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Ultra High Frequency Trigonometric Higher Order Neural Networks for Time Series Data Analysis

Ultra High Frequency Trigonometric Higher Order Neural Networks for Time Series Data Analysis

Ming Zhang
Copyright: © 2009 |Pages: 31
ISBN13: 9781599048970|ISBN10: 1599048973|ISBN13 Softcover: 9781616925673|EISBN13: 9781599048987
DOI: 10.4018/978-1-59904-897-0.ch007
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MLA

Zhang, Ming. "Ultra High Frequency Trigonometric Higher Order Neural Networks for Time Series Data Analysis." Artificial Higher Order Neural Networks for Economics and Business, edited by Ming Zhang, IGI Global, 2009, pp. 133-163. https://doi.org/10.4018/978-1-59904-897-0.ch007

APA

Zhang, M. (2009). Ultra High Frequency Trigonometric Higher Order Neural Networks for Time Series Data Analysis. In M. Zhang (Ed.), Artificial Higher Order Neural Networks for Economics and Business (pp. 133-163). IGI Global. https://doi.org/10.4018/978-1-59904-897-0.ch007

Chicago

Zhang, Ming. "Ultra High Frequency Trigonometric Higher Order Neural Networks for Time Series Data Analysis." In Artificial Higher Order Neural Networks for Economics and Business, edited by Ming Zhang, 133-163. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-59904-897-0.ch007

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Abstract

This chapter develops a new nonlinear model, Ultra high frequency Trigonometric Higher Order Neural Networks (UTHONN), for time series data analysis. Results show that UTHONN models are 3 to 12% better than Equilibrium Real Exchange Rates (ERER) model, and 4 – 9% better than other Polynomial Higher Order Neural Network (PHONN) and Trigonometric Higher Order Neural Network (THONN) models. This study also uses UTHONN models to simulate foreign exchange rates and consumer price index with error approaching 0.0000%.

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