Common DCF Model Mistakes

How to Error Proof a DCF Model

The DCF model states that the value of a company is equal to the sum of all of a company’s projected free cash flows (FCFs), which are discounted to the present date using an appropriate discount rate.

However, the discretionary assumptions used to project a company’s future performance are its main drawback, as these decisions are subjective and prone to the biases of the individual performing the analysis.

For that reason, the valuations derived from a DCF can vary greatly from each other.

The checklist below summarizes a few common errors often found in DCF models:

• Inclusion of Free Cash Flows (FCF) Before Year 1
• Too Short Initial Stage 1 Forecast Horizon
• Depreciation ≠ Capital Expenditures in Final Year of Forecast Period
• Mismatch in Free Cash Flows (FCFs) and Discount Rate
• Unrealistic Reinvestment Assumptions
• Forgetting to Discount Terminal Value (TV)
• Mismatch in Exit Multiple and Valuation Multiple
• Terminal Value > 75% of Implied Valuation
• Disregard of Relative Valuation — No “Sanity Check”

Mistake 1. Inclusion of Free Cash Flows (FCF) Before Year 1

The first mistake seen in DCF models is accidentally including the latest historical period as part of the Stage 1 cash flows.

The initial forecast period should consist of only projected free cash flows (FCFs) and never any historical cash flows.

The DCF is based on projected cash flows, not historical cash flows. While most understand this concept, many DCF models are linked from a separate tab, where the historical periods will also be carried over and may be erroneously linked into the DCF calculation.

As a result, make sure to discount and add only the company’s future cash flows.

Mistake 2. Too Short Initial Forecast Horizon (Stage 1)

The next error is related to having an initial forecast period that is too short, i.e. Stage 1.

For a mature company, a standard five-year forecast horizon is sufficient, i.e. the company is established with predictable cash flows and profit margins.

The time necessary for a mature company to reach a long-term sustainable state is brief — in fact, it could be even shorter than five years, if appropriate.

On the other hand, certain DCF models performed on high-growth companies need to extend the initial forecast period to a ten or even fifteen-year horizon.

Ask yourself, “Can this company continue to grow at this growth rate perpetually?”

If not, the forecast should be extended until the company matures further.

However, note that the longer the initial forecast period, the less credible the implied valuation is — which is also why the DCF is most reliable for mature companies with established market positions.

Mistake 3. Depreciation % of Capital Expenditures Converge into Final Forecast Period

Closely related to the prior mistake, a company’s depreciation as a percentage of its capital expenditures (Capex) should converge near a ratio of 1.0x, or 100%, by the end of the initial forecast period.

As a company matures, the opportunities for capital expenditures decline, resulting in less capex overall. More specifically, the majority of the company’s capex will be maintenance capex, as opposed to growth capex.

Given the reduced capex, having depreciation outpacing capex perpetually would be unrealistic as depreciation cannot reduce the value of a fixed asset (PP&E) below zero.

Mistake 4. Mismatch in Free Cash Flow (FCF) and Discount Rate

The most common DCF model is the unlevered DCF, where the free cash flow to firm (FCFF) is projected.

Since FCFF represents the cash flows that belong to all stakeholders, such as debt lenders and equity holders, the weighted average cost of capital (WACC) is the appropriate discount rate to use.

In contrast, the levered DCF — which is used far less common in practice — projects the free cash flow to equity (FCFE) of a company, which belongs solely to common shareholders. In this case, the correct discount rate to use is the cost of equity.

Mistake 5. Unrealistic Reinvestment (Capex and Change in NWC)

Generating future growth requires spending, so it cannot just be reduced without reason.

Of course, reinvestments such as Capex and the change in net working capital (NWC) will gradually decrease as a company matures and revenue growth slows down.

Yet, the reinvestment rate must still be reasonable and in line with that of the company’s industry peers.

For example, a company can be assumed to grow at 2.5% perpetually, but rational assumptions must be made where the continued revenue growth is supported, as opposed to simply cutting reinvestments to zero.

Mistake 6. Forgetting to Discount Terminal Value (TV)

After calculating the terminal value (TV), a crucial next step is to discount the terminal value to the present date.

An easy mistake to make is to neglect this step and add the undiscounted terminal value to the discounted sum of the free cash flows (FCFs).

The terminal value is calculated using either:

• Perpetuity Growth Method (or)
• Exit Multiple Methods

But regardless of which approach is used, the terminal value calculated represents the present value (PV) of the company’s cash flows in the final year of the explicit forecast period prior to entering the long-term perpetuity stage, not the value as of the present date.

Since the DCF estimates what a company is worth as of today, it is necessary to discount the terminal value (i.e. the future value) to the present date, i.e. Year 0.

The following formula is used to discount the terminal value.

Present Value of Terminal Value Formula

• Present Value of Terminal Value = Unadjusted TV / (1 + Discount Rate) ^ Years

Mistake 7. Unrealistic Terminal Growth Rate Assumption

The terminal growth rate assumption refers to the growth rate at which a company is expected to grow at into perpetuity.

One common error seen — particularly for high-growth companies — is an unrealistic terminal growth rate, such as 5%.

If a company is growing quickly far above its peers, extend the explicit forecast period until its growth rate normalizes.

A reasonable terminal growth rate assumption should generally be in line with the GDP growth rate, i.e. between 2% to 4%.

For a long-term growth rate in the upper part of that range (i.e. 4%), there should also be a valid reason supporting that assumption — e.g. a market leader such as Amazon (AMZN).

Otherwise, the terminal growth rate of most companies should be around 2% to 3%.

Mistake 8. Mismatch in Exit Multiple and Valuation Multiple

In the exit multiple approach of calculating the terminal value, the exit multiple chosen should correspond to the cash flows projected.

For an unlevered DCF, the multiples used are typically EV/EBITDA or EV/EBIT.

Why? Enterprise value represents all stakeholders, just like unlevered free cash flows.

But in the case of a levered DCF, where levered free cash flows are projected, an equity value-based multiple must be used such as the price-to-earnings ratio (P/E).

Mistake 9. Terminal Value > 75% of Implied Valuation

One of the most common criticisms of the DCF model is the contribution of the terminal value to the total implied valuation.

While a terminal value that is 60% to 75% of the total DCF value is ordinary, a terminal value that exceeds 85% of the total DCF value is a red flag that suggests that the initial forecast period should be extended and/or other assumptions likely require adjusting.

The perpetuity growth approach can also be used to cross-check the exit multiple approach’s terminal value (and vice versa).

The solution to this issue is to first prolong the explicit forecast period, as it might not be long enough for the company to have reached a normalized, stable growth state in the final year.

If that does not fix the problem, the terminal value assumptions such as the long-term growth rate could be too aggressive and not reflect stable growth.

Mistake 10. Disregard of Relative Valuation (No “Sanity Check”)

The DCF suffers from many drawbacks, with the most notable one being the overall sensitivity of the model to the assumptions used.

Hence, it is important to perform scenario analysis and sensitivity analysis to any complete DCF valuation model.

The independence of the DCF from the market is considered one of its benefits, but entirely neglecting the market price can often be a mistake.

Intentionally not performing any comps analysis as a “sanity check” under the reasoning that the market is the wrong approach.

The DCF and comps analysis should be used together, which is why institutional investors and investment banks never rely solely on one valuation method — albeit, there are times when certain approaches are weighted more heavily than others, such as if there are no comps.

Therefore, the intrinsic value and market value approaches should be used in conjunction to determine a valuation range, rather than attempting to pinpoint a single, precise valuation.

How are DCF Models Used by Investment Bankers?

Virtually every new investment banking analyst has experienced some version of this: You’re staffed on a pitch or a live deal; You spend several sleepless nights trying to determine a company’s value so your analysis can be included in the pitch; You methodically build a DCF model, LBO model, trading and deal comps; You calculate the 52 week trading highs and lows; You present a beautiful print out of your work (called a football field) to your senior banker.

Your senior banker leans back in his chair, pulls out a red pen, and starts modifying your work.

• “Let’s pull out this comp.”
• “Let’s show a slightly higher WACC range.”
• “Let’s bump up the hurdle rate on this LBO.”

What’s happened is that the senior banker has “tightened up” the football field to narrow the valuation range you just submitted and nudge it closer to the negotiated deal price.

You head back to your cubicle and wonder “is that really how valuation is supposed to be done? Is the senior banker’s goal to reach a preconceived notion of price?”

To answer these questions, let’s look at how the DCF is used in investment banking:

• Initial Public Offering (IPO): The DCF is used in an IPO to help determine a price for the offering and to educate institutional investors on the company’s fundamental drivers, and how those drivers support the pricing.
• Sell Side M&A: The DCF is often presented alongside a market-based valuation (such as comparable company analysis) as a way to contextualize it with a cash flow-based, intrinsic valuation. 
• Buy-Side M&A: The DCF is used to advise clients on the value of potential acquisition opportunities.
• Fairness opinion: The DCF is often presented to a selling company’s board of directors (alongside several other valuation approaches) to speak to the fairness of the transaction that management is proposing, which is often presented in a chart called a football field.

DCF Valuation vs. Market Pricing: What is the Difference?

A frequent criticism of investment banking valuation is that the tail wags the dog — that instead of the valuation being driven by the DCF, the valuation is a foregone conclusion based on market price, and the DCF is built to support that conclusion.

After all, an investment banker’s job is to maximize value for clients. It’s not (gasp) to get the valuation “right.”

There’s truth to this criticism. But is there anything wrong with how the investment banks do it? After all, an investment banker’s job is to maximize value for clients. It’s not (gasp) to get the valuation “right.” A simple example will illustrate why it would be absurd for the DCF to drive the investment banker’s pricing recommendation to clients.

Our example: “We can get you $300 million but you’re only worth $150 million”

A healthcare company retains an investment bank to advise on a potential sale. There are many willing buyers at a price of $300 million, but the investment banker’s DCF outputs a price of $150 million. It would be absurd for the banker to advise the healthcare company to ask for only $150 million. After all, the investment bank’s job is to maximize value for its client. Instead, what happens in this (very common) scenario is that the banker will modify the DCF model’s assumptions to align the output with what the market price will bear (something around $300 million in this case ).

It doesn’t mean the investment banking DCF is worthless–as some, such as Damodaran, suggest. To understand why there’s value in the analysis, it’s helpful to understand why a difference between the company’s DCF value and the market price exists in the first place.

DCF Implied Share Price and Market Price Divergence

DCF value diverges from market price when the DCF model’s assumptions are different from those implicit in the market’s pricing.

Thinking about the difference between price and value in this way helps illuminate the purpose and importance of the DCF in the investment banking context: The DCF framework enables the investment banker to show clients what a business must do intrinsically to justify the current market price.

The investment banker’s job isn’t to decide if a business is overvalued or undervalued — it’s to present a framework that helps the client make that decision.

When does the DCF diverge from market price?

The market may be right; The market may be wrong. The reality is that the investment banker isn’t an investor. His or her job isn’t to make a call on whether a business is overvalued or undervalued — it’s to present a framework that helps the client make that decision. After all, they’re the ones with skin in the game. While this may strike some as cynical, an investment banker is paid for getting the deal done, not for making the right call.

On the other hand, if you’re in equity research or if you’re an investor, you do have skin in the game, and it’s a whole ‘nother ballgame. Your job is to make the right call. If you invest in Apple because your DCF shows that it’s undervalued and you’re proven correct, you’ll get paid handsomely.

So what does all this mean? It means that the DCF is a framework that investment bankers use to reconcile a company’s market price with how the company must perform in the future to justify that price. Meanwhile, investors use it as a framework for identifying investment opportunities.

And everyone involved in the process understands this.

That said, banks can and should be clearer about the purpose of the DCF in the IB context. Clarification of the valuation’s purpose would be especially helpful when the valuation is presented to the public (either directly or indirectly). An example of this is a valuation included in a fairness opinion, a document presented to the seller’s shareholders and written by an investment bank hired by the selling company’s board.

Bottom Line: Common Errors in the DCF

DCF models built by investment bankers (or, for that matter, by investors or corporate managers) are not flawless. While most DCF models do a great job of adding bells and whistles, many finance professionals lack a complete understanding of the core concepts of the DCF model.

Some of the most common conceptual errors are:

• Double counting the impact of certain assets or liabilities (first in the cash flow forecast and again in the net debt calculation). For example, if you include affiliate income in unlevered free cash flows but also include its value in net debt, you’re double counting. Conversely, if you include non-controlling interest expense in the cash flows but also in net debt, you’re double counting.
• Failing to count the impact of certain assets or liabilities. For example, if you don’t include affiliate income in unlevered free cash flow but you also don’t include its value in net debt, you’re not counting the asset at all.
• Failing to normalize the terminal value cash flow forecast. The relationship between returns on capital, reinvestments and growth all have to be consistent. If you reflect terminal growth that isn’t supported by your implicit assumptions for returns on capital and reinvestments, your model will output an indefensible output.
• Calculating WACC incorrectly. Quantifying the cost of capital (WACC) is a complicated topic. There are many places where modelers can go wrong. There is confusion around the calculation of the market weights, calculating beta and the market risk premium.

Learn More → Common Errors in DCF Models (Michael J. Mauboussin)