Analyzing Fairness Opinion Valuations

SkillCommerce & finance

Evaluates fairness opinion methodologies across DCF, trading comps, and precedent transactions for board-level decisions. Use when reviewing fairness opinions, preparing board materials, or analyzing transaction fairness.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Analyzing Fairness Opinion Valuations skill

What this skill tells your AI

The instructions your AI receives, as published by casemark/skills in skills/capital/analyzing-fairness-opinion-valuations/SKILL.md and read by ahel’s review.

When To Use

  • Reviewing a fairness opinion delivered by an investment bank in connection with a merger, acquisition, going-private transaction, or related-party deal
  • Preparing board or special committee materials that summarize or critique valuation analyses
  • Comparing valuation ranges across methodologies (DCF, comparable companies, precedent transactions) to assess whether an offered price falls within a reasonable band
  • Evaluating whether the opinion provider's methodology, assumptions, and data sources are appropriate for the specific transaction context
  • Conducting a second-look analysis for litigation support (e.g., appraisal proceedings, duty-of-care challenges)

Inputs To Gather

  • Fairness opinion letter and supporting presentation — the full deliverable from the opinion provider, including appendices
  • Transaction terms — purchase price (per-share or aggregate), consideration mix (cash, stock, earnout), collar or walk-away provisions
  • Target company financials — historical income statements, balance sheets, and cash flow statements (3–5 years); management projections if available
  • Comparable company set used — tickers, selection rationale, trading multiples applied (EV/EBITDA, EV/Revenue, P/E)
  • Precedent transaction set used — deal list, multiples paid, premiums to unaffected price
  • DCF assumptions — projection period, terminal value approach (perpetuity growth vs. exit multiple), WACC components (beta, equity risk premium, cost of debt, capital structure)
  • Engagement letter / fee structure — whether the advisor's fee is contingent on deal completion (potential conflict indicator)
  • Market context — index levels, sector performance, and volatility environment at valuation date

Workflow

  1. Map the valuation summary — Extract the implied per-share or enterprise value range from each methodology. Build a consolidated "football field" chart showing how ranges overlap relative to the offer price.

  2. Assess the DCF analysis

    • Verify that projections are management-sourced or, if banker-adjusted, that adjustments are disclosed and justified.
    • Check the discount rate build-up: confirm beta source (raw vs. adjusted, peer median vs. target-specific), equity risk premium vintage, size premium inclusion, and debt cost assumptions. [VERIFY] whether the WACC falls within a defensible range for the target's industry and risk profile.
    • Evaluate terminal value: for perpetuity-growth models, confirm the long-term growth rate relative to GDP and industry norms; for exit-multiple models, confirm the multiple is anchored to a supportable comp set.
    • Test sensitivity tables — do the presented ranges capture reasonable bull/bear scenarios, or are they artificially narrow?
  3. Evaluate trading comparables

    • Review peer selection criteria (SIC/GICS codes, revenue size, margin profile, growth rate, geographic mix). Flag any inclusions or exclusions that appear to skew the range.
    • Confirm which multiples are used and whether they are calculated on a trailing, forward, or calendarized basis. Note the reference date.
    • Check for outlier treatment — was any comp excluded or adjusted, and is the rationale transparent?
  4. Evaluate precedent transactions

    • Confirm that deals are relevant by vintage (typically within 3–5 years), sector alignment, and transaction type (strategic vs. financial sponsor).
    • Distinguish between announced and completed transactions; note any deals that were later terminated.
    • Assess whether premiums paid are measured against unaffected share prices and whether appropriate look-back periods (1-day, 30-day VWAP) are used.
  5. Identify conflicts and process issues

    • Determine whether the opinion provider also served as a financing source, had prior advisory relationships, or earns a success fee. These do not invalidate the opinion but must be weighed.
    • Check whether a special committee retained independent advisors separately from company management.
  6. Synthesize and opine

    • Summarize where the offer price sits relative to each methodology's range (below midpoint, at midpoint, above midpoint).
    • Highlight any methodology whose range does not capture the offer price — this is a red flag requiring explanation.
    • Identify the key swing assumptions that, if adjusted, would move the valuation range materially.

Output

Produce a structured analysis memo containing:

  • Executive summary — one-paragraph conclusion on whether the valuation work supports the fairness determination, with caveats
  • Methodology comparison table — columns for each valuation approach, rows for implied low/mid/high value, offer price marked
  • DCF deep-dive — discount rate build-up table, projection summary, terminal value analysis, sensitivity matrix critique
  • Comps and precedents critique — peer/deal selection assessment, multiple range analysis, outlier flags
  • Conflict and process flags — fee structure, dual roles, committee independence observations
  • Key assumptions sensitivity — the 3–5 assumptions with the largest impact on valuation range, with directional commentary
  • [VERIFY] items — consolidated list of data points or assumptions requiring independent confirmation

Quality Checks

  • Every valuation range cited traces to a specific page or exhibit in the source opinion
  • Discount rate components are individually sourced and cross-checked against market data providers (Bloomberg, Kroll/Duff & Phelps Cost of Capital Navigator) [VERIFY]
  • Comparable company and precedent transaction sets are tested for cherry-picking — omissions of obvious peers are flagged
  • Sensitivity ranges are wide enough to capture realistic downside/upside scenarios; artificially tight ranges are called out
  • Conflict disclosures from the engagement letter are reflected in the process flags section
  • The analysis avoids rendering a legal conclusion on "fairness" — it evaluates the financial methodology, not the legal standard of review (entire fairness, business judgment rule) [VERIFY] applicable standard based on jurisdiction and transaction type

Signals

GitHub stars
41
Forks
15
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
analyzing-fairness-opinion-valuations
Source
github.com/casemark/skills