Forecasting Financial Performance using Regression Techniques: A case study on Comparative Analysis of Nestle and Unilever

Abstract

Forecasting financial performance is an essential part of business planning and decision making that uses past financial performance and current conditions to analyze financial statement such as income statement, balance sheet and cash flow of a company. The objective of this study is to demonstrate the relationship between net profit and return on investment (ROI) with sales revenue, operating expenses, income tax and investment using time series data. This is important because net profit and return on investment gives more information for forecasting financial performance of a company. This paper uses some forecasting tools and techniques such as simple and multiple regression model to interpret financial performance of a company and prospects of the business. In order to achieve this objective, “Excel Data Analysis” is used as an analytical tool to analyze the data of the study represented by the actual data taken from the relevant renowned companies such as Unilever and Nestle for the period (2005 - 2020). In this analysis, it is observed that the correlation between dependent variable and independent variable is medium and poor for using simple regression technique. It also interprets that the correlation is positively high for Unilever whereas it is positively medium for Nestle company if multiple regression analysis is applied instead of simple regression. The hypothesis of this analysis shows that there is a statistically significant relationship between net profit and return on investment with sales revenue, operating expenses, income tax and investment using multiple regression technique.