Financial Modeling

What Is Financial Modeling?

Financial modeling is the process of building a structured representation of a business's or investment's finances, usually in a spreadsheet, to estimate how it may perform in the future. A typical model links the company's income statement, balance sheet, and cash flow statement together, so that a change in one input, such as the expected rate of sales growth, flows through to the others. The result is a set of projections that can be used to estimate what an asset might be worth or how it might perform under different conditions.

How a Model Is Built

Most models follow a similar sequence. The modeler begins with historical financial statements and other relevant data, then sets assumptions about revenue growth, operating costs, taxes, capital spending, and working capital. These assumptions drive projections of the financial statements over a chosen number of future years.

From there, the projected figures are often run through a valuation method, such as a discounted cash flow analysis, to turn expected future cash into an estimated present value. Finally, the modeler tests the results with sensitivity analysis, changing key assumptions one at a time or together to see how much the output moves. A well-built model keeps inputs clearly labeled and separate from formulas, which makes it easier to review and update.

Why It Matters to Investors

Financial models help investors organize their thinking and compare companies on consistent assumptions. Writing out each assumption forces a clearer view of what must go right for a particular outcome to occur. Models are also widely used in corporate planning, lending decisions, and mergers and acquisitions.

Models have real limits, however. A model is only as good as its inputs, and small changes to long-term assumptions can produce large differences in the result. In a discounted cash flow analysis, much of the estimated value often comes from terminal value, which depends heavily on assumptions about the distant future. Models can also create a false sense of precision, and they cannot anticipate events that break sharply from past patterns. For this reason, many investors find it more useful to examine the assumptions behind a model than to focus only on its final figure.