Why different valuation methods produce divergent results

Valuation methods rarely align because each captures a different perspective on value — market sentiment, strategic logic, or return constraints. Understanding these perspectives explains why the same company can be worth EUR 400m in one model and EUR 550m in another.

• Trading multiples: reflect market mood and peer positioning — your peer group selection defines the quality of your median multiple. Do the industry and business model match?

• Transaction multiples: embed control premiums and deal-specific logic — they move with capital cycles and buyer aggressiveness and include the transaction premium of each deal.

• Discounted cash flow: prices in management optimism — it ultimately depends on the assumptions of the business plan and how achievable they are.

• Leveraged buyout model: anchors valuation to a private equity fund’s minimum return expectations — defining the floor valuation based on leverage, cost of debt, and EBITDA growth.

Trading multiples — peer group selection

Trading multiples are only as credible as the peer group behind them. The real craft lies in selecting companies with matching industry exposure, geography, and profitability profile. A European mid-market industrial shouldn’t be benchmarked against a diversified U.S. conglomerate or a turnaround case — even if they share similar industry codes. Sector fit ensures comparable margin structures, while geographic fit captures local capital costs and investor sentiment. Peers operating in the same region and cycle phase trade under similar risk premia, which keeps the multiple meaningful.

The peers should share the same business model and customer group to ensure real comparability. Outliers are often loss-making or restructuring peers trading at inflated EBITDA multiples and should be excluded when valuing a healthy company. If one comp runs at a 25 % EBITDA margin and another at 5 %, that’s a signal to revisit your set. The cleanest comps combine direct industry match, geographic proximity, and similar profitability, forming a coherent and defensible peer group.

Transaction multiples — market sentiment, peer selection and deal premium

Transaction multiples capture what buyers have actually paid, blending market sentiment with strategic intent. Because they include control premiums and synergy expectations, they typically sit above trading comps but still move with the broader cycle. In hot markets, abundant capital and aggressive bidders push valuations beyond fundamentals; in downturns, tighter financing and higher risk premiums pull them back. The result reflects market mood and buyer psychology as much as intrinsic value.

The best comparables are recent, industry-matched, and structurally similar — ideally within one to two years and of the same deal type (full sale vs. minority stake). A single outlier, such as a strategic paying a 30–40 % premium, can distort the entire sample. When one transaction trades at 30x EBITDA while the rest cluster around 8–10x, it’s better to adjust or highlight the most relevant deal instead of showing an inflated average. That approach keeps the analysis credible and decision-useful rather than cosmetic.

Discounted cash flow — business plan optimism, WACC sensitivity and terminal value

DCF valuations often look the most rigorous on paper yet hide the widest room for interpretation. Because they are built on management’s business plan and discounted by a chosen WACC, small input changes can move results by ±10–30 % in enterprise value.

The key driver is the business plan itself: how aggressive are the assumptions, and how likely are all strategic initiatives to materialize? In low-rate environments, those same projections inflate valuations; in higher-rate markets, they compress just as quickly. The model’s precision is mathematical — but its accuracy depends entirely on how realistic the forecasts and discount rates are.

In practice, business plan optimism and terminal value weighting explain most of the divergence. When more than 70 % of value stems from the terminal period, you often need to extend the explicit forecast to make revenue and EBITDA development tangible. At least then, you see which targets you’re implicitly betting on. The WACC, by contrast, tends to be relatively stable — anchored by observable cost of debt and equity inputs.

The real variable is the credibility of the plan: an overly optimistic business plan means that every one of your initiatives must succeed exactly as forecast. In that case, the DCF has already priced in flawless execution, leaving zero room for error. Even a minor shortfall in growth, margin, or timing can break the valuation narrative entirely — which is why DCFs often say more about confidence than about certainty. That’s why DCFs are best treated as a narrative test of assumptions, not a single-point truth — useful for explaining valuation logic, but dangerous when used in isolation.

Leveraged buyout model — entry valuation, cost of debt, leverage and EBITDA growth

An LBO model defines valuation through the lens of investor return constraints, not intrinsic value. The analysis starts from the target IRR and works backward to determine what a buyer can afford to pay, given expected leverage, interest costs, and operating growth. Lower debt costs and higher leverage expand headroom for a premium entry valuation; when financing tightens or rates rise, that equation reverses — even a strong company’s “sponsor value” can fall well below trading or DCF levels.

In practice, entry multiple, debt capacity, and sustainable EBITDA growth are the key swing factors. Private equity funds typically model several scenarios to test whether growth materializes and how downside cases can be mitigated. If confidence in the plan is low, they apply a discount to the business plan, directly reducing entry valuation.

LBO valuations therefore form the floor of the valuation range — the price a financial sponsor can justify while still achieving its minimum return. Conservative funds often target ~15 % IRR, while aggressive ones aim for 20–25 %. The outcome reflects return thresholds, not strategic synergies — a pure function of capital structure and discipline.

Where does it leave us?

Valuation divergence is not a flaw — it’s the outcome of different lenses on the same company.

Trading and transaction multiples reflect market perception and deal momentum, DCF captures management conviction and long-term belief in the plan, and LBO models anchor financial discipline and return thresholds.

The spread between them isn’t noise; it’s information. When those methods converge, it usually means assumptions, sentiment, and capital conditions are aligned. When they don’t, the gap reveals where optimism, risk, or financing constraints are hiding. In practice, that’s what valuation work really is — not finding one “right” number but understanding why certain groups of investors might price it lower or higher compared to others.