Title: Potential indicators for stock index prediction: a perspective
Authors: ParthaSarathi Mishra; Satchidananda Dehuri
Department of Computer Science and Applications, North Orissa University, Baripada 757003, Odisha, India
Department of Information and Communication Technology, Fakir Mohan University, Vyasa Vihar, Balasore 756019, Odisha, India
Abstract: This paper offers a brief review and analysis of potential indicators in stock index prediction and discusses the current state-of-the-art research. Forecasting price movements in the stock market has been a major challenge for common investors, businesses, brokers, and speculators. With the rapid growth of internet technologies, electronic finance (e-finance) has become a vital application of e-business. Thus, the primary area of concern is to determine the appropriate time to buy, hold or sell. Usually, one technical indicator may not be sufficient for making a trading decision. Rather, an optimal and potential set of indicators are used to provide confirmation of a technical hypothesis before taking actions. This paper suggests some useful information by processing past prices into an informative trading signal by testing ten potential indicators on the Dow Jones Index from 24 July 2000 to 22 October 2007, confirms which is potentially the best among them and finally builds a Neural Network (NN) model which is effective in improving the accuracy of stock price prediction.
Keywords: technical indicators; stock market; buy or sell signals; trend identification; e-finance; electronic finance; artificial neural networks; ANNs; stock index prediction; price forecasting; trading decision making.
Int. J. of Electronic Finance, 2012 Vol.6, No.2, pp.157 - 183
Available online: 07 Aug 2012