Title :
Predicting the BSE Sensex: Performance comparison of adaptive linear element, feed forward and time delay neural networks
Author :
Nair, Binoy B. ; Patturajan, M. ; Mohandas, V.P. ; Sreenivasan, R.R.
Author_Institution :
Dept. of Electron. & Commun. Eng., Amrita Vishwa Vidyapeetham, Coimbatore, India
Abstract :
Accurate prediction of financial time series (which can be considered as nonlinear systems) especially in relation to emerging markets like India assumes prominence in that, these markets offer significantly higher opportunities for wealth creation for the investor. This paper compares the effectiveness of different types of Adaptive network architectures in one-step ahead prediction of the daily returns of Bombay Stock Exchange Sensitive Index (SENSEX). The performance of each network is evaluated using 17 different performance measures to find the best network architecture. Also, an empirical evaluation of the weak form of Efficient Market Hypothesis (EMH) for the data in reference is carried out here.
Keywords :
feedforward neural nets; stock markets; time series; BSE sensex; Bombay stock exchange sensitive index; EMH; SENSEX; adaptive linear element; adaptive network architectures; efficient market hypothesis; feed forward neural networks; financial time series; time delay neural networks; Adaptive; Sensex; artificial neural networks; prediction;
Conference_Titel :
Power, Signals, Controls and Computation (EPSCICON), 2012 International Conference on
Conference_Location :
Thrissur, Kerala
Print_ISBN :
978-1-4673-0446-7
DOI :
10.1109/EPSCICON.2012.6175277
