Evidential probability of signals on a price herd predictions: Case study on solar energy companies

被引:9
|
作者
Ko, Yu-Chien [1 ]
Fujita, Hamido [2 ]
机构
[1] Chung Hua Univ, Dept Informat Management, Hsinchu 30012, Taiwan
[2] Iwate Prefectural Univ, Software & Informat Sci, Takizawa 0200693, Japan
关键词
Price herd (PH); Signal probability; Information cascade (BHW); Dominance-based rough set approach (DRSA); Rough set theory (RST); FINANCIAL-MARKETS; PATTERN-CLASSIFICATION; CONTRARIAN BEHAVIOR; DECISION-MAKING; INVESTMENT; UNCERTAINTY; CASCADES; FASHION; MODEL;
D O I
10.1016/j.ijar.2017.10.015
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (C) 2017 Elsevier Inc. All rights reserved.
引用
收藏
页码:255 / 269
页数:15
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