Forecasting of P/E Ratio for the Indian Equity Market Stock Index NIFTY 50 Using Neural Networks

Abstract

The ratio of present price of an index to its earnings is known as its price to earnings ratio denoted by P/E ratio. A high P/E means that an index’s price is high relative to earnings and overvalued. Its low value means that price is low relative to earnings and undervalued. A potential investor prefers an index with low P/E ratio. Therefore, the movement of the P/E ratio plays a crucial role in understanding the behaviour of the stock market. In this paper the modelling of the P/E ratio for the Indian equity market stock index NIFTY 50 using NNAR, MLP and ELM neural networks models and the traditional ARIMA model with Box-Jenkin’s method is carried out. It is found that MLP and NNAR neural networks models performed better than that of ARIMA model.