The forecasting ability of Internet-based virtual futures market

Authors:
An-Sing Chen;Jyun-Cheng Wang;Shu-Ching Yang;David C. Yen
Affiliations:
Department of Finance, National Chung-Cheng University, Chia-yi 621, Taiwan, ROC;Institute of Technology Management, National Tsing-Hua University, 300, Taiwan, ROC;Graduate Institute of Education, National Sun Yat Sen University, Kaohsiung, Taiwan, ROC;Jennifer J. Petters Chair in Asian Business, Department of Decision Sciences and Management Information Systems, Miami University, 305A Upham Hall, Oxford, OH 45056, United States
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

Internet-based virtual futures markets (VFMs) have been used in predicting election results and movie ticket sales. We construct an Internet-based VFM to predict an underlying stock price. While the virtual futures market has received much attention, questions remain as to the ideal number of participants. Results of Granger causality tests and analysis of directional accuracy show that a VFM with only a small number of participants (75) is able to generate informative futures prices useful in the prediction of the underlying stock price. Moreover, the participants were not professional investors but merely undergraduate finance students with only a cursory introduction to futures trading. Our results provide additional evidence supporting the use of VFMs in forecasting and show that VFMs are powerful forecasting tools.