DCF Model Training Free Guide
A free guide on how to build DCF models in Excel.
A free guide on how to build DCF models in Excel.
A DCF model is a specific type of financial model used to value a business. DCF stands for Discounted Cash Flow, so a DCF model is simply a forecast of a company’s unlevered free cash flow discounted back to today’s value. This DCF model training guide will teach you the basic, step by step.
Even though the concept is simple, there is actually quite a bit of technical background to each of the components described above, so let’s break each of them down into further detail. The basic building block of a DCF model is the 3 statement model, which links the financials together. This DCF model training guide will take you through the steps you need to know to build one yourself.
Cash flow is simply the cash generated by a business that’s available to be distributed to investors, or reinvested in the business. In financial modeling and DCF analysis the type of cash flow that’s used is most commonly Unlevered Free Cash Flow – cash that’s available to both debt and equity investors. To learn more, please read our guide on how to calculate unlevered free cash flow.
Cash flow is used because it represents economic value, while accounting metrics like net income do not. A company may have positive net income but negative cash flow, which would undermine the economics of the business. Cash is what investors really value at the end of the day, not accounting profit.
The cash flow that’s generated from the business is discounted back to a specific point in time (hence the name DCF model), typically to the current date. The reason cash flow is discounted comes down to several things, mostly summarized as opportunity cost and risk.
A firm’s Weighted Average Cost of Capital (WACC) represents the required rate of return expected by its investors. Therefore, it can also be thought of as a firm’s opportunity cost, meaning if they can’t find a higher rate of return elsewhere, they should buy back their own shares.
To the extent a company achieves rates of return above their cost of capital (their hurdle rate) they are “creating value” and if they are earning a rate of return below their cost of capital they are “destroying value”.
Investors’ required rate of return (as discussed above) generally relates to the risk of the investment (using the Capital Asset Pricing Model). Therefore, the riskier an investment, the higher the required rate of return and the higher the cost of capital.
The farther out the cash flows are the riskier they are, and thus need to be discounted further, based on the Time Value of Money.
The simplest way to describe the time value of money is as follows: “more money, more sooner, more better.”
This is a large topic, and there is an entire art behind forecasting the performance of a business. In simple terms, the job of a financial analyst is to make their most informed prediction about how each of the drivers of a business will impact its results in the future. See our guide to assumptions and forecasting to learn more.
Typically, a forecast for a DCF model will go out approximately 5 years, except for resource or long-life industries such as mining, oil and gas, and infrastructure where engineering reports will be used to build a long-term “life of resource” forecast. For an example of this, please see our mining financial modeling course.
There are several ways to build a revenue forecast, but broadly speaking they fall into two main categories: growth based and driver based.
A growth-based forecast is simpler and makes sense for stable, and possibly mature business, where a basic year over year growth rate can be used. For many DCF models this will be sufficient.
A drivers-based forecast is more detailed and challenging to develop. It requires disaggregating revenue into its various drivers, such as price, volume, products, customers, market share, and external factors. Regression analysis is often used as part of a drivers-based forecast to determine the relationship between underlying drivers, and top-line revenue growth.
Building an expense forecast can be a very detailed and granular process, or it can also be a simple year-over-year comparison.
The most detailed approach is called a Zero-Based budget, and requires building up the expenses from scratch, without giving any consideration to what was spent last year. Typically, each department in the company is asked to justify every expense they have, based on activity. This approach is often used in a cost cutting environment, or when financial controls are being imposed. It is also only practical to be performed internally, and not buy outsiders like investment bankers or equity research analysts.
Once most of the income statement is in place it’s time to forecast the capital assets. These typically include balance sheet items such as: property plant and equipment (PP&E), technology, research and development (R&D) and working capital including accounts receivable and inventory.
PP&E is often the largest balance sheet item and capital expenditures (capex) as well as depreciation need to be modeled in a separate schedule. The most detailed approach is to have a separate schedule in the DCF model for each of the major capital assets, and them consolidate them into a total schedule. Each capital asset schedule will have several lines: opening balance, capex, depreciation, dispositions, and closing balance.
This way this section is built will depend largely on what type of DCF model you’re building. The most common approach is to just keep the company’s current capital structure in place, assuming no major changes other that things that are “knows” like debt maturity. Since we’re using unlevered free cash flow this section is actually not that important to the DCF model. It is, however, important if you are looking at things from the perspective of an equity investor or equity research analyst. Investment bankers typically focus on enterprise value, as It’s more relevant for M&A transactions where the entire company is bought or sold.
The terminal value is a very important part of a DCF model. It often makes up more than 50% of the net present value of the business, especially if the forecast period is 5 years or less. There are two way to calculate the terminal value: the perpetual growth rate approach and the exit multiple approach.
The perpetual growth rate assumes that the cash flow generated at the end of the forecast period grows at a constant rate forever. So, for example, the cash flow of the business is $10 million and grows at 3% forever, with a cost of capital of 10%. The terminal value is $10 million / (15% – 2%) = $77 million.
With the exit multiple approach the business is assumed to be sold for what a “reasonable buyer” would pay for it. This typically means an EV/EBITDA multiple at or near current trading values for comparable companies. If the business has $12 million of EBITDA and similar companies are trading at 6x then the terminal value is $12 million x 6 = $72 million.
It’s important to pay close attention to the timing of cash flow in a DCF model as not all the time periods are necessarily equal. There is often an “stub period” at the beginning of the model where only a portion of the year’s cash flow is received by the investor. Additionally, the cash outflow (making the actual investment) is typically a spate time period before the stub is received.
XNPV and XIRR are easy ways to be very specific with the timing of cash flow when building a DCF model. Best practice is to always use these over the regular Excel NPV formula and IRR Excel functions.
When building a DCF model using unlevered free cash flow, the NPV that you arrive at is always the enterprise value (EV) of the business. This is what you need if you’re looking to value the entire business or compare it with other companies without taking into account their capital structures (i.e. an apples to apples comparison). For most investment banking transactions, the focus will be on enterprise value.
If you’re looking for the equity value of the business, you take the net present value (NPV) of the unlevered free cash flow and adjust it for: cash and equivalents, debt, and any minority interest. This will give you the equity value, which you can divide by the number of shares and arrive at the share price. This approach is more common for institutional investors or equity research analysts, both of whom are looking through the lens of buying or selling shares.
Once the DCF model is complete (i.e. you’ve arrived at the NPV of the business) it’s time to layer on sensitivity analysis to determine what range the business could be worth as various drivers or assumptions in the model change.
To this analysis an analyst uses two main Excel tools: data tables and goal seek. By linking the NPV of the business to cells that influence the underlying assumptions, it’s possible to see how the value changes with the inputs.
We’ve got a bunch of resources on how to perform sensitivity analysis in Excel if you’re interested in learning how to perform it.
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