Discriminant model of revenue prediction: a study of selected top performing companies in India

Jayant Hooda (), Vijay Singh and Amit Dangi
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Jayant Hooda: C.H.L. Government College Chhara
Vijay Singh: Indira Gandhi University
Amit Dangi: SGT University

Journal of Revenue and Pricing Management, 2021, vol. 20, issue 2, No 8, 185-193

Abstract: Abstract A business enterprise, striving for maximum revenue generation and sustainable profitability, comprehensively and continuously engages in exploring the key factors to expand the market base aiming to clinch the top seat. Owing to plurality of financial variables, it has always been an issue of academic and practical importance to arrive at a smaller but reliable set of financial indicators. Post Great Depression, empirical literature emphasized largely upon predicting bankruptcy of companies in dichotomous categories through linear combination of a few variables, e.g., Altman Z, Zeta, and Discriminant functions, etc. With the recent advancements in the IT, Data Analysis and Research, newer and robust statistical techniques are being used to obtain linear vectors of multiple groups to explain the financial performance. The present study selected twenty-eight financial variables representing major financial dimensions of a business to derive a variate or discriminant function of the significant variables to predict the revenue of the top performing companies (three pre-defined groups). Analysis was made separately for each of the 2 years (2016 and 2017). The obtained functions accurately classified 70% of the companies in each year. The results have implications for investors, management, credit rating agencies, mergers and acquisitions, etc., as their decisions depend upon sound prediction and forecasting.

Keywords: Revenue; Discriminant function; Ratio analysis; Financial performance; Prediction modeling (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1057/s41272-021-00299-x

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