Predicting Stock Price Index
2010 (English)Independent thesis Advanced level (degree of Master (One Year)), 15 credits / 22,5 HE credits
Student thesis
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.
Place, publisher, year, edition, pages
2010. , p. 57
Keywords [en]
Stock Price Index, Markov model, Hidden Markov model, Radial basis function neural network
National Category
Computational Mathematics Probability Theory and Statistics
Identifiers
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 (English)
Uppsok
Physics, Chemistry, Mathematics
Supervisors
Examiners
2010-02-022010-02-022025-10-01Bibliographically approved