Predicting the failures of prediction markets: A procedure of decision making using classification models
學年 109
學期 2
出版（發表）日期 2021-07-01
作品名稱 Predicting the failures of prediction markets: A procedure of decision making using classification models
作品名稱（其他語言）
著者 Chung-Ching Tai; Hung-Wen Lin; Bin-Tzong Chie; Chen-Yuan Tung
單位
出版者
著錄名稱、卷期、頁數 International Journal of Forecasting 35(1), p.297-312
摘要 Prediction markets have been an important source of information for decision makers due to their high ex post accuracies. Nevertheless, recent failures of prediction markets remind us of the importance of ex ante assessments of their prediction accuracy. This paper proposes a systematic procedure for decision makers to acquire prediction models which may be used to predict the correctness of winner-take-all markets. We commence with a set of classification models and generate combined models following various rules. We also create artificial records in the training datasets to overcome the imbalanced data issue in classification problems. These models are then empirically trained and tested with a large dataset to see which may best be used to predict the failures of prediction markets. We find that no model can universally outperform others in terms of different performance measures. Despite this, we clearly demonstrate a result of capable models for decision makers based on different decision goals.
關鍵字 Combining forecasts;Support vector machine;Decision trees;Principal component analysis;Discriminant analysis;Imbalanced data;Oversampling;SMOTE
語言 en_US
ISSN 0169-2070
期刊性質 國外
收錄於 SSCI EconLit NotTSSCI
產學合作
通訊作者
審稿制度 是
國別 USA
公開徵稿
出版型式 ,電子版,紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/116030 )

SDGS 減少不平等,和平正義與有力的制度