Using Regression Analysis in Business Valuation
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Summary
As valuation analysts, we often analyze how one or more variables explain the behavior of another variable such as revenues or trends in market multiples. We are also tasked with analyzing trends in data over time to be used as a basis for a forecast of future expected results. A tool that helps us analyze the relationships between variables is linear regression. Linear regression models can be useful tools in analyzing relationships between economic and financial variables over time and using these relationships as a basis to support various assumptions in business valuation. However, analysts need to be aware of the various assumptions and shortcomings of linear regression models.
Program Agenda
- Discuss the basics of linear regression models and the underlying assumptions.
- Explain the key regression statistics to determine the reliability of the regression models.
- Demonstrate how to incorporate economic and industry data into regression models to be used in the income approach.
- Discuss how regression analysis can be used to support the selection of market models in the market approach.
- Show the use of regression analysis to support a sales forecast through a case study.
Learning Objectives
- Explain the underlying assumptions of linear regression.
- Interpret key regression statistics to examine the reliability of regression models.
- Use regression models to support various assumptions in business valuation.
- Describe the limitations of regression analysis.
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CPE Information
- Prerequisites: Knowledge of Business Valuation
- Program Level: Advanced
- Preparation Required: None
- Delivery Method: Group Internet-Based
- Recommended CPE: 2.0 Credit Hours (Accounting – Technical)
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