著者

北 栄輔 原田 昌朗 山内 真 丸田 峻也

出版者

一般社団法人日本機械学会

雑誌

設計工学・システム部門講演会講演論文集 (ISSN:13480286)

巻号頁・発行日

vol.2014, no.24, pp."1405-1"-"1405-5", 2014-09-17

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Bayesian network is the is one of the probabilistic graphical models that represents a set of random variables and their conditional dependencies via a directed acyclic graph. In this study, Bayesian network is applied for the stock price forecast. The present method classifies stock price into three situations; normal value, positive and negative outliers. Different networks are defined by data in three situations in order to forecast the stock price. The effectiveness of the present method is discussed in the numerical example.