Can the neuro fuzzy model predict stock indexes better than its rivals?

Chin-Shien Lin, Haider Khan () and Chi-Chung Huang
Additional contact information
Chin-Shien Lin: Department of Finance, Providence University
Chi-Chung Huang: Graduate School of Business Administration, Providence University

No CIRJE-F-165, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

Abstract: This paper develops a model of a trading system by using neuro fuzzy framework in order to better predict the stock index. Thirty well-known stock indexes are analyzed with the help of the model developed here. The empirical results show strong evidence of nonlinearity in the stock index by using KD technical indexes. The trading point analysis and the sensitivity analysis of trading costs show the robustness and opportunity for making further profits through using the proposed nonlinear neuro fuzzy system. The scenario analysis also shows that the proposed neuro fuzzy system performs consistently over time.

Pages: 49 pages
Date: 2002-08
New Economics Papers: this item is included in nep-cbe, nep-ets and nep-fmk
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:tky:fseres:2002cf165

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