Price Interpretability of Prediction Markets: A Convergence Analysis

Published Online:https://doi.org/10.1287/opre.2022.0417

References

  • Abernethy J, Chen Y, Vaughan JW (2013) Efficient market making via convex optimization, and a connection to online learning. ACM Trans. Econom. Comput. 1(2):1–39.CrossrefGoogle Scholar
  • Abernethy JD, Frongillo RM, Li X, Vaughan JW (2014b) A general volume-parameterized market making framework. Proc. 15th ACM Conf. Econom. Comput., 413–430.Google Scholar
  • Abernethy J, Kutty S, Lahaie S, Sami R (2014a) Information aggregation in exponential family markets. Proc. 15th ACM Conf. Econom. Comput., 395–412.Google Scholar
  • Agrawal S, Delage E, Peters M, Wang Z, Ye Y (2011) A unified framework for dynamic prediction market design. Oper. Res. 59(3):550–568.LinkGoogle Scholar
  • Arrow KJ, Forsythe R, Gorham M, Hahn R, Hanson R, Ledyard JO, Levmore S, et al. (2008) The promise of prediction markets. Science 320(5878):877–878.CrossrefGoogle Scholar
  • Atanasov P, Witkowski J, Mellers B, Tetlock P (2022) Crowd prediction systems: Markets, polls, and elite forecasters. Proc. 23rd ACM Conf. Econom. Computat., 1013–1014.Google Scholar
  • Atanasov P, Rescober P, Stone E, Swift SA, Servan-Schreiber E, Tetlock P, Ungar L, et al. (2017) Distilling the wisdom of crowds: Prediction markets vs. prediction polls. Management Sci. 63(3):691–706.LinkGoogle Scholar
  • Aumann RJ (1976) Agreeing to disagree. Ann. Statist. 4(6):1236–1239.CrossrefGoogle Scholar
  • Ban A (2018) Strategy-proof incentives for predictions. Internat. Conf. Web Internet Econom. (Springer, Berlin), 51–65.Google Scholar
  • Barberis NC (2013) Thirty years of prospect theory in economics: A review and assessment. J. Econom. Perspective 27(1):173–196.CrossrefGoogle Scholar
  • Berg JE, Nelson FD, Rietz TA (2008) Prediction market accuracy in the long run. Internat. J. Forecasting 24(2):285–300.CrossrefGoogle Scholar
  • Berg JE, Neumann GR, Rietz TA (2009) Searching for Google’s value: Using prediction markets to forecast market capitalization prior to an initial public offering. Management Sci. 55(3):348–361.LinkGoogle Scholar
  • Bertsekas DP, Nedi A, Ozdaglar AE (2003) Convex Analysis and Optimization (Athena Scientific, Belmont, MA).Google Scholar
  • Birge JR, Chen H, Keskin NB, Ward A (2024) To interfere or not to interfere: Information revelation and price-setting incentives in a multiagent learning environment. Oper. Res. Forthcoming.LinkGoogle Scholar
  • Birge JR, Feng YF, Keskin NB, Schultz A (2021) Dynamic learning and market making in spread betting markets with informed bettors. Oper. Res. 69(6):1446–1476.LinkGoogle Scholar
  • Bonnisseau JM, Nguenamadji O (2013) Discrete Walrasian exchange process. Econom. Theory 52(3):1091–1100.CrossrefGoogle Scholar
  • Bordley RF (1982) A multiplicative formula for aggregating probability assessments. Management Sci. 28(10):1091–1213.Google Scholar
  • Carvalho A (2017) On a participation structure that ensures representative prices in prediction markets. Decision Support Systems 104:13–25.CrossrefGoogle Scholar
  • Chakraborty M, Das S (2015) Market scoring rules act as opinion pools for risk-averse agents. Adv. Neural Inform. Processing Systems 28:2359–2367.Google Scholar
  • Chakravorti T, Singh V, Rajtmajer S, McLaughlin M, Fraleigh R, Griffin C, Kwasnica A, et al. (2023) Artificial prediction markets present a novel opportunity for human-AI collaboration. Ricci A, Yeoh W, Agmon N, An B, eds. Proc. 22nd Internat. Conf. Autonomous Agents Multiagent Systems.Google Scholar
  • Chen Y, Pennock DM (2007) A utility framework for bounded-loss market makers. Proc. 23rd Conf. Uncertainty Artificial Intelligence, 49–56.Google Scholar
  • Chen Y, Vaughan JW (2010) A new understanding of prediction markets via no-regret learning. Proc. 11th ACM Conf. Electronic Commerce (ACM, New York), 189–198.Google Scholar
  • Chen MK, Ingersoll JE Jr, Kaplan EH (2008) Modeling a presidential prediction market. Management Sci. 54(8):1381–1394.LinkGoogle Scholar
  • Chen Y, Chu CH, Mullen T, Pennock DM (2005) Information markets vs. opinion pools: An empirical comparison. Proc. 6th ACM Conf. Electronic Commerce (ACM, NewYork), 58–67.Google Scholar
  • Choo L, Kaplan TR, Zultan R (2022) Manipulation and (mis) trust in prediction markets. Management Sci. 68(9):6716–6732.LinkGoogle Scholar
  • Cogwill B, Zitzewitz E (2015) Corporate prediction markets: Evidence from Google, Ford and Firm x. Rev. Econom. Stud. 82(4):1309–1341.CrossrefGoogle Scholar
  • Cowgill B, Wolfers J, Zitzewitz E (2009) Using prediction markets to track information flows: Evidence from Google. Das S, Ostrovsky M, Pennock D, Szymanksi B, eds. Auctions, Market Mechanisms and Their Applications (Springer, Berlin), 3.CrossrefGoogle Scholar
  • den Boer AV, Keskin NB (2022) Dynamic pricing with demand learning and reference effects. Management Sci. 68(10):7065–7791.Google Scholar
  • Föllmer H, Schied A (2011) Stochastic Finance: An Introduction in Discrete Time (Walter de Gruyter, Berlin).CrossrefGoogle Scholar
  • Freeman R, Pennock DM (2018) An axiomatic view of the parimutuel consensus wagering mechanism. Proc. 17th Internat. Conf. Autonomous Agent MultiAgent Systems (ACM, New York), 1936–1938.Google Scholar
  • Freeman R, Pennock DM, Vaughan JW (2017) The double clinching auction for wagering. Proc. ACM Conf. Econom. Comput. (ACM, New York), 43–60.Google Scholar
  • Frongillo R, Reid MD (2015) Convergence analysis of prediction markets via randomized subspace descent. Adv. Neural Inform. Processing Systems 28:3034–3042.Google Scholar
  • Frongillo R, Chen Y, Kash I (2015) Elicitation for aggregation. Proc. Conf. AAAI Artificial Intelligence 29(1):900–906.Google Scholar
  • Gjerstad S, Hall M (2005) Risk Aversion, Beliefs, and Prediction Market Equilibrium (Economic Science Laboratory, University of Arizona, Tucson, AZ).Google Scholar
  • Hanson R (2003) Combinatorial information market design. Inform. Systems Frontiers 5(1):107–119.CrossrefGoogle Scholar
  • Hanson R (2007) Logarithmic markets scoring rules for modular combinatorial information aggregation. J. Prediction Markets 1(1):3–15.CrossrefGoogle Scholar
  • Healy PJ, Linardi S, Lowery JR, Ledyard JO (2010) Prediction markets: Alternative mechanisms for complex environments with few traders. Management Sci. 56(11):1977–1996.LinkGoogle Scholar
  • Hu J, Storkey A (2014) Multi-period trading prediction markets with connections to machine learning. Proc. Internat. Conf. Machine Learn., 1773–1781.Google Scholar
  • Iyer K, Johari R, Moallemi CC (2014) Information aggregation and allocative efficiency in smooth markets. Management Sci. 60(10):2509–2524.LinkGoogle Scholar
  • Jian L, Sami R (2010) Aggregation and manipulation in prediction markets: Effects of trading mechanism and information distribution. Proc. 11th ACM Conf. Electronic Commerce (ACM, New York), 207–208.Google Scholar
  • Kahneman D, Tversky A (2013) Prospect theory: An analysis of decision under risk. Handbook of the Fundamentals of Financial Decision Making: Part I (World Scientific, Singapore), 99–127.CrossrefGoogle Scholar
  • Makarov D, Schornick AV (2010) A note on wealth effect under CARA utility. Finance Res. Lett. 7(3):170–177.CrossrefGoogle Scholar
  • Manski CF (2006) Interpreting the predictions of prediction markets. Econom. Lett. 91(3):425–429.CrossrefGoogle Scholar
  • Mas-Colell A, Whinston MD, Green JR (1995) Microeconomic Theory, vol. 1 (Oxford University Press, New York).Google Scholar
  • Morris PA (1974) Decision analysis expert use. Management Sci. 20(9):1233–1241.LinkGoogle Scholar
  • Ostrovsky M (2012) Information aggregation in dynamic markets with strategic traders. Econometrica 80(6):2595–2647.CrossrefGoogle Scholar
  • Othman A, Sandholm T (2010) When do markets with simple agents fail? Proc. 9th Internat. Conf. Autonomous Agents Multiagent Systems, vol. 1, 865–872.Google Scholar
  • Othman A, Pennock DM, Reeves DM, Sandholm T (2013) A practical liquidity-sensitive automated market maker. ACM Trans. Econom. Comput. 1(3):1–25.CrossrefGoogle Scholar
  • Pathak D, Rothschild D, Dudik M (2015) A comparison of forecasting methods: Fundamentals, polling, prediction markets, and experts. J. Prediction Markets 9(2):1–31.CrossrefGoogle Scholar
  • Pennock DM (1999) Aggregating Probabilistic Beliefs: Market Mechanisms and Graphical Representations (University of Michigan, Ann Arbor).Google Scholar
  • Sethi R, Vaughan JW (2016) Belief aggregation with automated market makers. Comput. Econom. 48(1):155–178.CrossrefGoogle Scholar
  • Slamka C, Skiera B, Spann M (2013) Prediction market performance and market liquidity: A comparison of automated market makers. IEEE Trans. Engrg. Management 60(1):169–185.CrossrefGoogle Scholar
  • Storkey A, Millin J, Geras K (2012) Isoelastic agents and wealth updates in machine learning markets. Proc. 29th Internat. Conf. Machine Learn., 1019–1026.Google Scholar
  • Tarnaud R (2019) Convergence within binary market scoring rules. Econom. Theory 68(4):1017–1050.CrossrefGoogle Scholar
  • Tversky A, Kahneman D (1992) Advances in prospect theory: Cumulative representation of uncertainty. J. Risk Uncertainty 5(4):297–323.CrossrefGoogle Scholar
  • Wolfers J, Zitzewitz E (2004) Prediction markets. J. Econom. Perspective 18(2):107–126.CrossrefGoogle Scholar
  • Wolfers J, Zitzewitz E (2006) Interpreting prediction market prices as probabilities. Technical report, National Bureau of Economic Research, Cambridge, MA.Google Scholar
  • Yu D, Gao JJ, Wang TY (2022) Betting market equilibrium with heterogeneous beliefs: A prospect theory-based model. Eur. J. Oper. Res. 298:137–151.CrossrefGoogle Scholar
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