To judge an interdisciplinary approach for stock market prediction: Evidence from India

This interdisciplinary paper is an attempt towards financial prediction in Indian stock market over recent years, using Artificial Neural Network (ANN). I have tested this newly created model against traditional ARCH/GARCH models using z-test. Different error metrics like Average Absolute Error (AAE), Mean Square Error(MSE), Max AE are used towards prediction of opening, maximum, and minimum daily stock prices respectively. This paper concludes the difference of predictive ability of the proposed model with that of traditional ARCH/GARCH models.