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...
Saved in:
Main Author: | Hu, Donglin |
---|---|
Other Authors: | Wang Lipo |
Format: | Final Year Project |
Language: | English |
Published: |
2016
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/68014 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
RBF neural networks for pattern classification
by: He, Jianlei.
Published: (2013) -
Stock selection using General Growing and Pruning Radial Basis Function (GGAP-RBF) neural network
by: Ng, Wee Ding.
Published: (2010) -
Stock trading using neural networks
by: Li, Bofeng
Published: (2017) -
Stock trading and prediction using neural networks
by: Guo, Meng.
Published: (2010) -
Stock trading using fuzzy neural networks
by: He, Guangxu
Published: (2016)