A hybrid of DEA-MLP model for stock market forecasting

Abstract

Being a burning area of interest among the researchers the stock market forecasting draws attention worldwide for new innovations of models, ways of interpretation, wider aspects, and multidimensional analysis. The present paper proposed a hybrid of Data Envelopment Analysis and Multilayer Perceptron model for stock market forecasting. The proposed model is experimented with real-world data from BSE Sensex. The DEA model has assigned the responsibility to filtered predicators for MLP model to enhance its prediction capabilities. Separate empirical investigations are conducted for existing MLP and then for the proposed model to justify the superiority of the proposed model. It was observed that the proposed one has outperformed the existing one in most of the front.