Financial data forecasting by evolutionary neural network based on ant colony algorithm

Authors:
Wei Gao
Affiliations:
Wuhan Polytechnic University, Hubei, Wuhan, P.R. China
Venue:
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part III
Year:
2011

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Abstract

The financial system is generally a very complicated system. So, it is very hard to be predicted. For example, it is a hard work to forecast the stock market. Here, from analyses the mathematic description of stock market system, a new forecasting method based on new evolutionary neural network is proposed here. In this new evolutionary neural network, the traditional BP algorithm and immune continuous ant colony algorithm proposed by author is combined. In order to verify this new prediction method, the stock market data of Shanghai market in 1996 is used. The results show that, our new method is very good to real practice.