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Internet-Based Virtual Stock Markets for Business Forecasting

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Author Info

  • Martin Spann

    ()
    (School of Business and Economics, Johann Wolfgang Goethe--University Frankfurt am Main, Mertonstrasse 17, 60054 Frankfurt am Main, Germany)

  • Bernd Skiera

    ()
    (School of Business and Economics, Johann Wolfgang Goethe--University Frankfurt am Main, Mertonstrasse 17, 60054 Frankfurt am Main, Germany)

Abstract

The application of Internet--based virtual stock markets (VSMs) is an additional approach that can be used to predict short-- and medium--term market developments. The basic concept involves bringing a group of participants together via the Internet and allowing them to trade shares of virtual stocks. These stocks represent a bet on the outcome of future market situations, and their value depends on the realization of these market situations. In this process, a VSM elicits and aggregates the assessments of its participants concerning future market developments. The aim of this article is to evaluate the potential use and the different design possibilities as well as the forecast accuracy and performance of VSMs compared to expert predictions for their application to business forecasting. After introducing the basic idea of using VSMs for business forecasting, we discuss the different design possibilities for such VSMs. In three real--world applications, we analyze the feasibility and forecast accuracy of VSMs, compare the performance of VSMs to expert predictions, and propose a new validity test for VSM forecasts. Finally, we draw conclusions and provide suggestions for future research.

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File URL: http://dx.doi.org/10.1287/mnsc.49.10.1310.17314
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Bibliographic Info

Article provided by INFORMS in its journal Management Science.

Volume (Year): 49 (2003)
Issue (Month): 10 (October)
Pages: 1310-1326

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Handle: RePEc:inm:ormnsc:v:49:y:2003:i:10:p:1310-1326

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Keywords: Internet; Forecasting; Virtual Stock Market; Design of Virtual Stock Markets; Movies; Virtual Markets;

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Cited by:
  1. Eliashberg, J. & Hegie, Q. & Ho, J. & Huisman, D. & Miller, S.J. & Swami, S. & Weinberg, C.B. & Wierenga, B., 2007. "Demand-driven scheduling of movies in a multiplex," Econometric Institute Research Papers EI 2007-17, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  2. Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," NBER Working Papers 10504, National Bureau of Economic Research, Inc.
  3. Egon Franck & Erwin Verbeek & Stephan Nüesch, 2008. "Prediction Accuracy of Different Market Structures – Bookmakers versus a Betting Exchange," Working Papers 0096, University of Zurich, Institute for Strategy and Business Economics (ISU), revised 2009.
  4. David V. Budescu & Boris Maciejovsky, 2004. "The Effect of Monetary Feedback and Information Spillovers on Cognitive Errors: Evidence from Competitive Markets," Papers on Strategic Interaction 2004-32, Max Planck Institute of Economics, Strategic Interaction Group.
  5. Robin Hanson, 2006. "Designing real terrorism futures," Public Choice, Springer, vol. 128(1), pages 257-274, July.
  6. Edoardo Gaffeo, 2013. "Using information markets in grantmaking. An assessment of the issues involved and an application to Italian banking foundations," DEM Discussion Papers 2013/08, Department of Economics and Management.
  7. van Bruggen, G.H. & Spann, M. & Lilien, G.L. & Skiera, B., 2006. "Institutional Forecasting: The Performance of Thin Virtual Stock Markets," ERIM Report Series Research in Management ERS-2006-028-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  8. Yiling Chen & Mike Ruberry & Jennifer Wortman Vaughan, 2012. "Designing Informative Securities," Papers 1210.4837, arXiv.org.
  9. Gerda Gemser & Mark Leenders & Charles Weinberg, 2012. "More effective assessment of market performance in later stages of the product development process: The case of the motion picture industry," Marketing Letters, Springer, vol. 23(4), pages 1019-1031, December.
  10. McKenzie, Jordi, 2013. "Predicting box office with and without markets: Do internet users know anything?," Information Economics and Policy, Elsevier, vol. 25(2), pages 70-80.
  11. Detlef Schoder & Johannes Putzke & Panagiotis Metaxas & Peter Gloor & Kai Fischbach, 2014. "Information Systems for “Wicked Problems”," Business & Information Systems Engineering, Springer, vol. 6(1), pages 3-10, February.
  12. Elberse, Anita & Anand, Bharat, 2007. "The effectiveness of pre-release advertising for motion pictures: An empirical investigation using a simulated market," Information Economics and Policy, Elsevier, vol. 19(3-4), pages 319-343, October.
  13. Bhargava, Hemant K. & Sun, Daewon, 2008. "Pricing under quality of service uncertainty: Market segmentation via statistical QoS guarantees," European Journal of Operational Research, Elsevier, vol. 191(3), pages 1189-1204, December.
  14. Jennifer Brown & Dylan B. Minor, 2011. "Selecting the Best? Spillover and Shadows in Elimination Tournaments," NBER Working Papers 17639, National Bureau of Economic Research, Inc.

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