analyzing-fairness-opinion-valuations
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.
Best use case
analyzing-fairness-opinion-valuations is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using analyzing-fairness-opinion-valuations should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/analyzing-fairness-opinion-valuations/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How analyzing-fairness-opinion-valuations Compares
| Feature / Agent | analyzing-fairness-opinion-valuations | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Analyzing Fairness Opinion Valuations ## 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
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