What would improve the case?
Pricing power, product mix, profitable demand and cash conversion.
A–Z / F · Global equities
← Research portfolioFerrari
Does business quality justify the valuation premium?
My research view at cutoff
High-quality business, valuation-sensitive entry. I would not infer a sell rating from the Porsche scenario. A stronger valuation conclusion requires a matched-date luxury-peer comparison and explicit growth assumptions.
Key finding22.03× EV/EBITDA versus Porsche’s 9.48×: the €144.29 peer scenario shows dependence on retaining a premium.
| Metric | Ferrari | Porsche AG |
|---|---|---|
| P/E | 37.30× | 44.89× |
| EV/EBITDA | 22.03× | 9.48× |
| TTM EBITDA / net profit | 1.74× | 5.65× |
Why P/E and EV/EBITDA point in different directions.
Porsche’s TTM net profit is small relative to EBITDA: approximately €843m versus €4,765m, against Ferrari’s €1,636m and €2,847m. Differences below EBITDA, net debt and equity value affect P/E, so a lower EV/EBITDA does not force a lower P/E.
I use Porsche to test an automotive valuation discount. It is not a clean substitute for Ferrari’s luxury positioning. Hermès and LVMH offer useful brand/pricing-power perspectives, but their product mixes and capital requirements differ too. A fair-value case needs matched-date inputs rather than a pooled multiple assembled from unlike periods.
What could weaken it?
Luxury demand, multiple compression, execution and the comparability of Porsche’s financing and control structure.
Contribution & method.
My research, Python analysis and original notebook charts. The downloadable Excel comps workbook extends the notebook’s calculations.
Market cutoff 9 October 2026. Financials FY2020–FY2025 and H1 2026. Euro valuation; US-listed return comparison. Porsche is an automotive stress peer, not a clean luxury-business equivalent: ownership, cyclicality, financing and capital intensity differ. Low earnings relative to EBITDA help explain Porsche’s higher P/E despite lower EV/EBITDA. Hermès and LVMH are relevant luxury comparators, but no unsourced multiples are inserted. The model is a comps/sensitivity exercise, not a DCF.
Risk-free assumption: 2.86% historical and 3.80% YTD stock-risk proxies; WACC is a separate estimated 7.32%.
Sources and common conventions →Read or review the work.
The portable notebook reviews the dated summary inputs offline. The linked original repository contains the full workflow.