Multivariate Methods in Assessing the Accuracy of Prediction Markets Ex Ante based on ohe Highest-Price Criterion

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Published: Jan 8, 2014
DOI: https://doi.org/10.5750/jpm.v7i3.752
Keywords:
Principal component analysis discriminant analysis PCA-DA model prediction markets Exchange of Future Events degree of market consensus

Main Article Content

Hung-Wen Lin
National Taiwan University
Chen-yuan Tung
Graduate Institute of Development Studies, National Chengchi University
Jason Yeh
The Chinese University of Hong Kong

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.

Article Details

Issue
Vol. 7 No. 3 (2013)
Section
Articles
Author Biographies

Hung-Wen Lin, National Taiwan University

Ph.D. student, Department of International Business, National Taiwan University

Chen-yuan Tung, Graduate Institute of Development Studies, National Chengchi University

Chen-yuan Tung , Ph.D. Professor Graduate Institute of Development Studies National Chengchi University Add: 64, Zhi-Nan Road, Sec. 2, Wenshan, Taipei, 11605, TAIWAN (O)Tel: 886-2-2938-7286 Fax: 886-2-2234-0056 E-mail: ctung@nccu.edu.tw

Jason Yeh, The Chinese University of Hong Kong

Associate Professor, Department of Finance, The Chinese University of Hong Kong

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