DocumentCode :
605156
Title :
Validation of Artificial Neural Network Model for Share Price UK Banking Sector Short-Term Trading
Author :
Turkedjiev, E. ; Angelova, M. ; Busawon, K.
Author_Institution :
Fac. of Eng. & Environ., Northumbria Univ., Newcastle upon Tyne, UK
fYear :
2013
fDate :
10-12 April 2013
Firstpage :
6
Lastpage :
11
Abstract :
The study´s objective is to justify the use of the ANN for the short-term prediction of share prices, particularly in the banking sector. The assumption is that financial share time-series contain significant non-linearity and that the ANN can be utilized effectively. The ANN model is compared with a linear regression model. Non-linearity is shown by deduction via a comparison of experimental results using the ANN and linear regression models. Furthermore the ANN model is compared with another nonlinear type of model i.e. bilinear model as well. The experiments are based on actual monthly (four-week) period datasets, and the performance of the models is formally evaluated. The conclusions are positive and do merit further experimentation.
Keywords :
banking; neural nets; regression analysis; share prices; time series; ANN model; artificial neural network model; bilinear model; financial share time-series; linear regression model; nonlinear type; period datasets; share price UK banking sector short-term trading; share prices; short-term prediction; Artificial neural networks; Computational modeling; Data models; Linear regression; Mathematical model; Numerical models; Share prices; Artificial neural networks; Banking sector; Bilinear model; Financial shares; Linear models; Short-term share trading; Validation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Modelling and Simulation (UKSim), 2013 UKSim 15th International Conference on
Conference_Location :
Cambridge
Print_ISBN :
978-1-4673-6421-8
Type :
conf
DOI :
10.1109/UKSim.2013.31
Filename :
6527381
Link To Document :
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