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政大典藏 > College of Social Science > Graduate Institute of Development Studies > Periodical Articles > Item 140.119/64890

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/64890

Title:	Multivariate Methods in Assessing the Accuracy of the Highest-price Criterion on Prediction Markets
Authors:	Tung, Chen-yuan;Yeh, Jason;Lin, Hung-Wen 童振源
Contributors:	國發所
Keywords:	degree of market consensus;discriminant analysis;Exchange of Future Events;PCA-DA model;prediction markets;Principal component analysis
Date:	2013.12
Issue Date:	2014-03-24 17:47:15 (UTC+8)
Abstract:	This study successfully establishes the principal component analysis with discriminant analysis (PCA-DA) model to assess the accuracy of contracts in the prediction markets ex ante based on the highest-price criterion. Trained by the xFuture data (7,274 contracts of future events) from 2006-2011, the PCA-DA model shows learning effects and provides 97.72% confidence to predict the outcome of any contract discriminated to the correct prediction group in the Exchange of Future Events. However, we need to greatly improve the low confidence of 19.58% for the PCA-DA model to predict the result of any contract discriminated to the incorrect prediction group. [ABSTRACT FROM AUTHOR]
Relation:	THE JOURNAL OF PREDICTION MARKETS,7(3), 31-46
Data Type:	article
Appears in Collections:	[Graduate Institute of Development Studies] Periodical Articles

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