Titlebook: Computational Intelligence in Economics and Finance; Shu-Heng Chen,Paul P. Wang Book 2004 Springer-Verlag Berlin Heidelberg 2004 Artificia

死亡率

有机体

https://doi.org/10.1007/978-3-8349-9276-5level, based on hidden Markov models (HMMs), finds global patterns from a DTS set. As a result, similar and periodic patterns are successfully extracted. We demonstrate our method on the analysis of “Exchange Rate Patterns” between the U.S. dollar and Australian dollar.

Lymphocyte

Searching Financial Patterns with Self-organizing Mapsck index in the near future. We further test profitability performance by trading on these SOM-induced financial patterns. The equity-curve results show that SOM-induced trading strategy is able to outperform the buy-and-hold strategy in quite a significant period of time.

浮夸

Financial Applications of Wavelets and Self-organizing Mapsfor the visualisation are based on the wavelet coefficients of 32-day trading periods with daily sampling of the closing value. The trajectory formed on the U-matrix of SOM shows the evolution of the individual stock and indicator data and aids the detection of abrupt changes in the behaviour of the time-series.