Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/64890
DC Field | Value | Language |
---|---|---|
dc.contributor | 國發所 | en_US |
dc.creator | Tung, Chen-yuan ;Yeh, Jason ;Lin, Hung-Wen | en_US |
dc.creator | 童振源 | zh_TW |
dc.date | 2013.12 | en_US |
dc.date.accessioned | 2014-03-24T09:47:15Z | - |
dc.date.available | 2014-03-24T09:47:15Z | - |
dc.date.issued | 2014-03-24T09:47:15Z | - |
dc.identifier.uri | http://nccur.lib.nccu.edu.tw/handle/140.119/64890 | - |
dc.description.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] | en_US |
dc.format.extent | 806394 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en_US | - |
dc.relation | THE JOURNAL OF PREDICTION MARKETS,7(3), 31-46 | en_US |
dc.subject | degree of market consensus ; discriminant analysis ; Exchange of Future Events ; PCA-DA model ; prediction markets ; Principal component analysis | en_US |
dc.title | Multivariate Methods in Assessing the Accuracy of the Highest-price Criterion on Prediction Markets | en_US |
dc.type | article | en |
item.fulltext | With Fulltext | - |
item.grantfulltext | restricted | - |
item.languageiso639-1 | en_US | - |
item.openairetype | article | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
Appears in Collections: | 期刊論文 |
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