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

 

柯宇謙,Hamido Fujita

Information Management

eugene@chu.edu.tw

 

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.

Keyword: price herd (PH), signal probability, information cascade (BHW), dominance-based rough set approach (DRSA), rough set theory (RST)

 

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