Terminal Value, WACC & DCF Sensitivities: What Interviewers Really Ask

If you've read our DCF guide, you know the basics of how a discounted cash flow model works. This blog goes deeper into the three areas that interviewers probe the hardest: terminal value, WACC, and sensitivity analysis. These are where follow-up questions live, and where most candidates get tripped up.

Terminal Value: Why It Matters So Much

Terminal value represents the value of a company beyond the explicit forecast period. In most DCFs, it accounts for 60–80% of total Enterprise Value. That single number often matters more than all 5 years of projected cash flows combined. That's why interviewers obsess over it.

There are two methods, and you need to know both cold.

Method 1: Gordon Growth Model (Perpetuity Growth)

\text{Terminal Value} = \text{Final Year FCF} \times (1 + g) / (\text{WACC} - g)

Where g is the perpetuity growth rate – the rate at which you assume the company's cash flows will grow forever. This should reflect long-term nominal GDP growth, typically 2–3%. Anything above 4% is almost always too aggressive, because you're saying the company will outgrow the economy forever.

The key sensitivity: as g approaches WACC, terminal value approaches infinity. If WACC is 10% and g is 9%, your terminal value is enormous and your model is broken. This is the most common mistake candidates make.

Method 2: Exit Multiple

Terminal Value = Final Year EBITDA × Exit Multiple

This is more commonly used in practice. You apply a trading multiple to the company's terminal year EBITDA, based on where comparable companies trade today. The logic is: at the end of the forecast period, an investor would value this company the same way the market values similar businesses now.

The exit multiple should reflect the company's steady-state – not the current market peak or trough. Most analysts use the median or average multiple from a peer group of comparable companies.

Which method is better? Neither is 'better' – they're complementary. Banks typically calculate both and cross-reference. If they give wildly different answers, it means your assumptions are inconsistent and something needs revisiting. Interviewers love asking this and want to hear that you'd use both as a sanity check.

WACC: The Discount Rate Deep Dive

WACC = (E/V) × Re + (D/V) × Rd × (1 - t)

You already know the formula, but interviewers will dig into each component.

Cost of Equity (CAPM)

Re = Rf + β × ERP

Risk-Free Rate: The yield on the 10-year government bond in the relevant currency. For UK deals, the 10-year Gilt. For US deals, the 10-year Treasury. It represents the time value of money without any credit risk.

Beta: Measures the stock's sensitivity to market movements. A beta of 1.0 means it moves in line with the market. Above 1.0 means more volatile (tech, growth), below 1.0 means less volatile (utilities, consumer staples). You typically use the 'levered beta' from comparable companies, unlever it (to strip out their capital structure), and re-lever it using your target's capital structure.

Equity Risk Premium: The excess return investors demand for holding equities over risk-free bonds. Typically 5–7%, sourced from academic studies or providers like Damodaran. This is not something you calculate – it's an assumption you source.

Cost of Debt

The Cost of Debt is the effective interest rate a company pays on its borrowings. You can estimate it from the company's existing debt instruments (weighted average coupon) or from the yield on its traded bonds. The tax adjustment – multiplying by (1 – Tax Rate) – reflects the fact that interest payments are tax-deductible.

Capital Structure Weights

E/V and D/V should be based on market values, not book values. For equity, use the current share price times diluted shares. For debt, you can use book value as a proxy if market value of debt isn't readily available (interviewers will accept this).

Sensitivity Analysis: What Drives the DCF Output

Sensitivity analysis shows how the implied valuation changes when you adjust key assumptions. The two most important sensitivities in a DCF are:

1. WACC vs Perpetuity Growth Rate: A standard sensitivity table shows the implied share price or Enterprise Value across a range of WACC values (e.g., 8%--12%) and growth rates (e.g., 1.5%--3.5%). This reveals how much terminal value drives the output and highlights which assumptions matter most.

2. WACC vs Exit Multiple: If you're using the exit multiple method, this table shows how the valuation changes across different multiples (e.g., 7x–11x EBITDA) and discount rates.

Other common sensitivities include revenue growth rate, EBITDA margin, and CapEx as a percentage of revenue. But the discount rate and terminal value inputs are always the most impactful because they compound across the entire valuation.

A 1% increase in WACC can reduce your implied valuation by 15–25%. A 0.5% change in perpetuity growth rate can shift the terminal value by 10–20%. These are the numbers that make interviewers want to see that you understand which inputs are doing the heavy lifting.

Common Interview Questions

Q: Why does terminal value often represent 60–80% of the DCF value?

A: Because the projection period is only 5–10 years, but terminal value captures all cash flows from year 6 to infinity. Even though those cash flows are discounted heavily, the perpetuity nature means the sum is very large.

Q: What's the mid-year convention and why use it?

A: Instead of assuming all cash flows arrive at the end of each year, the mid-year convention assumes they arrive at the midpoint (e.g., 0.5, 1.5, 2.5 instead of 1, 2, 3). This is more realistic because businesses generate cash throughout the year, and it slightly increases the present value.

Q: What's the most important assumption in a DCF?

A: The terminal value assumptions – either the perpetuity growth rate or exit multiple – because terminal value is the largest component of enterprise value. WACC is a close second.

Q: If you had to pick, would you use perpetuity growth or exit multiple?

A: Both. They're cross-checks on each other. If you can only use one, exit multiple is more commonly used in practice because it's grounded in observable market data.