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題名 影響預測準確度之因素與判定預測準確度之模型
The discrimination models of accuracy for prediction markets
作者 林鴻文
貢獻者 童振源<br>Chen-yuan Tung<br>陳樹衡<br>Shu-Heng Chen
林鴻文
關鍵詞 選舉預測市場
鑑別模型
預測準確率
邊際交易者
最適門檻
日期 2013
上傳時間 2-Jan-2014 14:38:25 (UTC+8)
摘要 從過去的研究顯示，預測市場(prediction market)已有良好預測準確率，但該準確率是事後、總體的機率概念，而非更有實際參考價值：事前、個別合約之鑑別預測。故本文先以建構4個選舉預測市場準確度的鑑別模型，在選前針對每一個選舉合約的交易價格進行鑑別，模型的鑑別資訊來自於，預測市場在選前一天提供選舉合約的40個原始自變數。我們的研究顯示：Logit鑑別模型最能在「選前」精準判斷，並可分辨哪些選舉合約的價格，在未來將符合「最高價」準則。本文前半部先以：2008年總統選舉、2009年縣市長選舉及2010年五都市長選舉，做為樣本外測試的樣本，使用原始自變數的Logit模型，其預測力均高於其他3個鑑別模型。Logit模型樣本外的鑑別正確準確率為100％，但是，Logit模型對於鑑別未正確預測組的預測能力仍須改善。最後，本文再使用全部「非選舉」和選舉類別的合約，成功建構預測市場的最適價格門檻，作為判定預測事件是否發生的標準，可將事件發生的機率預測（probabilistic forecasting），轉換成事件發生與否的類別預測（categorical forecasting），作為公共政策與企業決策的重要依據。
參考文獻 I. 中文部分
童振源、林馨怡、林繼文、黃光雄、周子全、劉嘉凱、趙文志（2009）。〈臺灣選舉預測：預測市場的運用與實證分析〉，《選舉研究》，第16卷，第2期，頁131-166。
童振源、周子全、林繼文、林馨怡（2011a）。〈2009 年臺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（2011b）。〈選舉結果機率之分析：以2006年與2008年臺灣選舉為例〉，《臺灣民主季刊》，第8卷，第3期，頁135-159。


II. 外文部分
Agrawal, Shipra, Nimrod Megiddo and Benjamin Armbruster (2010). “Equilibrium in Prediction Markets with Buyers and Sellers.” Economics Letters, Vol. 109, No. 1: 46-49.
Berg, Joyce, Forrest Nelson and Thomas Rietz (2003). Accuracy and Forecast Standard Error of Prediction Markets. Working Paper, Henry B. Tippie College of Business Administration, University of Iowa. Available from: http://www.biz.uiowa.edu/ iem/archive/forecasting.pdf
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.
Berg, Joyce, Robert Forsythe and Thomas Rietz (1997). What Makes Markets Predict Well? Evidence from the Iowa Electronic Markets. in W. Albers, W. Güth, P. Hammerstein, B. Moldovanu and Evan Damme (Eds.), Understanding Strategic Interaction: Essays in Honor of Reinhard Selten, New York: Springer, 444-463.
Blin, Jean-Marie and Andrew B. Whinston (1975). “Discriminant Functions and Majority Voting.” Management Science, Vo. 21, No. 5:557-566.
Brüggelambert, Gregor (2004). “Information and Efficiency in Political Stock Markets: Using Computerized Markets to Predict Election Results.” Applied Economics,Vol. 36, No. 7: 742-768.
Carvalho, M.C.M., M. S. Dougherty, A. S. Fowkers, and M. R. Wardman (1998). “Forecasting Travel Demand: A Comparison of Logit and Artificial Neural Network Methods.” Journal of the Operational Research Society, Vol. 49, No. 7: 717-722.
Chantziara, Thalia and George Skiadopoulos (2008), “Can the Dynamics of Term Structure of Petroleum Futures Be Forecasted? Evidence from Major Markets.” Energy Economics, Vol. 30:962-985.
Christiansen, Jed D. (2007). “Prediction Markets: Practical Experiments in Small Markets and Behaviours Observed.” Journal of Prediction Markets, Vol. 1: 17-41.
Cox, Gary W. (1997). Making votes count: strategic coordination in the world’s electoral systems. New York: Cambridge University Press.
Forsythe, Robert, Forrest Nelson, George R. Neumann and Jack Wright (1992). “Anatomy of An Experimental Political Stock Market.” American Economic Review, Vol. 82, No.5: 1142-1161.
Forsythe, Robert, Thomas Rietz, Thomas Ross (1999). “Wishes, Expectations and Actions: A Survey on Price Formation in Election Stock Markets.” Journal of Economic Behavior and Organization, Vol. 39, No. 1: 83-110.
Gjerstad, Steven (2005). Risk aversion, beliefs, and prediction market equilibrium. Mimeo. From http://www.aeaweb.org/assa/2006/0106_1015_0701.pdf
Gürkaynak, Refet, Justin Wolfers (2005). Macroeconomic Derivatives: An Initial Analysis of Market-Based Macro Forecasts, Uncertainty, and Risk. Working Paper 2005-26, Federal Reserve Bank of San Francisco, http://www.frbsf.org/publications/economics/papers/2005/wp05-26bk.pdf.
Hwang, Dar-Yeh, Chenc F. Lee and K. Thomas Liaw (1997). “Forecasting Bank Failures and Deposit Insurance Premium.” International Review of Economics and Finance, Vol. 6, No. 3: 317-334.
Kessler, Stephan and Bernd Scherer (2011), “Hedge Fund Return Sensitivity to Global Liquidity.” Journal Financial Markets, Vol. 14, No. 2:301-322.
Leigh, Andrew and Justin Wolfers (2006). “Competing Approaches to Forecasting Elections: Economic Models, Opinion Polling and Prediction Markets.” Economic Record, Vol. 82, No. 258: 325-340.
Luckner, Stefan. Christof Weinhardt and Rudi Studer (2006). Predictive Power of Markets: A Comparsion of Two Sports Forecasting Exchanges, in Information Management and Market Engineering, T. Dreier, R. Studer, C. Weinhardt (Eds) Karlsruhe University Press, Karlsruhe, pp. 187-195.
Manski, Charles (2004). Interpreting the predictions of prediction markets. (NBER Working Paper No. 10359, March).
Mitchneck, Beth (1995). “An Assessment of The Growing Local Economic Development Function of Local Authorities in Russia.” Economic Geography, Vol. 71, No. 2:150-170.
Mitra, Devashish, Dimitrios D. Thomakos and Mehmet A. Ulubaşoğlu (2002), “Protection for Sale in A Developing Country: Democracy vs. Dictatorship.” Review of Economics and Statistics, Vol. 84, No. 3:497-508.
Oliven, Kenneth and Thomas Rietz (2004). “Suckers Are Born but Markets Are Made: Individual Rationality, Arbitrage, and Market Efficiency on An Electronic Futures Market.” Management Science, Vol. 50, No. 3: 336-351.
Ortner, Gerhard (1998). “Forecasting Markets—An Industrial Application.” mimeo, Technical University of Vienna.
Ottaviani, Marco and Peter Norman Sørensen (2007). Aggregation of information and beliefs in prediction markets. (Working Paper, available from: http://faculty.london.edu/mottaviani/AIBIPM.pdf)
Pennock, David M., Steve Lawrence, C. Lee Giles and Finn Årup Nielsen (2001). “The Real Power of Artificial Markets.” Science, Vol. 291, No. 5506: 987-988.
Perignon, Christophe, Daniel R. Smith, and Christophe Villa (2007). “Why Common Factors in International Bond Returns Are Not So Common.” Journal International Money and Finance, Vol. 26:284-304.
Servan-Schreiber, Emile, Justin Wolfers, David M. Pennock and Brian Galebach (2004). “Prediction Markets: Does Money Matter?” Electronic Markets, Vol. 14, No. 3: 243-251.
West, Robert Craig (1985). “A Factor-Analytic Approach to Bank Condition.” Journal of Banking and Finance, Vol. 9, No. 2: 253-266.
Wolfers, Justin and Andrew Leigh (2002). “Three Tools for Forecasting Federal Elections Lessons from 2001.” Australian Journal of Political Science, Vol. 37, No. 2: 223-240.
Wolfers, Justin and Eric Zitzewitz (2004). “Prediction Markets.” Journal of Economic Perspectives 18(2): 107-126.
Wolfers, Justin and Eric Zitzewitz. (2006). Interpreting prediction market prices as probabilities. (NBER Working Paper No. 12200, available from: http://www.nber.org/papers/w12200).
描述 博士
國立政治大學
經濟學系
96258504
102
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0962585041
資料類型 thesis
dc.contributor.advisor 童振源<br>Chen-yuan Tung<br>陳樹衡<br>Shu-Heng Chenzh_TW
dc.contributor.author (Authors) 林鴻文zh_TW
dc.creator (作者) 林鴻文zh_TW
dc.date (日期) 2013en_US
dc.date.accessioned 2-Jan-2014 14:38:25 (UTC+8)-
dc.date.available 2-Jan-2014 14:38:25 (UTC+8)-
dc.date.issued (上傳時間) 2-Jan-2014 14:38:25 (UTC+8)-
dc.identifier (Other Identifiers) G0962585041en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/63232-
dc.description (描述) 博士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 經濟學系zh_TW
dc.description (描述) 96258504zh_TW
dc.description (描述) 102zh_TW
dc.description.abstract (摘要) 從過去的研究顯示，預測市場(prediction market)已有良好預測準確率，但該準確率是事後、總體的機率概念，而非更有實際參考價值：事前、個別合約之鑑別預測。故本文先以建構4個選舉預測市場準確度的鑑別模型，在選前針對每一個選舉合約的交易價格進行鑑別，模型的鑑別資訊來自於，預測市場在選前一天提供選舉合約的40個原始自變數。我們的研究顯示：Logit鑑別模型最能在「選前」精準判斷，並可分辨哪些選舉合約的價格，在未來將符合「最高價」準則。本文前半部先以：2008年總統選舉、2009年縣市長選舉及2010年五都市長選舉，做為樣本外測試的樣本，使用原始自變數的Logit模型，其預測力均高於其他3個鑑別模型。Logit模型樣本外的鑑別正確準確率為100％，但是，Logit模型對於鑑別未正確預測組的預測能力仍須改善。最後，本文再使用全部「非選舉」和選舉類別的合約，成功建構預測市場的最適價格門檻，作為判定預測事件是否發生的標準，可將事件發生的機率預測（probabilistic forecasting），轉換成事件發生與否的類別預測（categorical forecasting），作為公共政策與企業決策的重要依據。zh_TW
dc.description.tableofcontents 第一章 前言 1
第二章 研究方法與資料 3
第一節 Logit模型與DA模型 4
第二節 鑑別模型設定與預測說明 5
第三節 合約資料與敘述統計 7
第三章 四個模型之鑑別力測試 10
第一節 Logit鑑別模型 10
第二節 4個鑑別模型之鑑別力比較 16
第四章 樣本外的預測能力 17
第一節 2008年總統大選前夕 18
第二節 2009年縣市長選舉前夕 23
第三節 2010年五都市長選舉前夕 25
第五章 最適價格門檻 27
第一節 緒論 27
第二節 資料描述 28
第三節 認定「最適價格」之程序 32
第四節 實證分析 35
第五節 各類預測事件的最適價門檻準則之實證分析 38
第六節 三種價格門檻準則的樣本外測試與比較 42
第六章 結論 47
參考文獻 50
I. 中文部分 50
II. 外文部分 50
附錄 1 55		zh_TW
dc.format.extent 1503785 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0962585041en_US
dc.subject (關鍵詞) 選舉預測市場zh_TW
dc.subject (關鍵詞) 鑑別模型zh_TW
dc.subject (關鍵詞) 預測準確率zh_TW
dc.subject (關鍵詞) 邊際交易者zh_TW
dc.subject (關鍵詞) 最適門檻zh_TW
dc.title (題名) 影響預測準確度之因素與判定預測準確度之模型zh_TW
dc.title (題名) The discrimination models of accuracy for prediction marketsen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) I. 中文部分
童振源、林馨怡、林繼文、黃光雄、周子全、劉嘉凱、趙文志（2009）。〈臺灣選舉預測：預測市場的運用與實證分析〉，《選舉研究》，第16卷，第2期，頁131-166。
童振源、周子全、林繼文、林馨怡（2011a）。〈2009 年臺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（2011b）。〈選舉結果機率之分析：以2006年與2008年臺灣選舉為例〉，《臺灣民主季刊》，第8卷，第3期，頁135-159。


II. 外文部分
Agrawal, Shipra, Nimrod Megiddo and Benjamin Armbruster (2010). “Equilibrium in Prediction Markets with Buyers and Sellers.” Economics Letters, Vol. 109, No. 1: 46-49.
Berg, Joyce, Forrest Nelson and Thomas Rietz (2003). Accuracy and Forecast Standard Error of Prediction Markets. Working Paper, Henry B. Tippie College of Business Administration, University of Iowa. Available from: http://www.biz.uiowa.edu/ iem/archive/forecasting.pdf
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.
Berg, Joyce, Robert Forsythe and Thomas Rietz (1997). What Makes Markets Predict Well? Evidence from the Iowa Electronic Markets. in W. Albers, W. Güth, P. Hammerstein, B. Moldovanu and Evan Damme (Eds.), Understanding Strategic Interaction: Essays in Honor of Reinhard Selten, New York: Springer, 444-463.
Blin, Jean-Marie and Andrew B. Whinston (1975). “Discriminant Functions and Majority Voting.” Management Science, Vo. 21, No. 5:557-566.
Brüggelambert, Gregor (2004). “Information and Efficiency in Political Stock Markets: Using Computerized Markets to Predict Election Results.” Applied Economics,Vol. 36, No. 7: 742-768.
Carvalho, M.C.M., M. S. Dougherty, A. S. Fowkers, and M. R. Wardman (1998). “Forecasting Travel Demand: A Comparison of Logit and Artificial Neural Network Methods.” Journal of the Operational Research Society, Vol. 49, No. 7: 717-722.
Chantziara, Thalia and George Skiadopoulos (2008), “Can the Dynamics of Term Structure of Petroleum Futures Be Forecasted? Evidence from Major Markets.” Energy Economics, Vol. 30:962-985.
Christiansen, Jed D. (2007). “Prediction Markets: Practical Experiments in Small Markets and Behaviours Observed.” Journal of Prediction Markets, Vol. 1: 17-41.
Cox, Gary W. (1997). Making votes count: strategic coordination in the world’s electoral systems. New York: Cambridge University Press.
Forsythe, Robert, Forrest Nelson, George R. Neumann and Jack Wright (1992). “Anatomy of An Experimental Political Stock Market.” American Economic Review, Vol. 82, No.5: 1142-1161.
Forsythe, Robert, Thomas Rietz, Thomas Ross (1999). “Wishes, Expectations and Actions: A Survey on Price Formation in Election Stock Markets.” Journal of Economic Behavior and Organization, Vol. 39, No. 1: 83-110.
Gjerstad, Steven (2005). Risk aversion, beliefs, and prediction market equilibrium. Mimeo. From http://www.aeaweb.org/assa/2006/0106_1015_0701.pdf
Gürkaynak, Refet, Justin Wolfers (2005). Macroeconomic Derivatives: An Initial Analysis of Market-Based Macro Forecasts, Uncertainty, and Risk. Working Paper 2005-26, Federal Reserve Bank of San Francisco, http://www.frbsf.org/publications/economics/papers/2005/wp05-26bk.pdf.
Hwang, Dar-Yeh, Chenc F. Lee and K. Thomas Liaw (1997). “Forecasting Bank Failures and Deposit Insurance Premium.” International Review of Economics and Finance, Vol. 6, No. 3: 317-334.
Kessler, Stephan and Bernd Scherer (2011), “Hedge Fund Return Sensitivity to Global Liquidity.” Journal Financial Markets, Vol. 14, No. 2:301-322.
Leigh, Andrew and Justin Wolfers (2006). “Competing Approaches to Forecasting Elections: Economic Models, Opinion Polling and Prediction Markets.” Economic Record, Vol. 82, No. 258: 325-340.
Luckner, Stefan. Christof Weinhardt and Rudi Studer (2006). Predictive Power of Markets: A Comparsion of Two Sports Forecasting Exchanges, in Information Management and Market Engineering, T. Dreier, R. Studer, C. Weinhardt (Eds) Karlsruhe University Press, Karlsruhe, pp. 187-195.
Manski, Charles (2004). Interpreting the predictions of prediction markets. (NBER Working Paper No. 10359, March).
Mitchneck, Beth (1995). “An Assessment of The Growing Local Economic Development Function of Local Authorities in Russia.” Economic Geography, Vol. 71, No. 2:150-170.
Mitra, Devashish, Dimitrios D. Thomakos and Mehmet A. Ulubaşoğlu (2002), “Protection for Sale in A Developing Country: Democracy vs. Dictatorship.” Review of Economics and Statistics, Vol. 84, No. 3:497-508.
Oliven, Kenneth and Thomas Rietz (2004). “Suckers Are Born but Markets Are Made: Individual Rationality, Arbitrage, and Market Efficiency on An Electronic Futures Market.” Management Science, Vol. 50, No. 3: 336-351.
Ortner, Gerhard (1998). “Forecasting Markets—An Industrial Application.” mimeo, Technical University of Vienna.
Ottaviani, Marco and Peter Norman Sørensen (2007). Aggregation of information and beliefs in prediction markets. (Working Paper, available from: http://faculty.london.edu/mottaviani/AIBIPM.pdf)
Pennock, David M., Steve Lawrence, C. Lee Giles and Finn Årup Nielsen (2001). “The Real Power of Artificial Markets.” Science, Vol. 291, No. 5506: 987-988.
Perignon, Christophe, Daniel R. Smith, and Christophe Villa (2007). “Why Common Factors in International Bond Returns Are Not So Common.” Journal International Money and Finance, Vol. 26:284-304.
Servan-Schreiber, Emile, Justin Wolfers, David M. Pennock and Brian Galebach (2004). “Prediction Markets: Does Money Matter?” Electronic Markets, Vol. 14, No. 3: 243-251.
West, Robert Craig (1985). “A Factor-Analytic Approach to Bank Condition.” Journal of Banking and Finance, Vol. 9, No. 2: 253-266.
Wolfers, Justin and Andrew Leigh (2002). “Three Tools for Forecasting Federal Elections Lessons from 2001.” Australian Journal of Political Science, Vol. 37, No. 2: 223-240.
Wolfers, Justin and Eric Zitzewitz (2004). “Prediction Markets.” Journal of Economic Perspectives 18(2): 107-126.
Wolfers, Justin and Eric Zitzewitz. (2006). Interpreting prediction market prices as probabilities. (NBER Working Paper No. 12200, available from: http://www.nber.org/papers/w12200).		zh_TW