Question 1

Walk me through a basic LBO model.

Accepted Answer

Five steps: (1) Entry — purchase price and EBITDA multiple. (2) Sources & uses — how the deal is financed (senior debt, mezzanine, equity). (3) Operating model — project revenue, EBITDA, and free cash flow over a 3–7 year hold. (4) Debt schedule — model interest payments and principal paydown using FCF. (5) Exit — apply an exit multiple to terminal EBITDA, subtract remaining debt, divide equity proceeds by equity invested to get MOIC; annualize for IRR.

Question 2

What happens to IRR if the hold period increases from 3 years to 5 years?

Accepted Answer

It depends on value creation during years 4–5. IRR is a time-sensitive metric — early exits generally produce higher IRRs given the same MOIC, because the same return is compressed into fewer years. If EBITDA growth and debt paydown in years 4–5 produce meaningful additional equity value, a longer hold can be justified on an absolute return basis, but IRR math typically penalizes longer holds unless returns compound significantly.

Question 3

How does leverage affect returns in an LBO?

Accepted Answer

Leverage amplifies equity returns by reducing the equity check at entry. If you buy a business for $100 using $70 of debt and $30 of equity, and sell it for $120 with $50 of remaining debt, your equity grows from $30 to $70 — a 2.3x MOIC. Without leverage (all equity), the same $120 sale on $100 invested is only 1.2x. The tradeoff: higher leverage increases debt service burden and default risk.

Question 4

What's the difference between free cash flow and EBITDA in an LBO model?

Accepted Answer

EBITDA is a proxy for operating earnings before capital structure and taxes. FCF is what's actually available to pay down debt: FCF = EBITDA – capex – change in working capital – cash taxes – cash interest. In a debt-heavy LBO, the gap between EBITDA and FCF is large. Businesses with low capex and minimal working capital needs (e.g., software, services) are better LBO candidates because more EBITDA converts to FCF for debt repayment.

Question 5

How do you sensitize an LBO model?

Accepted Answer

Run a two-variable sensitivity table — typically entry multiple vs. exit multiple, or EBITDA growth vs. leverage ratio — showing IRR and MOIC at each combination. The key is identifying which variables are highest-impact. For most LBOs, entry multiple and exit multiple dominate; growth assumptions matter less unless the thesis is specifically growth-driven. Always anchor to the base case and show the range of outcomes, not just the upside.

Question 6

What are the three main drivers of LBO returns?

Accepted Answer

(1) EBITDA growth — organic revenue/margin expansion or M&A. (2) Multiple expansion — exiting at a higher EV/EBITDA than entry. (3) Debt paydown — FCF reduces outstanding debt, increasing equity value. In strong deal environments, multiple expansion often dominates; in mature or distressed businesses, debt paydown and operational improvement are the primary levers. The best candidates can state which driver mattered most in a specific deal context.

Question 7

If a PE firm buys a company at 8x EBITDA with 5x leverage and sells at 10x EBITDA after 5 years with 2x EBITDA in debt remaining, what's the approximate MOIC?

Accepted Answer

Assume $100M EBITDA at entry: Purchase price = $800M. Debt = $500M, equity = $300M. EBITDA grows (say) at 10%/year to ~$161M. Exit value = 10x × $161M = $1.61B. Remaining debt = 2x × $161M = $322M. Equity proceeds = $1.61B − $322M = $1.29B. MOIC = $1.29B / $300M ≈ 4.3x. IRR ≈ 34% over 5 years. Interviewers are testing your ability to set up the framework, not memorize exact numbers.

Question 8

How do you calculate IRR quickly in a mental math interview?

Accepted Answer

Use the Rule of 72 and MOIC shortcuts: 2x in 3 years ≈ 26% IRR. 2x in 4 years ≈ 19% IRR. 2x in 5 years ≈ 15% IRR. 3x in 5 years ≈ 25% IRR. 3x in 7 years ≈ 17% IRR. A common PE target is 20–25% IRR (2–3x over 3–5 years). Practice converting MOICs to IRRs at common hold periods — interviewers will test this in heads-down case studies and verbal screens.

Question 9

What characteristics make a good LBO candidate?

Accepted Answer

Six key traits: (1) Stable, predictable FCF — supports debt service. (2) Defensible market position — pricing power, switching costs, recurring revenue. (3) Asset-light model — high FCF conversion from EBITDA. (4) Low existing leverage — capacity to add debt. (5) Clear exit path — strategic buyers or public markets exist. (6) Management team that can operate under PE pace. Negative signals: cyclical revenue, high capex, customer concentration, tech disruption risk.

Question 10

What sectors do you think are most attractive for LBOs right now, and why?

Accepted Answer

Frame around rate environment (high rates favor cash-generative businesses over growth), sector tailwinds (healthcare services, infrastructure, B2B software with high retention), and deal activity (where is dry powder being deployed?). Have a specific view — not just 'defensive sectors.' Example: 'Healthcare services businesses with Medicare Advantage exposure and sticky referral networks trade at reasonable multiples, generate predictable cash flows, and have multiple add-on acquisition targets — a strong LBO backdrop.' Avoid vague macro themes.

Question 11

How would you think about an LBO of a SaaS company?

Accepted Answer

Key considerations: (1) Revenue quality — ARR, NRR, churn, CAC/LTV. High NRR (>110%) means the business grows within its installed base, improving debt serviceability. (2) FCF conversion — SaaS can have low FCF margins due to growth spend; look for Rule of 40 efficiency. (3) Leverage capacity — lenders value predictable ARR; senior debt often expressed as ARR multiples rather than EBITDA multiples for high-growth SaaS. (4) Exit paths — strategic vs. sponsor-to-sponsor. (5) Key man risk. SaaS LBOs require adjusting the standard debt-heavy model.

LBO Interview Questions — How to Answer Them (With AI Practice)

LBO Model Mechanics