Refining ohlson model for valuing bank stocks- an artificial neural network approach

Abstract

This study performs and compares the accuracy of Simplified Ohlson model and Refined Ohlson 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 Simplified Ohlson Model & Refined Ohlson 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 Ohlson model using ANN can be used as a valuation tool to provide better and more accurate estimation of equity stock prices of banks.