著者

上山 薫 左 毅 上島 康孝 北 栄輔

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会第二種研究会資料 (ISSN:24365556)

巻号頁・発行日

vol.2010, no.FIN-004, pp.07, 2010-01-23 (Released:2023-01-06)

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In this research, we describe the prediction of the stock price fluctuation by using Bayesian Network. Bayesian Network is trained with stock price fluctuations DJIA30 in New York stock exchange market, FTSE100 in London stock exchange market and NIKKEI225 in Tokyo stock exchange market. Then the network is applied to predict FTSE100 fluctuation. Firstly, FTSE100 fluctuation in 2007 is predicted by technical analysis and Bayesian Network analysis. The results show that the prediction accuracy of Bayesian Network is much better than that of technical analysis. Next, we will discuss the prediction accuracy of the Bayesian Network in 2007 (sub-prime loan problem). The results show that the prediction accuracy decreases not only at the time of the event but at the time of the policy change for the event.

著者

上山薫 上島 康孝 左毅 北 栄輔

出版者

一般社団法人情報処理学会

雑誌

情報処理学会研究報告数理モデル化と問題解決(MPS) (ISSN:09196072)

巻号頁・発行日

vol.2008, no.126, pp.139-142, 2008-12-10

参考文献数

3

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本研究ではペイジアンネットワーク (BN) を用いた株価指数の変動予測について述べる.最初に 2007 年 1 月から 10 月の予測を行ったところ,テクニカル分析よりも高い的中率を示した.続いて,2007 年と日本のバブル崩壊期の的中率の変化を詳しく調査したところ,的中率の低下をもとに,問題が顕在化した時期でなく,問題の原因が生じた時期をある程度推測できることが分かった.This paper describes the application of the prediction of stock index by using Bayesian network. In the prediction of FTSE100 in 2007 January - October, the prediction accuracy of Bayesian network was better than that of technical analysis. Next, one observed the history of the prediction accuracy of index in 2007 and during the years of the asset-inflated economy in Japan. The results indicated that the reduction of prediction accuracy is effective for finding the reasons of the problems.