Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/14690
Title: Refining Price to Earnings Model for Valuing Bank Stocks -An Artificial Neural Network Approach
Authors: B. Charumathi
Suraj E. S.
Keywords: Price to Earnings Valuation Model
Prediction Accuracy
Artificial Neural Network
Issue Date: 2015
Publisher: Journal of Banking Information Technology and Management
Abstract: This study performs and compares the accuracy of Price to Earnings model and Refined Price to Earnings model using Artificial Neural Network (ANN) for valuing bank stocks. Prediction accuracy measuring procedures are used to compare the performance of these models. This study also focused on comparing the predictive power of Price to Earnings Model & Refined Price to Earnings Model (using ANN) using coefficient of determination. The outcomes of predictions are discussed to know the power of Artificial Neural Network. The results of empirical analysis support that Refined Price to earnings model using ANN can be used as a valuation tool to provide better and more accurate estimation of equity stock prices of banks.
URI: http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/14690
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