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Multivariate regression: A tool for forecasting stock prices

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dc.contributor.author Rebello, R.W.
dc.contributor.author Reddy, Y.V.
dc.date.accessioned 2015-06-04T02:44:46Z
dc.date.available 2015-06-04T02:44:46Z
dc.date.issued 2010
dc.identifier.citation The IUP Journal of Accounting Research and Auditing Practices. 9(1and2); 2010; 7-32. en_US
dc.identifier.uri http://irgu.unigoa.ac.in/drs/handle/unigoa/2427
dc.description.abstract This paper examines and analyzes the use of Multivariate Regression Analysis (MRA) as a forecasting tool. The authors attempt to test the capability of the multivariate regression model to forecast the prices of stocks classified as 'A-Group' by the Bombay Stock Exchange (BSE). Researchers in the past have applied numerous variables to forecast stock prices; the authors in this study use three variables, namely stock price, operating cash flow and risk-free rate of interest. The results of the study are encouraging and the average variation of 173 stocks is less than 4 percent. The findings suggest that stock markets do not follow a random walk and there exists a possibility of forecasting stock prices by using operating cash flows and risk-free rate of returns. The authors opine that it is possible to capture nonlinearities contained in the stock prices by using MRA. If MRA is used judiciously, it is possible to forecast stock prices fairly well and this could bring transparency in stock trading and benefit the investors. en_US
dc.publisher IUP Publications Online en_US
dc.subject Commerce en_US
dc.title Multivariate regression: A tool for forecasting stock prices en_US
dc.type Journal article en_US


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