Project Marchmont — Specialty Retail Take-Private
A 2-hour Consumer & Retail / Special Committee case study with a complete model answer
Modeled After
Perella Weinberg Partners
Special committee materials for a controlled specialty retailer: a growth versus EV/Revenue regression, EV/EBITDA benchmarked against same-store-sales growth, an EBITDA bridge interrogating an anomalous forecast growth year, a sector earnings-reaction event study, and valuation sensitized directly to comparable-store-sales growth
Structure and exhibit set are modeled after Perella Weinberg Partners. The company, the financials and every figure in this case are entirely our own.
The Situation
Marchmont Apparel Group, Inc.
Marchmont Apparel Group, Inc.
- Sector
- Specialty apparel retail — 612 stores in 44 states under two teen banners, plus a direct channel at about 15% of net revenue
- Size
- Geography
- United States; headquartered in Tenniston, Ohio, with a single owned distribution center at Culvermoor and fourteen owned store properties
- Ownership
- Situation
The Prompt
You are the financial advisor to the Special Committee of the Board of Directors of Marchmont Apparel Group, Inc. 40 a share in cash.
Supporting Materials
What you are handed at the start of the case, in the format a real process would use.
Blank modeling template
XLSXUnlock
What You Have to Produce
The deliverables, in the order the committee will read them. The exercise runs 120 minutes.
PART 1
The unaffected price, and the date a premium is struck to
PART 2
The store base, four-wall economics and the closure program
PART 3
Build the revenue, then walk the EBITDA
PART 4
Rent, the sale-leaseback and what the structure can pay
PART 5
Seasonality and the peak funding need
PART 6
Comparable companies, precedents and the discounted cash flow
PART 7
The alternatives, the process and the recommendation
How to Approach It
The order a strong candidate works in, and why. This is the shape of the answer — the finished answer deck and Excel model are in the solution set below.
- 01
Decide what the unaffected price is before you compute a premium
- 02
Build revenue, do not grow it
- 03
Carry EBITDAR from the first tab, not as an afterthought
- 04
Argue with the plan line by line, not in aggregate
- 05
Regress the multiple, then sanity-check it against the median
- 06
Price the sale-leaseback against what it costs, not just what it raises
- 07
Sensitize on comparable sales, and prove it is the right axis
- 08
Give the Committee a price, and a price you would refuse
Key Concepts
The ideas this case is built on. Know these cold and the case becomes a question of execution rather than knowledge.
Comparable store sales as a valuation driver
Comparable store sales measure the change in revenue at stores open for a full comparable period, so they strip out the effect of opening and closing stores. In specialty retail they are the single statistic the market prices on, because they separate a chain that is growing by building stores from one that is growing because customers are coming back. That is why a peer set's EV/EBITDA multiples line up against comparable sales rather than against size or margin, and why regressing the multiple on comparable sales says more than the median does.
Four-wall economics
A store's four-wall contribution is its revenue less the costs incurred inside its four walls — merchandise, payroll, occupancy and store-level expense — before any allocation of corporate overhead and before the direct channel. It is the number that decides whether a store is worth keeping, and a schedule of stores by four-wall margin is how a retailer decides what to close. It is also why a store schedule never ties to the reported P&L without a bridge: the schedule is before overhead and excludes the direct channel, and the P&L is neither.
The opening-year ramp and the closing-year stub
A new store earns only part of its first full-year volume in the year it opens, because it opens partway through the year and takes time to reach run rate. A store being closed earns part of its run rate before the doors shut, and the liquidation markdowns that clear its inventory come with it. Modeling either as a full year is the most common error in a retail revenue build, and it compounds: the following year's comparable base is wrong too.
EBITDAR and lease-adjusted leverage
EBITDAR is EBITDA before rent. Lease-adjusted leverage adds the capitalized value of the lease obligations to funded debt and divides by EBITDAR, which puts an operator that owns its stores and one that leases them on the same basis. Under current accounting the capitalized value is the disclosed operating lease liability rather than a flat multiple of rent, and a chain with four years of average remaining term capitalizes far less per dollar of rent than one with twenty. When rent is larger than EBITDA, the lease-adjusted view is the leverage question.
The borrowing base and seasonal peak funding
An asset-based revolver lends against a percentage of the net orderly liquidation value of eligible inventory plus a percentage of eligible receivables, less reserves. For a retailer the base therefore rises and falls with inventory, which peaks before the holiday season and troughs at a January fiscal year end. So the year-end balance sheet shows the smallest inventory, the smallest borrowing base and usually no drawings — the one month of the year that says nothing about how much money the business needs. Peak funding is a monthly question.
Sale-leaseback
A sale-leaseback converts owned real estate into cash and a lease. The gross value is the market rent divided by a capitalization rate; the cash is that less transaction costs and tax on the gain over book value. On the other side, the new lease is a liability, it is usually much longer than the leases already on the balance sheet, and if the debt is sized on a lease-adjusted test then capitalizing the new rent consumes borrowing capacity at the same moment the proceeds create it.
Earnings-reaction event study
An event study regresses the abnormal return around an announcement on the size of the surprise, using a peer sample to establish what the sector normally does. In a take-private it answers a question the premium table cannot: whether the unaffected price reflects the news or overshot it. It says where the sector's own reaction function puts a stock after a miss of a given size, which is the honest benchmark for a premium struck weeks later.
MFW and the majority-of-the-minority condition
In a controlling-stockholder buyout, Delaware courts apply business judgment review rather than entire fairness only if the transaction is conditioned from the outset on both an empowered, independent special committee and an uncoerced, informed majority-of-the-minority vote. Conditions bolted on after price negotiation has begun do not qualify. Where the controller has said it will not sell, the minority vote — not a go-shop — is the only real protection, and it is worth nothing if it can be waived.
Go-shop efficacy
A go-shop lets a target solicit competing bids for a defined period after signing, usually at a reduced termination fee. Whether it is a market check in practice is an empirical question, and the answer differs sharply depending on whether a controlling holder is present: a bidder facing a controller who has announced it will not sell its stake is bidding for the right to lose. The base rates are worth computing before treating a go-shop as a substitute for price.
Charging stock-based compensation, and the multiple that follows
Stock-based compensation is a real cost to existing holders even though it is non-cash, so a discounted cash flow that starts from EBITDA has either to charge it or to dilute the share count for it. A peer-observed exit multiple is struck on reported EBITDA, which is before compensation. Applying that multiple to a post-compensation earnings base charges the same cost twice. Striking the multiple on the matching basis is the correction, and it moves the answer materially.
What Makes It Hard
The specific traps in this case — the places candidates lose the assessment without noticing.
Check Your Answer
Type the figures you produced and find out how many are right before you open the worked answer. You get a verdict and, where you are off, a pointer to the part of the build to re-check — never the number itself. Everything you type stays on this device.
How to type a figure. Digits, with an optional unit: 1,234.5, $1,234.5, 2.6x, 21.4%. For a negative use (20.0) or -20.0. Enter as many decimals as you carried — precision is never penalised.
What the Case Asked For
The arithmetic is only half of it. Tick off what you actually produced — this half is yours to score, because nothing can grade a written recommendation from a checkbox.
The Model Answer
The worked answer in full: answer deck and Excel model, built the way a banker would actually build them. It is a reference, not a submission — a strong answer under the clock is far shorter.
What the Solution Covers
- —Comparable store sales as the valuation driver
- —Growth versus EV/Revenue regression
- —EBITDA bridge interrogating an anomalous growth year
- —Earnings-reaction event study
- —Leveraged recapitalization analysis
- —Go-shop efficacy statistics
Answer Deck
Full model answer, banker-formatted
Upgrade to Diamond
Sign up and upgrade to Diamond to unlock the answer deck, the Excel model and the audio walkthrough.
Get StartedThe Excel Model
The model is linked and tied out end to end — every schedule, every formula and every check, in the file itself.
Downloads are available to Diamond members
Excel Model and PowerPoint Deck and Answer Deck (PDF) — yours to open, edit and rebuild
Walkthrough
A conversational walkthrough of how to approach the case under time pressure — where to start, what to cut, and how the recommendation gets defended.
Audio Walkthrough
How to approach Project Marchmont — Specialty Retail Take-Private
60-second preview — upgrade to Diamond for the full walkthrough
Frequently Asked Questions
Why regress the multiple instead of using the peer median?
Because in specialty retail the multiple is a function of the comparable-store line, and Marchmont's comparable sales are not at the peer median. Applying the median multiple is arithmetically identical to assuming its comparable sales are average. The regression makes that assumption explicit and lets you price the gap; the median is the sanity check you run beside it, not the answer.
Is the EV/Revenue regression a primary methodology or a reference?
Treat it as a reference and be able to say why. EV over revenue is EV over EBITDA multiplied by the margin, as a matter of arithmetic, so applying a peer median revenue multiple to a company whose margin sits below the peer median embeds a margin recovery nobody has underwritten. Run it, show it, and mark it as reference-only on the field — the growth regression is informative about where a retailer sits, but it is not a valuation you should be recommending a price off.
How do I decide which leverage test governs?
Compute both. A funded leverage ceiling is a multiple of EBITDA; a lease-adjusted ceiling is a multiple of EBITDAR less the capitalized lease obligations. The smaller one binds, and which one that is can change when the lease book changes — a sale-leaseback moves rent out of EBITDA and adds a long-dated liability, which pushes on both tests in opposite directions. If one of the two never binds under any scenario, you have written a decorative row.
Do I need a full LBO with a returns bridge?
No, and building one would answer a question nobody asked. A special committee is not underwriting a sponsor's return; it is deciding whether a price is fair to holders who cannot vote it down. What you do need from the buy side is an ability-to-pay analysis: what the committed financing supports, and therefore whether the price on the table is near the top of what the family can do or comfortably inside it.
Why does the event study matter if the market had four weeks to reprice?
Because the drift over those four weeks tells you the market did not take the print back, and that is exactly the point. The study is not a claim that the price was wrong on the day; it is a statement of where the sector's own reaction function puts a stock after a miss of a given size. If the actual move was materially larger than the relation predicts and the stock did not recover, the Committee has a defensible basis for saying the reference price the premium is struck to understates the business — and it has a number, not an assertion.
How should I treat stock-based compensation?
Charge it, and say so. Then restate the exit multiple onto the same basis before applying it, because a peer-observed multiple is struck on reported EBITDA and applying it to a post-compensation base charges the cost twice. State the treatment explicitly on the page — silence about what is in the earnings is what makes a multiple-based valuation unreviewable.
Is a go-shop enough of a market check to make the price fair?
That is an empirical question and you have the data to answer it. Compute the base rate of a go-shop producing a topping bid, split by whether a controlling holder was present, and let the numbers decide what weight the Committee can put on it. Then say what protection actually does the work here, and what would have to be true of that protection for it to be worth anything.
What is the right way to handle the store schedule's reconciliation?
Bridge the reported P&L to store four-wall EBITDA first — add back unallocated corporate expense, deduct the direct channel's contribution — and only then compare it with the bucket schedule. One bucket has to absorb the residual or the two are simply different datasets. Choose the largest bucket, and the one your conclusion leans on least, say that you have, and keep the loss-making bucket as a clean observation, because the closure analysis runs entirely off it.
How long should the presentation be?
Short enough that the Committee reaches the recommendation. This is a two-hour exercise and the workbook consumes most of it; what you hand over is the submission a strong candidate produces, not a book a bank sends a client. Lead with the answer, put the evidence behind it, and put the backup in an appendix.
About This Consumer & Retail / Special Committee Case Study
Consumer & Retail / Special Committee case study for investment banking interviews. 120-minute format covering comparable store sales as the valuation driver, growth versus ev/revenue regression, ebitda bridge interrogating an anomalous growth year. Includes the full prompt, a model answer deck, a tied-out Excel model and an audio walkthrough.
This case study sits in Investment Banking, under Consumer & Retail. Every case ships with the full prompt, the supporting materials, a complete model answer and an audio walkthrough of the judgment behind the recommendation.
120-Minute Format
The time limit a real assessment would give you
Answer Deck
Included in the model answer
Excel Model
Included in the model answer
Audio Walkthrough
How to approach the case under time pressure
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