Brandon Leon

Toolkit · Free template · Buy-side

An IB-grade Reverse-LBO workbook. Free.

8 tabs, every formula auditable: Drivers, Forward LBO with year-by-year debt schedule, Reverse LBO max-entry-multiple table at four IRR thresholds (15% / 20% / 25% / 30%), Returns Attribution, Sensitivity grid, Sources & Uses, and a Notes tab walking every formula. Two worked cyclical examples ship together — Micron through-cycle (where the question is whether sponsors would bid the AI cycle) and Western Digital post-SanDisk-spin take-private (where the question is what NAND-only at 5× leverage looks like for a financial buyer). Methodology disagreement across cyclicals is the recommendation. The Python pipeline that auto-populates this for any ticker is available on request.

Get the workbooks

Two 8-tab Excel workbooks — MU reverse-LBO (through-cycle) and WDC reverse-LBO (post-spin take-private) — so you can see how the same framework reads two different cyclical names. Drop your email, the downloads appear here. ~18 KB each, no follow-up unless you opt in.

Just the files by default. Disclaimer.

Thanks — here are the workbooks.

Workbook — MU Reverse-LBO (.xlsx, ~18 KB) Workbook — WDC Reverse-LBO (.xlsx, ~18 KB)

Run the workbooks side by side. The methodology disagreement IS the recommendation. Each workbook contains a Notes tab walking every formula and the audit trail.

Want to run the same math live in your browser? Open the calculator →

Want the full Python pipeline?

The workbooks above are static templates. The Python + Jupyter pipeline I built around them pulls live data from yfinance, runs the full end-to-end build (loader → sector scorecard → 5y forecast → reverse-LBO bisection → sensitivity grids → Excel) and produces fully populated workbooks for any ticker in ~60 seconds. I send the source on request to analysts, researchers, and students with a real use case — tell me what you're working on and I'll send it over.

I read every request and reply personally. Usually within 24 hours.

Got it — I'll be in touch within a day.

What's in the template

How to use it

Two paths, depending on which tier you have.

Workbook tier

  1. Download both workbooks

    Drop your email at the top to reveal the downloads. You get MU_reverse_lbo.xlsx and WDC_reverse_lbo.xlsx — same framework, two cyclical pulls. Open in Excel or LibreOffice.

  2. Read both side by side

    The point is to see how the framework reads different cycles. MU's reverse-LBO premium (or discount) tells you whether sponsors would underwrite at today's price; WDC's tells you whether the post-spin NAND business is sponsor-territory cheap. The spread between them is the option value of the cyclical call.

  3. Replace with your own company

    Overwrite the yellow Drivers cells: shares, net debt, EBITDA, growth, margins, deal-structure assumptions. Live formulas recalculate automatically. The Reverse-LBO table tells you, at each target IRR, what entry multiple a sponsor would underwrite and what implied take-private price that maps to.

Pipeline tier (request access above ↑)

  1. Email me a use case

    Use the request form near the top. Tell me what you're working on. I send the source over after a quick read.

  2. Run setup

    Mac/Linux: ./setup.sh  ·  Windows: double-click setup.bat. Installs Python dependencies (yfinance, openpyxl, xlsxwriter, pandas).

  3. Edit Cell 1 of the notebook (or use the CLI)

    Plug in your ticker and scorecard. jupyter notebook reverse_lbo.ipynb → Run All. Or use python run_reverse_lbo.py MU --preset semiconductors. Pipeline produces a fully populated 8-tab workbook in ~60 seconds.

What you need

FAQ

Why ship two workbooks instead of one?
For cyclicals especially, the methodology choice is the recommendation. MU through-cycle (winsorized mid-cycle EBITDA, conservative HBM tail-off) reads differently than WDC post-spin (NAND-only, longer cycle trough-to-peak, cleaner asset coverage). Shipping both lets you see the framework reading two different cycles at once. If the workbooks disagree on whether the price is sponsor-territory cheap, that disagreement is the bull/bear framing in compact form.
Is the workbook running real bisection IRR or a proxy?
The workbook uses a closed-form approximation for the Reverse-LBO and a MOIC^(1/H)−1 proxy for the sensitivity grid. Both match bisection-grade IRR within ~30 bps in tested ranges. For full bisection (matches the Python pipeline exactly), use the browser calculator; same Drivers, full iteration each pass. The workbook is auditable on paper; the calculator is faster on a single name. They give the same answer.
What's the difference between this and the LBO/M&A template?
The LBO/M&A template is the full 17-tab forward LBO with sources & uses, debt schedule, returns attribution, accretion/dilution, peer-blended comps, sanity-check auto-flags — everything you'd build for a buy-side IC. This template is leaner: 8 tabs focused specifically on running a name backwards from a target IRR to find the price a sponsor would pay. The two workbooks share the same audit standards and the same MU through-cycle scorecard; the LBO/M&A template is the right starting point for a real LBO underwrite, this template is the right framework for asking "is this name takeable from public hands."
Why use reverse-LBO at all if you're not actually running a deal?
Three reasons. (1) Reverse-LBO is the cleanest way to ground a public-market thesis in capital-structure reality. The framework forces you to commit to an exit multiple and a leverage capacity — the two assumptions public-market models tend to hand-wave. (2) The implied take-private price is a real floor under the stock if the operating story holds. Below that price, sponsors would step in. (3) It's a discipline tool for bull theses. If your bull case requires a multiple no sponsor would underwrite at 20% IRR, you should at least know that.
Is this really free?
Yes — both tiers. The workbooks are a free download. The pipeline is also free for analysts, researchers, and students with a real use case — I just want to know what you're working on before I send the source. Built on open-source libraries (yfinance, openpyxl, pandas, jupyter). No paid data feeds required.
Why gate the pipeline behind a request form?
Two reasons. (1) The pipeline is a real piece of work and I'd rather it goes to people with a use case I can engage with. (2) Every request is a conversation — if you tell me you're building a thesis on a name, I'll often have something useful to add. The form isn't a filter to keep people out; it's a filter to start better conversations. I reply to every request, usually within 24 hours.
What sectors are calibrated?
Six scorecards ship with the template: semiconductors, semiconductors_ai_cycle, energy, materials, industrials, generic. Each is a calibrated set of through-cycle factors — mid-cycle margin method, capex intensity, NWC %, target leverage, entry/exit multiples. Add your own scorecards by editing one Python dict in the pipeline.
What if I'm not technical?
The workbook tier is just Excel — if you can open a .xlsx and overwrite cells, you can use it. The browser calculator at pe-reverse-lbo.html is even easier — you just type numbers, the implied take-private price recalculates live. The pipeline tier requires Python (free; install from python.org) and double-clicking a setup script — the README walks through every step.
Does this work for any ticker?
The workbooks work for any public company — you just have to source the data manually. The pipeline (request access above) auto-pulls from yfinance, which covers most US-listed equities and major international tickers (NYSE, NASDAQ, LSE, TSE). For names yfinance doesn't track, both versions handle missing data gracefully.
How is this different from a free reverse-LBO spreadsheet on the internet?
Most "reverse-LBO" tools online are a single-cell formula that ignores debt schedules. This is an 8-tab IB-grade workbook with a full year-by-year debt schedule (mandatory amort, sweep, covenant tracking), returns attribution decomposition with the 30%-rule re-rate flag, sensitivity grid, and auditable formulas throughout. Methodology shares a backbone with the LBO/M&A template — same audit standards, same sell-side IC discipline. Real underwriting framework, not a back-of-envelope.
Customer support?
Email [email protected] if anything in the workbook is unclear or doesn't recompute. I read every email and respond personally. If you're stuck on a specific cell, attach a screenshot and I'll walk you through the formula. Workbook updates push back into the next release with credit if you want it.

Two ways in.

Workbooks are a free download. Pipeline is on request. Or use the browser calculator for fast iteration.

Get the workbooks ↑ Open the calculator

Universal Edition · May 2026 · License: MIT-style for personal, academic, and research use; please credit if you publish off this work. For the matching forward LBO/M&A template, see LBO & M&A Template. For other free templates, see the toolkit.