, Deutsche Bank Research.
  29. Lessmann, Stefan & Sung, Ming-Chien & Johnson, Johnnie E.V., 2010. "Alternative methods of predicting competitive events: An application in horserace betting markets," International Journal of Forecasting, Elsevier, vol. 26(3), pages 518-536, July.
  30. Thomas, Ashok & Spataro, Luca & Mathew, Nanditha, 2014. "Pension funds and stock market volatility: An empirical analysis of OECD countries," Journal of Financial Stability, Elsevier, vol. 11(C), pages 92-103.
  31. S Lessmann & M-C Sung & J E V Johnson, 2011. "Towards a methodology for measuring the true degree of efficiency in a speculative market," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2120-2132, December.
  32. Forrest, David & Simmons, Robert, 2000. "Forecasting sport: the behaviour and performance of football tipsters," International Journal of Forecasting, Elsevier, vol. 16(3), pages 317-331.
  33. M. Sung & J. E. V. Johnson, 2010. "Revealing Weak‐Form Inefficiency in a Market for State Contingent Claims: The Importance of Market Ecology, Modelling Procedures and Investment Strategies," Economica, London School of Economics and Political Science, vol. 77(305), pages 128-147, January.
  34. 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.
  35. Ronald Peeters & Leonard Wolk, 2019. "Elicitation of expectations using Colonel Blotto," Experimental Economics, Springer;Economic Science Association, vol. 22(1), pages 268-288, March.
  36. Christian Walter, 2004. "Volatilité boursière excessive : irrationalité des comportements ou clivage des esprits ?," Revue d'Économie Financière, Programme National Persée, vol. 74(1), pages 85-104.
  37. Butler, David & Butler, Robert & Eakins, John, 2021. "Expert performance and crowd wisdom: Evidence from English Premier League predictions," European Journal of Operational Research, Elsevier, vol. 288(1), pages 170-182.
  38. Viet Hoang Nguyen & Yongcheol Shin, 2011. "Asymmetric Price Impacts of Order Flow on Exchange Rate Dynamics," Melbourne Institute Working Paper Series wp2011n14, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  39. Lessmann, Stefan & Sung, Ming-Chien & Johnson, Johnnie E.V. & Ma, Tiejun, 2012. "A new methodology for generating and combining statistical forecasting models to enhance competitive event prediction," European Journal of Operational Research, Elsevier, vol. 218(1), pages 163-174.
  40. Chau, Frankie & Deesomsak, Rataporn & Koutmos, Dimitrios, 2016. "Does investor sentiment really matter?," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 221-232.
  41. Quitzau, Jörn & Vöpel, Henning, 2009. "Der Faktor Zufall im Fußball: Eine empirische Untersuchung für die Saison 2007/08," HWWI Research Papers 1-22, Hamburg Institute of International Economics (HWWI).
  42. Swidler, Steve & Shaw, Ron, 1995. "Racetrack wagering and the "uninformed" bettor: A study of market efficiency," The Quarterly Review of Economics and Finance, Elsevier, vol. 35(3), pages 305-314.
  43. Michael Cain & David Law & David Peel, 2000. "The Favourite‐Longshot Bias and Market Efficiency in UK Football betting," Scottish Journal of Political Economy, Scottish Economic Society, vol. 47(1), pages 25-36, February.
  44. Hsin, Chin-Wen & Guo, Wen-Chung & Tseng, Seng-Su & Luo, Wen-Chih, 2003. "The impact of speculative trading on stock return volatility: the evidence from Taiwan," Global Finance Journal, Elsevier, vol. 14(3), pages 243-270, December.
  45. Gregory, Richard Paul, 2021. "What determines Manager and Investor Sentiment?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
  46. Sung, Ming-Chien & McDonald, David C.J. & Johnson, Johnnie E.V. & Tai, Chung-Ching & Cheah, Eng-Tuck, 2019. "Improving prediction market forecasts by detecting and correcting possible over-reaction to price movements," European Journal of Operational Research, Elsevier, vol. 272(1), pages 389-405.
  47. Ledyard, John & Hanson, Robin & Ishikida, Takashi, 2009. "An experimental test of combinatorial information markets," Journal of Economic Behavior & Organization, Elsevier, vol. 69(2), pages 182-189, February.
  48. Mukhtar Ali, 1998. "Probability models on horse-race outcomes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(2), pages 221-229.
  49. Alistair Bruce & David Marginson, 2014. "Power, Not Fear: A Collusion-Based Account of Betting Market Inefficiency," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 21(1), pages 77-97, February.
  50. Robin Hanson, 2006. "Designing real terrorism futures," Public Choice, Springer, vol. 128(1), pages 257-274, July.
  51. Blume, Lawrence & Easley, David, 2009. "The market organism: Long-run survival in markets with heterogeneous traders," Journal of Economic Dynamics and Control, Elsevier, vol. 33(5), pages 1023-1035, May.
  52. Grant, Andrew & Johnstone, David & Kwon, Oh Kang, 2019. "The cost of capital in a prediction market," International Journal of Forecasting, Elsevier, vol. 35(1), pages 313-320.
  53. Sperb, Luis Felipe Costa & Sung, Ming-Chien & Johnson, Johnnie E.V. & Ma, Tiejun, 2019. "Keeping a weather eye on prediction markets: The influence of environmental conditions on forecasting accuracy," International Journal of Forecasting, Elsevier, vol. 35(1), pages 321-335.
  54. Woodland, Bill M & Woodland, Linda M, 1991. "The Effects of Risk Aversion on Wagering: Point Spread versus Odds," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 638-653, June.
  55. Michael Cain & David Law & David Peel, 2002. "Is one price enough to value a state-contingent asset correctly? Evidence from a gambling market," Applied Financial Economics, Taylor & Francis Journals, vol. 12(1), pages 33-38.
  56. Taipalus, Katja, 2006. "Bubbles in the Finnish and US equities markets," Scientific Monographs, Bank of Finland, number 35/2006.
  57. Stefan Reitz & M.P Taylor, 2006. "The Coordination Channel of Foreign Exchange Intervention," Computing in Economics and Finance 2006 16, Society for Computational Economics.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.