Duration
About 3.5 hours
You set every stage timing from the professor panel, so it fits one block or splits across two sessions.
Comparable Company Analysis Simulation
Comparables simulation where students build a peer set
The Finsimco Comparable Company Analysis Simulation gives each student a hundred and forty companies and one business to value. The screen decides the answer before any multiple is calculated.
- About 3.5 hours, single-player
- Screening, adjustment and the median
- In-class, online or hybrid delivery
At a glance
Format
Single-player simulation
Each student holds the screening, adjustment and conclusion roles in turn and submits one valuation range.
Level
Undergraduate to MBA
Adjustable: a given peer set on clean data, up to a full screen, lease adjustments and a pending acquisition.
Professor tools
Timeline and session controls
Manage students, adjust stage timings, control progression and monitor individual inputs.
Prerequisites
Enterprise value
Students need enterprise value and EBITDA. Screening, multiple selection and calendarisation are taught inside.
Delivery
In class, online or hybrid
The web-based simulation supports in-person, remote, blended and homework-supported delivery.
Assessment
Optional, per student
Every submission is individual, so the screen, the adjustments and the review answers export per student.
Course fit
Fits valuation and banking modules
Designed for Corporate Finance, Valuation, Investment Banking, Equity Research and Financial Modelling courses.
Concepts covered
The topics a comparable company analysis module has to cover: screening a universe into a peer set, enterprise value multiples, why a median describes none of the peers, regressing multiples on growth, calendarisation and lease adjustments and reading an outlier.
Forward growth along the bottom, enterprise value to revenue up the side. Nine peers are plotted with a regression through them: the multiple a company trades at is mostly explained by how fast it grows, with an r-squared of nought point seven one. Two names sit well below the line, which is what cheap looks like once growth is accounted for. The target trades at four point one times against a predicted four point eight. The median of the nine would value the slowest grower at twice what it trades at.
Learning outcomes
Written to drop into your module descriptor without rewriting. On completing the simulation, your students will be able to:
- Build a peer set from a large universe and justify every exclusion.
- Explain why a median multiple across different growth rates describes none of the peers.
- Regress multiples on a fundamental driver and interpret the residuals.
- Make leases, options and one-off items consistent across a peer set.
- Explain what an outlier in a peer set is actually telling you.
- Produce a valuation range and state what would move it.
What students do
Each student builds the set alone, holding the screening, adjustment and conclusion roles in turn. All three want something different from the same universe, and only one range is submitted.
The gameflow every student sees before they start. The three roles come into play while the set is built and challenged; briefing, the assessment and the debrief are worked as a single view. Materials arrive stage by stage: company universe and role cards at briefing, then the screening tool, adjustment workbook and regression output, then the review comments, excluded names and client position.
Screening
Students narrow a hundred and forty companies down to the handful that are genuinely comparable, which is where the valuation is actually decided.
Adjustment
Students calendarise the periods, treat leases and options consistently and remove the one-off items, so the multiples measure the same thing.
Conclusion
Students decide what the peer set implies for this company, which is a regression question rather than a median one.
How it works
Five stages. Students screen a hundred and forty companies, adjust the survivors and produce a range.
- 1
Stage 1 · 15 min
Briefing Docs · Company Universe · Role Cards
1Briefing
Students watch the intro video, review a target with two hundred and sixty million dollars of revenue growing at twenty per cent and a universe of a hundred and forty companies in the sector, and take on all three roles before any screen is set.
- 2
Stage 2 · 60 min
Screening Tool · Adjustment Workbook · Regression Output · Tool Tips
2Screen & Adjust
The peer set is built. Working as screening, the student narrows a hundred and forty companies to nine through three bands; as adjustment, makes the periods, leases and one-off items consistent; as conclusion, runs the multiple against growth and finds that the median is four point three while the regression predicts four point eight for this company.
- 3
Stage 3 · 55 min
Review Comments · Excluded Names · Client Position · Live Scores
3The Challenge
The peer set is challenged. A reviewer asks why three obvious names were excluded, one peer has a pending acquisition that is distorting its multiple, another reports on a different year end, and the client observes that a wider size band would produce a higher number.
- 4
Stage 4 · 40 min
Review Questions · Peer Set Summary · Outcome Report · Review Pack
4The Assessment
The range is assessed. Students are asked which exclusion changed the answer most, why the median is the wrong statistic for this set, what the two names below the line were telling them, and how much of their range came from the screen rather than from the analysis.
- 5
Stage 5 · No limit
Winners · Completion Summary
5Debriefing
Students review their own peer set, compare ranges across the cohort, revisit the exclusions that separated them and reflect on the feedback. Winners and the completion summary give you a structure for the discussion.
What the experience looks like
The student interface carries the universe, the screen and the regression. The professor panel carries the timeline, the controls and every individual peer set.
Screen
Students work candidate by candidate, with revenue, margin, growth and the multiple side by side, and a written reason required for every company excluded.
Regression
The residual column is where the work is. Two peers trade well below what their growth justifies, and both of them were nearly screened out.
Professor Controls
Your view. Adjust any stage timing, start or stop the session, and compare how many peers each student kept with the range they produced.
See how this simulation fits your module
Explore the student and professor experience, and discuss timing, setup and syllabus fit.
Where it fits your syllabus
It works best as the session that shows where a valuation is really decided.
Teach before it
What enterprise value and EBITDA are. Screening, calendarisation and regression on fundamentals are explained inside the activity.
Where it sits
Mid module, typically weeks four to eight, after the basic multiples have been covered.
What it sets up
Discounted cash flow, precedent transactions, fairness opinions, pitch material, and any assessment asking students to produce a valuation.
The comparables course guide sets out where it sits in a full module.
What students get wrong
The three mistakes students make on this case, and what each one gives you in the debrief. Our simulations are designed around them: read the learning science behind it.
1
They take the median
Nine multiples ranging from two to six times averaged into one number describes none of the companies and is then applied to a tenth. The regression takes two minutes longer and explains seventy-one per cent of the variation.
2
They exclude the inconvenient names
A peer that trades at half the multiple of the rest is the most informative company in the universe, and it is the one most likely to be screened out for a technical reason. The reviewer always asks about it.
3
They adjust the target and not the peers
Students carefully strip one-off items out of the company they are valuing and compare the result to nine peers that have had nothing done to them, which quietly builds a discount into every multiple.
How to debrief it
The debrief runs itself. Every student sees their results, the cohort comparison and the decisions that produced them, with nothing for you to prepare. If you would rather lead the discussion, these questions work straight from a slide, and they use what your cohort actually did.
- Which exclusion changed your answer most?
- Why is the median the wrong statistic for this peer set?
- What were the two names below the line telling you?
- Whose range was widest, and was that honesty or indecision?
- How much of your range came from the screen rather than the analysis?
Assess the screen and the adjustments, not the number
Assessment is optional. Run the simulation ungraded as an applied activity, or use platform data as supporting evidence. Every student generates a screen, a peer set, adjustments, a regression and a valuation range with rationales. Because the simulation is single-player, every input belongs to one named student, so there is no group-work marking to untangle. All of it exports as CSV or PDF, per student, so you can assess reasoning rather than a result.
What professors can assess
- Whether each exclusion is justified on comparability rather than on convenience
- Whether the same adjustments were applied to the peers and to the target
How to interpret the score
- A range that brackets the eventual price is not proof the work was sound; read the screen
- Use the leaderboard for cohort comparison, not for grading
On generative AI: written rationales are exactly what marking teams now worry about. Because every exclusion is recorded inside the platform with its reason before the challenge arrives, the reasoning can be checked against the evidence rather than taken on trust.
Low risk to try with a class
Students rate it
93% of students rate Finsimco simulations Excellent, across more than 30,000 responses.
You are not on your own
Teaching notes, a setup and facilitation guide and a gameflow diagram come with it, and we support your first delivery directly.
No grading commitment
Run it ungraded the first time. Assessment is optional and can be added once you have seen how your cohort responds.
A bad session is recoverable
Pause or stop at any point and resume later without losing submitted data, so an overrun costs you a timetable slot, not the activity.
Read what lecturers say.
What AACSB and AMBA say about simulations
Ron Tuninga, Managing Director for EMEA at AACSB, and Victor Hedenberg, Membership Director at AMBA, on why simulation-based learning belongs in business education. Watch both interviews.
FAQs
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Get the course fit sheet
A one-page summary of this simulation, covering stages and timings, roles, concepts, learning outcomes and the debrief questions, plus a full sample teaching pack from one of our live simulations, so you can see exactly what you would be running.
Book a Demo
During the call, we can:
- Show the student and professor experience
- Discuss format, timing and syllabus fit
- Walk through setup, live delivery and optional assessment evidence
- Answer questions from your module team