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Predicting Stock Price Index
Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Tillämpad matematik och fysik (CAMP). (Applied Mathematics, Finance Mathematics)
Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Tillämpad matematik och fysik (CAMP). (Applied Mathematics, Finance Mathematics)
2010 (engelsk)Independent thesis Advanced level (degree of Master (One Year)), 15 poäng / 22,5 hpOppgave
Abstract [en]

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.

sted, utgiver, år, opplag, sider
2010. , s. 57
Emneord [en]
Stock Price Index, Markov model, Hidden Markov model, Radial basis function neural network
HSV kategori
Identifikatorer
URN: urn:nbn:se:hh:diva-3784OAI: oai:DiVA.org:hh-3784DiVA, id: diva2:291586
Presentation
2010-01-22, D 415, Halmstad University, D building, 13:15 (engelsk)
Uppsök
Physics, Chemistry, Mathematics
Veileder
Examiner
Tilgjengelig fra: 2010-02-02 Laget: 2010-02-02 Sist oppdatert: 2010-02-03bibliografisk kontrollert

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