REFINING EQUITY VALUATION MODELS AND DEVELOPING AN INTEGRATED MODEL FOR INDIAN BANK STOCKS USING ANN

The aim of investors of bank stocks is to earn reasonable returns. This paper presents the framework for valuing bank stocks using different valuation models. But Most of the studies indicate that many equity valuation models are inaccurate due to various reasons. Accurate equity valuation will help the investors and managers to improve their chances of avoiding the unprofitable investments. This paper investigates the significance of six equity valuation models in terms of predictive power and valuation accuracy of bank stocks; then revises select three best equity valuation models; and refines the same by using artificial neural network to improve their valuation accuracy. Further, this paper also focus on developing a new integrated equity valuation model using artificial neural network for bank stocks in India. This study selected a sample of 14 banks which constitute the BSE Bankex. Due to high levels of valuation errors, predicting and choosing appropriate bank stocks became a difficult task for investors in India. Hence, there arises the need to study how the valuation accuracy of bank stocks can be improved by revising, refining the existing models and developing an integrated model using artificial neural network approach.