Neuro-fuzzy Phillips-type Stabilization Policy for Stock Prices and Exchange-rates Models

Y. Ito (Japan)


Neuro-fuzzy, Phillips-type stabilization policy, stock prices, exchange-rates, Japan


This paper has two purposes. First, the traditional Phillips-type PID feedback stabilization model can be extended to Neuro-Fuzzy stabilization policy model with stock prices and exchange-rate markets throughout New York, Frankfurt and Tokyo markets using Fuzzy type with IF-THEN clause control and RBF membership function for multi-targets and multi-control models. Second, the average stock prices and exchange-rates are interdependent among so many factors such as the performance of big corporations, political and international financial and money flows and macroeconomic factors. We consider how this dynamic behavior of these markets can be controlled by these new computer-oriented technology.

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