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Multivariate Regression: A Tool for Forecasting Stock Prices

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  • R W Rebello
  • Y V Reddy

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%. 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.

Suggested Citation

  • R W Rebello & Y V Reddy, 2010. "Multivariate Regression: A Tool for Forecasting Stock Prices," The IUP Journal of Accounting Research and Audit Practices, IUP Publications, vol. 0(1 & 2), pages 7-32, January &.
    • Handle: RePEc:icf:icfjar:v:09:y:2010:i:1&2:p:7-32
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