Regression analysis comes with several applications in finance. For example, the statistical method is fundamental to the Capital Asset Pricing Model (CAPM). Essentially, the CAPM equation is a model that determines the relationship between the expected return of an asset and the market risk premium.
The analysis is also used to forecast the returns of securities, based on different factors, or to forecast the performance of a business. Learn more forecasting methods in CFI’s Budgeting and Forecasting Course!
1. Beta and CAPM
In finance, regression analysis is used to calculate the Beta (volatility of returns relative to the overall market) for a stock. It can be done in Excel using the Slope function.
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2. Forecasting Revenues and Expenses
When forecasting financial statements for a company, it may be useful to do a multiple regression analysis to determine how changes in certain assumptions or drivers of the business will impact revenue or expenses in the future. For example, there may be a very high correlation between the number of salespeople employed by a company, the number of stores they operate, and the revenue the business generates.
The above example shows how to use the Forecast function in Excel to calculate a company’s revenue, based on the number of ads it runs.
Learn more forecasting methods in CFI’s Budgeting and Forecasting Course!
Excel remains a popular tool to conduct basic regression analysis in finance, however, there are many more advanced statistical tools that can be used.
Python and R are both powerful coding languages that have become popular for all types of financial modeling, including regression. These techniques form a core part of data science and machine learning where models are trained to detect these relationships in data.
Learn more about regression analysis, Python, and Machine Learning in CFI’s Business Intelligence & Data Analysis certification.