政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/54812

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/54812

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Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/54812

Title:	整體經驗模態分解在台灣期貨市場與選舉預測市場的應用 Applications of ensemble empirical mode decomposition to future and election prediction markets in Taiwan
Authors:	鄭緯暄
Contributors:	王信實鄭緯暄
Keywords:	本質模態函數預測市場價格發現整體經驗模態分解濾波雜訊 IMF Prediction Market Price Discovery EEMD Filter Noise
Date:	2011
Issue Date:	2012-10-30 11:47:57 (UTC+8)
Abstract:	金融市場常常受到政治、經濟與社會環境等因素所影響，所得到價格為眾多變數交互作用的結果，包含了許多雜訊。本文引進一套數據處理方法「整體經驗模態分解」(Ensemble Empirical Mode Decomposition，EEMD)來分析「期貨市場」以及「預測市場」。第一個實證利用EEMD處理台股期貨，分析對台股指數的解釋能力，並同時與原始台股期貨預測台股指數，比較預測結果；第二個實證利用EEMD來分析預測市場，判別是否能有效的消除雜訊，準確預測選舉結果。第一個實證結果發現，EEMD能有效地過濾期貨市場的雜訊，另外，在最後到期日前十二天或者是前九天，以週期為6.5日經EEMD處理的台股期貨對台股指數的預測較原始台股期貨預測準確；第二個實證結果指出，直接利用EEMD處理預測市場得到的長期趨勢「剩餘訊號」(Residue)來預測選舉並無優於原始預測市場，主因為預測市場參與者不只在乎長期趨勢，亦在乎短期事件的衝擊，故直接利用剩餘訊號預測選舉結果會有所失真，而將剩餘訊號由低頻率之「本質模態函數」(Intrinsic Modes Function，IMF)合併至週期為6日與12日的IMF，得到了EEMD週趨勢價格，分成選前一天和選前十天的資料並與原始預測市場以及民調預測做比較，從不同的準則來看，發現以EEMD週趨勢價格來做選舉預測，準確度較原始預測市場與民調預測的結果更好。根據中選會2012年初選前對選罷法做成的解釋，未來事件交易所在選前十日亦須停止交易，我們可將EEMD運用在日後的選舉預測，把預測市場的合約價格以EEMD處理，應可提高選舉預測的準確度。 The financial markets are usually affected by political, economic and social environment factors, and thus the volatilities of asset prices in these markets are subject to a lot of noises and shocks. To filter out noises and quantify shocks, this paper applies a data processing method, Ensemble Empirical Mode Decomposition (EEMD), and demonstrates its improved prediction to the futures and election prediction markets. While the first empirical application shows that the EEMD effectively filters out the noises in the futures market, the second one indicates that the Taiwanese election prediction using EEMD “residue” is not as accurate as that by original data from the prediction market. The reason why the residue cannot serve as a good predictor is that the market participants consider not only the long-term trend, but also shocks, especially those right before the elections. We then attempt to predict the election outcomes by the week trend series processed by EEMD. The prediction by the week EEMD trend series turns out to be more accurate than that by the poll and original prediction market. Based on this study, we can apply the EEMD to the next election prediction and improve its accuracy.
Reference:	中文部分江鴻鑫、夏榮生（2005）。「標準化互相關應用於經驗模態分解法於之研究」。第三十三屆測量學術發表會論文，頁23-38。吳順德、陳思予、陳虹伯（2009）。「經驗模態分解法之研究趨勢探討與問題分析」。《國立台北科技大學學報》，第42卷，第1期。吳順德、陳思予、陳虹伯（2009）。「經驗模態分解法與小波分解法應用於濾除心電訊號之基準線飄移問題之比較」。2009年資訊技術與產業應用研討會，國立台灣師範大學機電科技學系。周靖秦、陳秀淋（2011）。「利用小波轉換分析美國總體指標與道瓊工業指數之關係」。《經濟論文》，第39卷，第3期，頁339 -367。林建中（2010）。「以經驗模態分解法來分析臺灣股票加權指數與世界經濟大國股票指數之相關性及趨勢研究」。碩士論文，國立台北大學企業管理學系碩士班。施雅菁（2003）。「小型台指期貨價格之研究」。碩士論文，私立淡江大學財務金融研究所。畢德成（2000）。「希伯特頻譜於地震資料之應用」。碩士論文，國立中央大學土木工程學系碩士班。陳振雄（2010）。「應用希爾伯特—黃轉換之訊號濾波研究」，《科學與工程技術期刊》，第6卷，第1期，頁75-84。童振源、周子全、林繼文、林馨怡（2011）。「2009年台灣縣市長選舉預測分析」，《選舉研究》，第18卷，第1期，頁63-94。童振源、周子全、林繼文、林馨怡（2011）。「選舉結果機率之分析—以2006年與2008年台灣選舉為例」，《台灣民主季刊》，第8卷，第3期，頁135-159。童振源、林馨怡、林繼文、黃光雄、周子全、劉嘉凱、趙文志（2009）。「台灣選舉預測—預測市場的運用與實證分析」，《選舉研究》，第16卷，第2期，頁131-66。黃台心（2009）。《計量經濟學》，二版。台北，新陸書局。詹錦宏、蔡建安（2005）。「台指期貨與摩台指期貨價格發現功能之研究」，《管理研究學報》。蔡茹鈴（2008）。「小波轉換與HHT轉換法在金融股價預測之應用」。碩士論文，逢甲大學應用數學系碩士班。謝文良（2002）。「價格發現、資訊傳遞、與市場整合－台股期貨市場之研究」，《財務金融研究季刊》，第十卷，第3期，頁1-31。羅飛雪、戴吾蛟（2010）。「小波分解與EMD在變形監測應用中的比較」，《大地測量與地球動力學》，第30卷，第3期，頁137-141。英文部分 Berg, J., F. Nelson, and T. Rietz (2003). “Accuracy and Forecast Standard Errors of Prediction Markets,” Working paper. Tippie College of Business Administration, University of Iowa. Berg, Joyce, Forrest Nelson, and Thomas Rietz (2008). “Prediction Market Accuracy in the Long Run,” International Journal of Forecasting, Vol.24, No.2, 285–300. Black, F. (1976). “Studies of Stock Market Volatility Changes,” Proceedings of the American Statistical Association, Business and Economic Statistics Section, 177-81. Booth, G.G., R.W. So and Y. Tse, (1999). “Price Discovery in the German Equity Index Derivatives Markets,” The Journal of Futures Markets, Vol.19, No.6, 619-643. Box, G. E., Jenkins, G. M., & Reinsel, G. C. (2008). Time series analysis: Forecasting and control. Hoboken, New Jersey, U.S.A: John Wiley & Sons, Inc. Camerer, Colin (1998). “Can Asset Markets be Manipulated? A Field Experiment with Racetrack Betting,” Journal of Political Economy, Vol.106, No.3, 457-482. Chan, K., Y. P. Chung, and W. M. Fong, (2002). “The Informational Role of Stock and Option Volume,” Review of Financial Studies, Vol.15, No.4, 1049-1075. Chan, K.S., (1992). “A Further Analysis of the Lead-Lag Relationship between the Cash Market and Stock Index Futures Market,” The Review of Financial Studies, Vol.5, No,1, 123-152. Chatrath, A., Christie-David, R., Dhanda, K. K. and Koch, T. W. (2002). “Index Futures Leadership, Basis Behavior and Trader Selectivity,” Journal of Futures Markets, Vol.22, No.7, 649-677. Chen, Y. L., S.Y. Tzang, and, S.H. Ou (2009). “The Study on the EEMD Post Processing Method to Analyze Non-Stationary Wave-Induced Pore Pressures in A Fluidized Bed,” Proceedings of 11th Conference on Underwater Technology, 505-513. Fleming, J. and B. Ostdiek, and R,E. Whaley, (1996). “Trading Costs and the Relative Rate if Price Discovery in Stock Index Futures Markets.” Journal of Futures Markets, Vol.16, No.4, 457-488. Gallegati, M. (2008). “Wavelet Analysis of Stock Returns and Aggregate Economic Activity,” Computational Statistics and Data Analysis, Vol.52, No.6, 3061–3074. Green, Kesten C., J. Scott Armstrong, and Andreas Graefe (2007). “Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared,” Foresight: The International Journal of Applied Forecasting, 8, 17-20. Grossmann A, Morlet J. (1984). “Decomposition of hardy functions into square integrable wavelets of constant shape,” SIAM J Math. Anal., Vol.15, No.4, 723–736. Hasbrouck, J. (1995). “One Security, Many markets: Determining the Contributions to Price Discovery,” Journal of Finance, Vol.50, No.4, 1175-1199. Herbst, A.F., J.P. McCormack, and E.N. West. (1987). “Investigation of a Lead- Lag Relationship between Spot Stock Indices and Their Futures Contracts,” The Journal of Futures Markets, Vol.7, No.3, 373-420. Huang, N.E., M.C. Wu, S.R. Long, S.S.P. Shen, W. Qu, P. Gloersen, K.L. Fan (2003). “A Confidence Limit for the Empirical Mode Decomposition and the Hilbert Spectral Analysis,” Proc. R. Soc. Lond. A 459, 2317-2345. Huang, N.E., Wu, M.L., Qu, W.D., Long, S.R., Shen, S.S.P., (2003). “Applications of Hilbert–Huang Transform to Nonstationary Financial Time Series Analysis,” Applied Stochastic Models in Business and Industry, Vol.19, No.3, 245–268. Huang, N.E., Z. Shen, S.R. Long, M.L. Wu, H.H. Shih, Q. Zheng, N.C. Yen, C.C. Tung, H.H. Liu (1998). “The Empirical Mode Decomposition and Hilbert Spectrum for Nonlinear and Non-stationary Time Series Analysis,” Proc. R. Soc. Lond. A 454, 903-995. Iihara,Y., K. Kato and T. Tokunaga, (1996). “Intraday Return Dynamics between the Cash and the Futures Markets in Japan,” Journal of Futures Markets, Vol.16, No.2, 147-162. Kawaller I.G., P.D. Koch and T.W. Koch, (1987). “The Temporal Price Relationship between S&P500 Futures Stock Markets,” The Journal of Finance, Vol.42, No.5, 1309-1329. Kou, S. G., and Michael E. Sobel (2004). “Forecasting the Vote: A Theoretical Comparison of Election Markets and Public Opinion Polls,” Political Analysis, Vol.12, No.3, 277–295. Lee, D.S. and E. Moretti (2009). “Bayesian Learning and the Pricing of New Information: Evidence from Prediction Markets,” American Economic Review, Vol.99, No.2, 330-336. Mallat S. (1989). “A Theory for Multiresolution Signal Decomposition: the Wavelet Representation,” IEEE Trans Pattern Anal Mach Intell., Vol.11, No.7, 674–693. Min, J. H. and M. Najand (1999). “A Further Investigation of the Lead-Lag Relationship between the Spot Market and Stock Index Futures: Early Evidence from Korea”, Journal of Futures Markets, Vol.19, No.2, 217-232. Ramsey ,J.B. (1999). “The Contribution of Wavelets to the Analysis of Economic and Financial Data, ” Philosophical Transactions of the Royal Society of London A 357, 2593–2606. Rhode, Paul W., and Koleman S. Strumpf. (2007). “Manipulating Political Stock Markets: A Field Experiment and a Century of Observational Data,” University of Pennsylvania. Mimeo. Roope, M., and R. Zurbruegg. (2002). “The Intra-day Price Discovery Process between The Singapore Exchange and Taiwan Futures Exchange,” The Journal of Futures Markets, Vol.22, No.3, 219-240. Rosenbloom, E. S., and William Notz. (2006). “Statistical Tests of Real-Money versus Play-Money Prediction Markets Electronic Markets,” Electronic Markets, Vol.16, No.1, 63-69. Servan-Schreiber, Emile et al. (2004). “Prediction Markets: Does Money Matter?,” Electronic Markets, Vol.14, No.3, 243-251. Snowberg, Erik, Justin Wolfers, and Eric Zitzewitz (2006). “Partisan Impacts on the Stock Market: Evidence from Prediction Markets and the 2004 Election,” University of Pennsylvania. Mimeo. Stoll, H.R. and R.E. Whaley, (1990). “The Dynamics of Stock Index and Stock Index Futures Returns,” Journal of Financial and Quantitative Analysis, Vol.25, No.4, 711-742. Sun, Jingliang and Huanye Sheng (2010). “Applications of Ensemble Empirical Mode Decomposition to Stock-Futures Basis Analysis,” IEEE International Conference on Information and Financial Engineering, 396-399. Tao, Xiong, Yukun Bao, Zhongyi Hu, Rui Zhang, and Jinlong Zhang (2011). “Hybrid Decomposition and Ensemble Framework for Stock Price Forecasting: A Comparative Study,” Advances in Adaptive Data Analysis, Vol.3, No.3, 447–482. Tse, Y., (1999). “Price Discovery and Volatility Spillovers in the DJIA Index and Futures Markets,” Journal of Futures Markets, Vol.19, No.8, 911-930. Tung, Chenyuan, Tzu Chuan Chou, Jih Wen Lin, and Hsin Yi Lin (2011). “Comparing the Forecasting Accuracy of Prediction Markets and Polls for Taiwan`s Presidential and Mayoral Elections,” Journal of Prediction Markets, Vol.5, No.3, 1-26. Wu, Z. and N. E. Huang (2009). “Ensemble Empirical Mode Decomposition: A Noise-assisted Data Analysis Method,” Advances in Adaptive Data Analysis, Vol.1, 1–41. Zhang, X., K.K. Lai, and S.Y. Wang (2008). “A New Approach for Crude Oil Price Analysis Based on Empirical Mode Decomposition,” Energy Economics, Vol.30, No.3, 905-918.
Description:	碩士國立政治大學經濟學系 99258017 100
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0099258017
Data Type:	thesis
Appears in Collections:	[Department of Economics] Theses

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