WACC and Terminal Growth with Precision: Compliance‑Safe Assumptions Wording

Step 1 – Anchor the concepts: what WACC and terminal growth represent, and the compliance lens

In valuation narratives, the Weighted Average Cost of Capital (WACC) performs two roles. First, it is a translation tool: it converts future, uncertain cash flows into a present value by applying a discount rate that blends the required returns of equity holders and debt holders. Second, it is a communication device: it signals to readers how risk, capital structure, and financing costs are being weighed in the analysis. Because WACC influences headline valuation outputs (enterprise value, equity value, and the target price), the wording around its components must be accurate, neutral in tone, and traceable to observable or defensible inputs.

Terminal growth (often “g” in a DCF) expresses an assumed long‑run growth rate of free cash flow beyond the explicit forecast period. Its narrative function is to describe a steady‑state outlook that does not overreach operationally or macroeconomically. Well‑framed terminal growth language shows awareness of long‑term economic anchors (for example, developed‑market inflation and real growth) and the company’s maturity stage, without predicting outcomes. Terminal growth wording should not imply guaranteed performance; instead, it should reflect a prudent macro‑consistent assumption that aligns with the model’s cash flow profile in the terminal period.

A compliance lens applies three filters to wording:

• Precision: Name each component, state the basis, and use verbs that indicate estimation rather than certainty.
• Balance: Provide enough detail to support replication and audit, without sounding promotional or selectively disclosing non‑public information.
• Consistency: Keep terminology and magnitudes coherent across DCF, trading multiples, and sum‑of‑the‑parts (SOTP) sections. Changes in inputs should be mirrored in the language across methods.

To achieve this, use a constrained vocabulary that favors neutral, evidence‑linked verbs and avoids promissory phrasing.

• Preferred verbs and phrases: “reflects,” “is based on,” “incorporates,” “is informed by,” “is consistent with,” “assumes,” “takes into account,” “captures,” “moderates,” “aligns with,” “commensurate with,” “indicates,” “suggests,” “within a range of.”
• Caution or avoid: “will deliver,” “guarantees,” “ensures,” “proves,” “no risk,” “certain,” “cannot miss,” “assured,” “management will achieve,” “above‑market forever,” “best‑in‑class without downside,” “minimum return.”

For each WACC component, maintain a precise definition and a neutral linkage to sources or reasoning:

• Risk‑free rate: Typically derived from a sovereign yield curve of appropriate maturity and currency. Wording should indicate source and date, and acknowledge market variability.
• Equity risk premium (ERP): A market‑wide premium inferred from long‑run data or contemporaneous estimates. Clarify whether it is a regional or global ERP and ensure it is compatible with the risk‑free rate’s currency and market.
• Beta: A measure of the stock’s covariance with the market. State whether it is raw or adjusted, the estimation window, and peers or index reference as appropriate. Indicate use of a bottom‑up or regression approach without overstating certainty.
• Size/liquidity premia: Additive components that aim to capture additional return expectations for smaller or less liquid securities, when used. Justify with recognized frameworks, noting they are judgmental and subject to debate.
• Cost of debt (pre‑tax): A marginal, currency‑matched borrowing cost implied by current yields, credit spreads, or management’s capital structure objectives. Avoid implying access to financing at fixed rates in the future.
• Tax rate: The effective tax rate used to translate pre‑tax debt costs into after‑tax WACC. Specify whether statutory, blended, or normalized.
• Capital structure weights: Target or market weights should be described as consistent with observed averages or management’s communicated objectives; avoid suggesting a binding commitment.
• Terminal growth: A long‑run real‑plus‑inflation view consistent with the firm’s maturity and industry dynamics. Position it as conservative or moderate by comparison to macro anchors rather than as a promise of sustained outperformance.

Step 2 – Build compliant sentences from raw inputs and align across methods

When converting numerical inputs into prose, aim for brevity, provenance, and traceability. The goal is to help a reader understand what was assumed and why, without implying the outcome is guaranteed. Consider the following structure: state the component, the numeric input, the basis or source, and the alignment to the valuation approach.

• Risk‑free rate: “The risk‑free rate is set at 3.9%, based on the [jurisdiction] [10‑year] government bond yield as of [date], to align currency and duration with the projected cash flows.” This sentence identifies the number, attributes it to an observable market source, and connects it to the cash flow horizon.

• Equity risk premium (ERP): “We apply a 5.5% equity risk premium, informed by long‑run market estimates for [region] and consistent with the currency of the risk‑free rate.” This shows methodological consistency and avoids asserting a single “correct” ERP.

• Beta: “Equity beta is 1.1 on an adjusted basis, drawing on a bottom‑up peer set and a two‑year weekly regression as a cross‑check.” This wording indicates process and moderation without presenting beta as a fixed truth.

• Size/liquidity premia: “A 50–100 bps size/liquidity adjustment is included where relevant to capture trading depth and issuance profile; for this name, we incorporate [X] bps.” This presents a range for context and a point estimate for the model, signaling judgment and documentation.

• Cost of debt (pre‑tax): “Pre‑tax cost of debt is 6.0%, reflecting current spreads implied by the firm’s credit profile and currency of borrowing.” This avoids implying a contractual borrowing rate and places the input in market terms.

• Tax rate: “An effective tax rate of 24% is used to translate pre‑tax to after‑tax costs, calibrated to normalized geographic mix.” This indicates normalization rather than year‑specific noise.

• Capital structure weights: “We weight costs by a target capital structure consistent with the firm’s historical average leverage and peer practice.” If you state numbers, do so plainly and keep them consistent with the model.

• Terminal growth: “Terminal growth is set at 2.0%, anchored to long‑run inflation plus modest real growth for the firm’s end markets.” This locates g within macro context rather than firm‑specific ambition.

Once these sentences are established in the DCF section, echo them appropriately in the multiples and SOTP sections to maintain model‑to‑message alignment.

• DCF alignment: “The base‑case DCF uses a WACC of [x.x%], derived from a 3.9% risk‑free rate, a 5.5% ERP, a 1.1 beta, the stated size/liquidity adjustment where applicable, and a 6.0% pre‑tax cost of debt (24% tax rate). Terminal growth is 2.0%.” This compact recap enables auditability.

• Multiples alignment: “The implied DCF multiples are cross‑checked against peer EV/EBITDA and P/E ranges; the DCF’s discount rate and terminal growth yield valuation levels that are consistent with the midpoint of the peer distribution when normalized for margin mix and growth.” This prevents conceptual drift between narratives.

• SOTP alignment: “Segment‑level discount rates vary within a narrow band around the group WACC to reflect business mix; terminal value assumptions by segment are constrained to macro‑consistent ranges. Aggregated SOTP outputs are reconciled to the consolidated DCF and peer multiples.” This makes clear that the sum and the whole are coherent.

The key is to avoid rewriting assumptions in different ways across sections. The same numbers should drive the same story: the WACC reflects market conditions and the firm’s risk profile; terminal growth reflects a prudent long‑term view; the outputs agree with what peers and segment economics imply.

Step 3 – Articulate sensitivities and deltas with non‑promissory, quantified language

Sensitivity language should quantify direction and magnitude while avoiding certainty. Use verbs that describe relationships rather than forecasts. Introduce ranges and increments that readers can reconcile to standard sensitivity tables.

• WACC sensitivity: “Valuation is sensitive to the discount rate. A +50 bps change in WACC typically reduces the DCF equity value by approximately [x–y]%, holding operating assumptions constant. This effect reflects the compounding impact of a higher discount rate on both the explicit period and terminal value.” The wording highlights dependence without implying inevitability.

• Terminal growth sensitivity: “A +50 bps change in terminal growth generally increases the DCF equity value by approximately [x–y]%, given the model’s terminal value weight. This is consistent with the steady‑state formula linking g to the terminal cash flow level.” Again, avoid suggesting that higher g is attainable; focus on mechanics.

• Cross‑method triangulation: “The target price range is informed by DCF sensitivities and cross‑checked against peer multiples. The DCF midpoint aligns with the median peer EV/EBITDA when applying normalized margins; higher WACC/low g cases correspond to the lower end of the multiples range.” This language connects methods and clarifies how deltas shift positioning.

• Drivers and deltas phrasing: Prefer “is consistent with,” “suggests,” “indicates,” “moves toward,” “shifts the valuation toward,” “narrowly exceeds,” “sits within,” “moderates the uplift,” “captures downside,” over “proves,” “guarantees,” “ensures,” or “locks in.”

Quantification should be transparent but framed as model‑based: “Model sensitivities indicate,” “our base‑case tables show,” “holding other inputs constant,” “mechanically implies,” and “within the modeled range.” This signals that the figures are outputs of chosen assumptions, not promises of performance.

For segment‑level SOTP sensitivities, state aggregation and range logic: “Segment discount rates vary by ±100 bps around group WACC to reflect risk differentials. A +100 bps adjustment to [higher‑risk segment] reduces its indicated value by [x–y]%, resulting in a [x–y]% change to the consolidated SOTP.” This approach preserves internal consistency and keeps the focus on relative risk.

When linking sensitivities to target price updates, avoid causal claims that exceed the model’s scope. Prefer: “The revised target reflects updated market inputs to the risk‑free rate and credit spreads, which increase WACC by [x] bps; the resulting DCF output moves the midpoint of our triangulated range to [value], still consistent with peer multiples.” This explains a change and shows method alignment.

Step 4 – Practice and self‑check: drafting workflow and compliance checklist

A disciplined drafting workflow improves clarity and reduces compliance risk. Begin by freezing the numeric inputs, then write one sentence per WACC component using the preferred verbs. After that, compose a single consolidation sentence for the DCF, followed by echo sentences for multiples and SOTP. Finally, draft two sensitivity statements: one for WACC and one for terminal growth. Read across all sections to ensure consistent numbers, terms, and tone.

Use this compliance checklist to self‑audit the wording:

• Component completeness: Have you named each WACC component explicitly—risk‑free rate, ERP, beta, size/liquidity adjustment (if any), pre‑tax cost of debt, tax rate, and capital structure weights—and stated the terminal growth? Are the currency, market, and maturities aligned?
• Source clarity: Does each number reference a recognizable source or method (market yields, peer analysis, credit spreads, published ERP estimates) without implying privileged information?
• Neutral verbs: Are you using “reflects,” “is based on,” “incorporates,” “is consistent with,” “assumes,” “captures,” and similar neutral verbs? Have you removed promissory verbs such as “guarantees” and “ensures”?
• Range awareness: Where appropriate, have you acknowledged reasonable ranges (e.g., size/liquidity premia, beta estimation windows) while still providing a point estimate for modeling?
• Cross‑method consistency: Do the DCF, multiples, and SOTP narratives reference the same risk posture and macro anchors? Is there any numeric drift between sections?
• Sensitivity framing: Do sensitivity statements specify direction and approximate magnitude while clearly stating that other inputs are held constant? Do they avoid implying certainty or selective disclosure?
• Macro anchor discipline for g: Is terminal growth justified relative to long‑run inflation and industry maturity, without suggesting indefinite outperformance?
• Tax and capital structure: Are the tax rate and leverage description consistent with how you computed after‑tax WACC, and do they avoid implying binding commitments or fixed future financing terms?
• Transparency of changes: If the target price changed from a prior report, is the explanation traced to updated market inputs or model revisions rather than to implied promises about future results?
• Readability: Are sentences concise, free from jargon where possible, and structured so a non‑specialist can follow the logic from inputs to valuation outputs?

Embedding these practices leads to prose that is defensible, replicable, and consistent with regulatory expectations. The reader can see what you assumed, why those assumptions are reasonable, how they fit together across DCF, multiples, and SOTP, and how changes to WACC or terminal growth would move the outputs. The tone remains analytical and balanced, avoiding promissory or overly certain language. Ultimately, this model‑to‑message discipline supports professional credibility: you demonstrate that each number has an origin, each sentence has a purpose, and each valuation method corroborates the others within a coherent, compliance‑safe framework.