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

This chapter develops a new nonlinear model, ultra high frequency trigonometric higher order neural networks (UTHONN) for time series data analysis. UTHONN includes three models: UCSHONN (ultra high frequency sine and cosine higher order neural networks) models, UCCHONN (ultra high frequency cosine and cosine higher order neural networks) models, and USSHONN (ultra high frequency sine and sine higher order neural networks) models. 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 10-6.