政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/6139

English | 正體中文 | 简体中文 | Post-Print筆數 : 27 | Items with full text/Total items : 109952/140887 (78%)
Visitors : 46344800 Online Users : 661

RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.

Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer

政大機構典藏 > 商學院 > 財務管理學系 > 期刊論文 > Item 140.119/6139

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/6139

Title:	Forecasting S&P 500 stock index futures with a hybrid AI system
Authors:	徐燕山;蔡瑞煌 Hsu, Yen-Shan;Ray Tsaih;Lai, Charles C.
Keywords:	Hybrid AI system;Rule-based system;Reasoning Neural Networks;Back Propagation Networks;S&P500 stock index futures
Date:	1998-12
Issue Date:	2008-11-05 17:05:31 (UTC+8)
Abstract:	This study presents a hybrid AI (artificial intelligence) approach to the implementation of trading strategies in the S&P 500 stock index futures market. The hybrid AI approach integrates the rule-based systems technique and the neural networks technique to accurately predict the direction of daily price changes in S&P 500 stock index futures. By highlighting the advantages and overcoming the limitations of both the neural networks technique and rule-based systems technique, the hybrid approach can facilitate the development of more reliable intelligent systems to model expert thinking and to support the decision-making processes. Our methodology differs from other studies in two respects. First, the rule-based systems approach is applied to provide neural networks with training examples. Second, we employ Reasoning Neural Networks (RN) instead of Back Propagation Networks. Empirical results demonstrate that RN outperforms the other two ANN models (Back Propagation Networks and Perceptron). Based upon this hybrid AI approach, the integrated futures trading system (IFTS) is established and employed to trade the S&P 500 stock index futures contracts. Empirical results also confirm that IFTS outperformed the passive buy-and-hold investment strategy during the 6-year testing period from 1988 to 1993.
Relation:	Decision Support Systems, 23(2), 161-174
Data Type:	article
DOI 連結:	http://dx.doi.org/10.1016/S0167-9236(98)00028-1
DOI:	10.1016/S0167-9236(98)00028-1
Appears in Collections:	[財務管理學系] 期刊論文

Files in This Item:

File	Description	Size	Format
161174.pdf		185Kb	Adobe PDF2	1220	View/Open

社群 sharing

著作權政策宣告 Copyright Announcement

1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.

Loading...