The paper estimates earnings per share (EPS) of top three Indian public sector banks on the basis of Ohlson O score, Zmijewski score and Graham Number, for a period of 12 years (2004-2015), with the help of the generalized method of moments (GMM), along with the use of an artificial neural...

Stock price forecasting is a classic problem facing analysts. Forecasting models have been developed for predicting individual stocks and stock indices around the world and in numerous industries. According to a literature review, these models have yet to be applied to the restaurant industry....

This study has examined the IPO performance in India from 2007 to 2013. Results show that under-pricing exists in the first day of trading during the particular period, but results show that the degree of under-pricing is dramatically decreased in comparison with what is shown in previous...

This article proposes an approach to constructing sentiment lexicons in the financial domain. The approach takes advantages of news bulletins and a given financial variable, such as stock prices, to generate candidates of sentiment expressions by fusing the two data sources. The candidates are...

The present article predicts the movement of daily Indian stock market (S&P CNX Nifty) price by using Feedforward Neural Network Model over a period of eight years from January 1st 2008 to April 8th 2016. The prediction accuracy of the model is accessed by normalized mean square error (NMSE) and...

Social media-based forecasting has received significant attention from academia and industries in recent years. With a focus on Twitter, this paper investigates whether sentiments of the tweets regarding the 7 largest US financial service companies (in U.S. dollars) are related to the stock...