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.