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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/52576

Title: Evidential probability of signals on a price herd predictions: Case study on solar energy companies
Authors: Yu-Chien Ko
Hamido Fujita
Contributors: 國立臺灣海洋大學:資訊工程學系
Keywords: Price herd (PH)
Signal probability
Information cascade (BHW)
Dominance-based rough set approach (DRSA)
Rough set theory (RST)
Date: 2018-01
Issue Date: 2019-11-19T01:34:06Z
Publisher: International Journal of Approximate Reasoning
Abstract: Abstract: Many investors fail due to following prices. An imitating herd in the stock market influences not only people's wealth but economic stability. This research proposes a notion of price herd which simulates price behavior and its practice. Based on this concept, a model evidentially solving the signal probabilities of the price herd to predict its behavior is proposed. Empirically, the model is applied in the financial database, available from Taiwan Economic Journal, to analyze the solar energy industry during 2009–2014. In the results, it successfully identifies the herding signal, predicts the price downward 43% (0.99 close to the reality) in 2011, discloses a debtor herd beyond investors, and reveals the rational behavior of the price herd. Its technique centers in the prediction of information cascade, the induction of dominance-based rough set approach, and the approximations and granules of rough set theory.
Relation: 92 pp.255-269
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/52576
Appears in Collections:[資訊工程學系] 期刊論文

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