預測市場的研究近年來在學界逐漸受到重視，因為它利用價格具有訊息加總的功能，每每創造出良好的預測績效，但一個預測市場的建立在諸多原因下，通常不易吸引大規模的參與者，例如為免觸犯法令規定，以虛擬貨幣代替真錢進行交易，在缺乏真實貨幣的獲利誘因下，很難有效吸引參與者，即便真能以真實貨幣交易，若實驗的議題並非一般大眾感興趣的話題也不易吸引多數人參與，在這種情況下無法避免要面臨市場交易過於淺薄的問題，雖然不少文獻標榜淺薄市場不會影響預測市場的預測精準度，但並不表這是一個可以置之不理的問題。
本文以預測市場預測2006年北高市長選舉為實證基礎，闡明淺薄市場對價格產生的影響，以及這些影響將導致對未來事件的錯誤評價與推論，要避免這種錯誤的評價與推論唯有設法消除淺薄市場引發的干擾，因此我們提出了五種可以消除這些干擾的方法並從中選擇一較佳者。如同一般文獻的讚揚，我們再次從預測市場獲得精確的預測效果，同時證明所謂淺薄市場不影響預測市場的預測精準度前提乃在消除淺薄市場對價格產生的干擾之後才能還原這個真相。

中文部分：
[1] 呂奇傑、李天行與劉柏君 (2006)，「應用小波轉換與倒傳遞類神經網路於股價指數之預測」，第四屆跨領域管理學術與實務研討會：東海大學。
[2] 鄧肯．華茲著，傅士哲與謝良瑜譯 (2004)，《六個人的小世界》，大塊文化。
[3] 謝宜良 (2006)，「以小波轉換為基礎之風險值估計」，銘傳大學財務金融所碩士論文。

英文部分：
[1] Antoniou, A. and Ergul, N. (1997), “Market Efficiency, Thin Trading and Non-linear Behaviour: Evidence from an Emerging Market,” European Financial Management, Vol. 3, 175-190.
[2] Barabasi, A. -L. (2005), “The Origin of Bursts and Heavy Tails in Human Dynamics,” Nature, Vol. 435, 207-211.
[3] Berg, J., Forsythe, R., Nelson, F., and Rietz, T. (2000), “Results from a Dozen Year of Election Futures Markets Research,” Technical Report, University of Iowa.
[4] Berg, J., Forsythe, R., and Rietz, T. (1997), “What Makes Markets Predict Well? Evidence from the Iowa Electronic Markets,” Understanding Strategic Interaction: Essays in Honor of Reinhard Selten, Springer, New York, .444-463.
[5] Berg, J., Nelson, F., and Rietz, T. (2003), “Accuracy and Forecast Standard Error of Prediction Markets,” working draft.
[6] Bossaerts, P., and Plott, C. (2002), “The CAPM in Thin Experimental Financial Markets,” Journal of Economic Dynamics and Control, Vol. 26, 1093-1112.
[7] Bouchaud, J.-P. (2001), “Power-laws in Economy and Finance: Some Ideas from Physics,” Quantitative Finance, Vol. 1, 105–112.
[8] Chen, K.-Y., and Plott, C. R. (2002), “Information Aggregation Mechanisms: Concept, Design and Implementation for a Sales Forecasting Problem,” working paper.
[9] Chen, S.-H., and Yeh, C.-H. (2002), “On the Emergent Properties of Artificial Stock Markets: the Efficient Market Hypothesis and the Rational Expectations Hypothesis,” Journal of Economic Behavior and Organization, Vol. 49, 217-239.
[10] Dimson, E., and Mussavian, M. (1998), “a Brief History of Market Efficiency,” European Financial Management, Vol. 4, 91-103.
[11] Engle, R. F., and Russell, J. R. (1998), “Autoregressive Conditional Duration: a New Model for Irregularly Spaced Transaction Data,” Econometrica, Vol. 66, 1127-1162.
[12] Fama, E. F. (1970), “Efficient Capital Markets: A Review of Theory and Empirical Work,” The Journal of Finance, Vol. 25, 383-417.
[13] Forsythe, R., Nelson, F., Neumann, G. R., and Wright, J. (1992), “Anatomy of an Experimental Political Stock Market,” The American Economic Review, Vol. 82, 1142-1161.
[14] Forsythe, R., Rietz, T. A., and Ross, T. W. (1999), “Whishes, Espectations and Actions: A Survey on Price Formation in Election Stock Markets,” Journal of Economic Behavior and organization, Vol. 39, 83-110.
[15] Fung, J. K. W., Mok, H. M. K., and Wong, K. C. K. (2004), “Pricing Efficiency in a Thin Market with Competitive Market Makers: Box Spread Strategies in the Hang Seng Index Options Market,” The Financial Review, Vol. 39, 435-454.
[16] Gabaix, X., Gopikrishnan, P., Plerou, V., and Stanley, H. E. (2003), “A Theory of Power-law Distributions in Financial Market Fluctuations,” Nature, Vol. 423, 267-270.
[17] Gencay, R., Selcuk, F., and Whitcher, B. (2002), An Introduction to Wavelets and other Filtering Methods in Finance and Economics, Academic Press.
[18] Gontis, V., (2002), “Multiplicative Stochastic Model of the Time Interval between Trades in Financial Markets,” Nonlinear Analysis: Modelling and Control, Vol. 7, 43-54.
[19] Hanson, R. (2003), “Combinatorial Information Market Design,” Information System Frontiers, Vol. 5, 107-119.
[20] Hanson, R., and Opera, R. (2007), “Manipulators Increase Information Market Accuracy,” Review of Economics and Statistics, under review.
[21] Hanson, R., Oprea, R., and Porter, D. (2006), “Information aggregation and Manipulation in an Experimental Market,” Journal of Economic Behavior and Organization, Vol. 60, 449-459.
[22] Hayek, F. A. (1945), “The Use of Knowledge in Society,” American Economic Review, Vol.35, 519-530.
[23] Hidalgo R., C. A. (2006), “Conditions for the Emergence of Scaling in the Inter-event Time of Uncorrelated and Seasonal Systems,” Physica A, Vol. 369, 877-883.
[24] Huber, J., and Hauser, F. (2005), “Systematic Mispricing in Experimental Markets – Evidence from Political Stock Markets,” Proceedings of International Conference on Finance, Kopenhagen, Denmark (2005), 2-4 September.
[25] LeBaron, B., Arthur, W. B., and Palmer, R. (1999), “Time Series Properties of an Artificial Stock Market,” Journal of Economic Dynamics and Control, 23, 1487-1516.
[26] Manski, C. F. (2005), “Interpreting the Predictions of Prediction Markets,” Economic Letters forthcoming.
[27] Mantegna, R. N., and Stanley, H. E. (2000), An Introduction to Econophysics, Cambridge University Press.
[28] Miller, M. H., Muthuswamy, J., and Whaley, R. E. (1994), “Mean Reversion of Standard and Poor’s 500 Index Basis Changes: Arbitrage-induced or Statistical Illusion?” The Journal of Finance, Vol. 49, 479-513.
[29] Muth, J. F. (1961), “Rational Expectations and The Theory of Price Movements,” Econometrica, Vol. 29, 315-335.
[30] Nelson, R. G., and Turner S. C. (1995), “Experimental Examination of a Thin Market: Price Behavior in a Declining Terminal Market Revisited,” Journal of Agricultural and Applied Economics, Vol. 27, 149-160.
[30] Newman, M. E. J. (2005), “Power law, Pareto distributions and Zipf’s law,” Contemporary Physics, Vol. 46, 323-351.
[31] Pagon, A. (2005), “Polls and Markets in the 2004 Presidential Election: A Risk Premium to Explain Deviations between Polling Predictions and Market Prices,” Stanford University Department of Economics Honor Theses 2005.
[32] Plott, C. R. (2000), “Markets as Information Gathering Tools,” Southern Economic Journal, Vol. 67, 1-15.
[33] Servan-Schreiber, E., Wolfers, J., Pennock, D. M., and Galebach, B. (2004), “Prediction Market: Does Money Matter?” Electronic Markets, Vol. 14, 243-251.
[34] Silber, W. L. (1975), “Thinness in Capital Markets: the Case of the Tel Aviv Stock Exchange,” Journal of Financial and Quantitative Analysis, Vol. 10, 129-142.
[35] Vazquez, A., Oliveira, J. G., Dezso, Z., Goh, K.-I., Kondor, I., and Barabasi, A.-L. (2006), “Modeling Bursts and Heavy Tails in Human Dynamics,” Physical Review E, Vol. 73, 036127.
[36] Wang, S.-C., Li, S.-P., Tai, C.-C., Chen, S.-H. (2006), “Statistical Properties of an Experimental Political Futures Market,” Quantitative Finance forthcoming.
[37] Wang, S.-C., Liu, K.-P., Yu, C.-Y., and Li, S.-P. (2004), “A Web-based Political Exchange for Election Outcome Predictions,” IEEE/WIC/ACM International Conference on Web Intelligence (WI'04), 173-178.
[38] Wang, S.-C., Tseng, J.-J., Li, S.-P., Chen, S.-H. (2006), “Prediction of Bird Flu (H5N1) Outbreaks in Taiwan by Online Auction: Experimental Result,” New Mathematics and Natural Computation, Vol. 2, 271-279.
[39] Wolfers, J., and Zitzewitz, E. (2004), “Prediction Markets,” The Journal of Economic Perspectives, 18, 2, 107-126.
[40] Wolfers, J., and Zitzewitz, E. (2006), “Prediction Markets in Theory and Practice,” NBER working paper.
[41] Wolfers, J., and Zitzewitz, E. (2006), “Five Open Questions about Prediction Markets,” NBER working paper.