Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
Online ISSN : 2188-4749
Print ISSN : 2188-4730
第38回ISCIE「確率システム理論と応用」国際シンポジウム(2006年11月, 長野諏訪)
A Quasi-ARMA Model for Financial Time Series Prediction
Lei HUANGJinglu HUKotaro HIRASAWA
著者情報
ジャーナル フリー

2007 年 2007 巻 p. 64-69

詳細
抄録
In this paper, we propose a so called Quasi-ARMA model, for financial time series prediction which is to model the history data of an existing series, and forecast the future unknown values. The Quasi-ARMA model contains two parts: the first is a macro-part, which is a linear interface with linear ARMA like structure and embeds the complexity into the coefficient; The second part is a kernel-part, which is a nonlinear model using a neurofuzzy networks, which is used to parameterize the coefficients. The model we proposed shows better performance on prediction accuracy, and gives more consistent and reliable forecasting results than conventional neural networks (NNs) in modeling high noisy financial time series. Computer simulations are carried out and confirms the effectiveness of the proposed model.
著者関連情報
© 2007 ISCIE Symposium on Stochastic Systems Theory and Its Applications
前の記事 次の記事
feedback
Top