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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/87237

    Title: 論市場計分法在預測市場的準確性 : 以臺灣總統大選為例
    Other Titles: Accuracy of prediction market with market scoring rule : a case study of Taiwan presidential election
    Authors: 吳慧品;Wu, Hui-Pin
    Contributors: 淡江大學產業經濟學系碩士班
    池秉聰;Chie, Bin-Tzong
    Keywords: 預測市場;雙方喊價市場;市場計分法;總統大選;群聚效果;反執政黨效果;Prediction Market;Double Auction;Market Scoring Rule;Presidential election;Cluster Effect;Anti-Ruling Party Effect
    Date: 2012
    Issue Date: 2013-04-13 10:52:39 (UTC+8)
    Abstract:   過去預測市場的交易機制大多都是利用雙方喊價市場進行交易,本文採用 Hanson (2003) 提出的預測方法—市場計分法來進行預測,實驗背景為2012年與2008年的臺灣總統大選,並參考真實世界的預測市場—臺灣的「未來事件交易所」中,各縣市對於總統候選人得票率預測合約的資訊,再加入族群的群聚效果以及反執政黨效果作為參數,最後設計實驗在不同的群聚效果之下,比較模擬市場計分法的預測結果,與預測市場中利用雙方喊價市場機制的預測結果之差異。
      Instead of using double auction market mechanism, we apply market scoring rule (MSR) to overcome potential liquidity problem (Hanson, 2003). Year 2008 and 2012 Taiwan Presidential Election results have been adopted in agent-based model (ABM). We use ABM to explore the possible belief distributions behind the prediction market in Taiwan, known as xFuture. We assume that the initial belief distribution come from the results of actual vote shares. Then this initial belief distribution will evolve through social networking, controlled by degree of segregation and information radius. In addition, we also add anti-ruling party effect to approximate excess demand of opposition party as evidenced in the trading volume of prediction market. Our goal is to find the best fit setting for the prediction market. We find that under high social consensus, MSR with a higher degree of segregation setting tends to fit xFuture better. In addition, we find that higher degree of segregation settings fit most KMT ruling cities, while lower degree settings tend to fit DPP ruling cities. The results may reflect different society opinion between these two periods.
    Appears in Collections:[產業經濟學系暨研究所] 學位論文

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