Stock trading using RBF neural networks
Stock market comprises of complex sample of data in time series. It has unique characteristics like non-linearity, high noise and uncertainties. In order to gain profit, prediction of stock price becomes a hot topic all the time. According to the characteristics of financial time series, BP neura...
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| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2016
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| Online Access: | http://hdl.handle.net/10356/68014 |
| Summary: | Stock market comprises of complex sample of data in time series. It has unique
characteristics like non-linearity, high noise and uncertainties. In order to gain profit,
prediction of stock price becomes a hot topic all the time. According to the
characteristics of financial time series, BP neural network prediction model with the
minimum standard of empirical risk has poor generalization ability, which easy to
fall into the optimal and disadvantages of local presence, we come up with RBF
neural network. |
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