This study is based on three models, Markov model, Hidden Markov model and the Radial basis function neural network. A number of work has been done before about application of these three models to the stock market. Though, individual researchers have developed their own techniques to design and test the Radial basis function neural network. This paper aims to show the different ways and precision of applying these three models to predict price processes of the stock market. By comparing the same group of data, authors get different results. Based on Markov model, authors find a tendency of stock market in future and, the Hidden Markov model behaves better in the financial market. When the fluctuation of the stock price index is not drastic, the Radial basis function neural network has a nice prediction.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hh-3784 |
| Date | January 2010 |
| Creators | Gao, Zhiyuan, Qi, Likai |
| Publisher | Högskolan i Halmstad, Tillämpad matematik och fysik (CAMP), Högskolan i Halmstad, Tillämpad matematik och fysik (CAMP) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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