openai/precedent-transactions

Build a precedent transactions analysis for the company named in the user's request. If no ticker or company is provided, ask for one before proceeding.

This is the third pillar of valuation (alongside trading comps and DCF) — it answers: what have acquirers actually paid for businesses like this one? The output is two tables: comparable M&A transactions with deal multiples, and the subject company's own acquisition history.

Before starting, read ../data-access.md for data access methods and ../design-system.md for formatting conventions. Follow the data access detection logic and design system throughout this skill.

Follow these steps:

1. Company Lookup

Look up the company by ticker using discover_companies. Capture:

• company_id
• latest_calendar_quarter — anchor for all period calculations below (see ../data-access.md Section 1.5)
• latest_fiscal_quarter
• Firm name for report attribution (default: "Daloopa") — see ../data-access.md Section 4.5

Identify:

• Full legal company name
• Primary stock exchange and reporting currency
• Country of domicile and primary operations
• Industry and sub-sector
• Approximate revenue and EBITDA scale (to calibrate comparable deal sizing)

2. Subject Company Financials

Calculate 4 quarters backward from latest_calendar_quarter. Pull from Daloopa:

• Revenue (compute trailing 4Q / LTM total)
• EBITDA (compute trailing 4Q; if not available, use Operating Income + D&A, label "(calc.)")
• Operating Income
• Net Income
• Free Cash Flow (OCF - CapEx, label "(calc.)")

These serve as the reference point for comparing deal multiples — what would an acquirer be paying relative to this company's current financials?

3. Identify Comparable Precedent Transactions

Find 8-15 completed M&A transactions from the last 7-10 years involving target companies comparable to the subject. "Comparable" means:

• Same industry and sub-sector
• Similar business model (e.g., SaaS, semiconductor IP, consumer internet, industrials)
• Roughly comparable scale — within ~0.5x-4x of the subject's revenue
• Completed transactions only (not rumored, not pending)

Research sources in priority order:

1. SEC EDGAR (for US targets) — SC TO, DEFM14A, 8-K filings disclose EV and deal terms
2. Equivalent regulators for non-US targets: FCA (UK), EDINET (Japan), HKEx (Hong Kong), SEDAR+ (Canada), ASX (Australia)
3. Official investor relations press releases from acquirer or target
4. Reputable financial news: Reuters, Bloomberg, Wall Street Journal, Financial Times

Use web search to identify deals: "{industry} acquisitions {sub-sector} last 10 years", "{TICKER} comparable M&A transactions", "{sector} deal comps precedent transactions".

Do NOT use: finance blogs, Seeking Alpha, Reddit, anonymous wiki contributions, or aggregators without a traceable primary source.

For each transaction, capture:

• Announcement date
• Acquirer name
• Target name
• Transaction Enterprise Value
• Deal consideration (All Cash / All Stock / Cash + Stock)
• Source (press release URL, SEC filing, or regulatory filing)

4. Source Target Financials via Daloopa

For each target company in the precedent transactions table, source LTM Revenue and EBITDA from Daloopa:

1. Look up the target using discover_companies with the target's ticker or name
2. Find relevant series using discover_company_series with keywords ["revenue", "EBITDA"] and the appropriate period (the last complete fiscal year before the deal announcement)
3. Pull the data using get_company_fundamentals with the discovered series IDs
4. For EBITDA, look for series containing "Adjusted EBITDA", "EBITDA", or fall back to "Operating Income" + D&A
5. If a target is not in Daloopa (e.g., pre-IPO targets, private companies), fall back to SEC filings, press releases, or regulatory filings

Daloopa is the primary source. Only fall back to other sources when a target is genuinely unavailable in the database.

5. Compute Deal Multiples

For each transaction where both EV and financials are available:

• EV/Revenue = Transaction EV ÷ LTM Revenue
• EV/EBITDA = Transaction EV ÷ LTM EBITDA
• Round to one decimal, append "x"
• If a figure cannot be sourced, mark as N/A — do not estimate

Compute summary statistics (excluding N/A values):

• 75th Percentile
• Average (bold)
• Median (bold)
• 25th Percentile

If fewer than 3 valid data points exist for a multiple, note that the statistic is not meaningful.

6. Subject Company's Acquisition History

Find deals where the subject company itself was the acquirer. Sources: company IR page, SEC 8-K or equivalent filings, Reuters/Bloomberg/WSJ.

For each acquisition, capture:

• Date
• Target name
• Deal value (if disclosed)
• Consideration (Cash / Stock / Mix)
• Strategic rationale (one sentence from press release or filing)

7. Implied Valuation for Subject Company

Apply the precedent transaction multiples to the subject's current financials:

| Methodology | Percentile | Multiple | Subject LTM Metric | Implied EV | |---|---|---|---|---| | EV/Revenue | Median | XX.Xx | $XXX | $XXX | | EV/Revenue | 25th-75th | XX.Xx-XX.Xx | $XXX | $XXX-$XXX | | EV/EBITDA | Median | XX.Xx | $XXX | $XXX | | EV/EBITDA | 25th-75th | XX.Xx-XX.Xx | $XXX | $XXX-$XXX |

Convert implied EV to implied equity value (EV - Net Debt) and implied share price where market data is available (see ../data-access.md Section 2). Compare to current market price.

Context matters more than precision:

• Precedent transaction multiples are snapshots from specific deal contexts (competitive auctions, strategic premiums, distressed sales). Note which deals had unusual dynamics.
• Control premiums are embedded in these multiples — a public market investor should not expect to realize the full precedent transaction value unless a takeout actually happens.
• If the current market cap is well below precedent transaction implied value, that's a signal of takeout optionality, not necessarily undervaluation.

8. Deal Environment Commentary

Search filings and news for context on the M&A environment:

• Search: "{industry} M&A outlook {current_year}" — deal activity trends
• Search: "{TICKER} acquisition target rumors" — is the subject itself a takeout candidate?

Summarize in 3-5 bullets:

• Is deal activity in this sector accelerating or declining?
• What are typical premiums being paid (control premium trends)?
• Are strategic buyers or financial sponsors (PE) driving activity?
• Any regulatory headwinds to deals in this space (antitrust scrutiny)?
• Is the subject company a plausible acquisition target? Why or why not?

9. Save Report

Save to reports/{TICKER}_precedent_transactions.html using the HTML report template from ../design-system.md. Write the full analysis as styled HTML with the design system CSS inlined. This is the final deliverable — no intermediate markdown step needed.

The report should include interactive features:

• Clickable acquirer names in Table 1 that open a modal showing all source links for that transaction (press release, SEC filing, Daloopa data links). Implement with data- attributes and safe DOM methods (createElement, textContent, appendChild) — never innerHTML.
• Consideration badges styled inline: All Cash (green background), All Stock (purple background), Cash + Stock (amber background).

Structure the report with these sections:

<h1>{Company Name} ({TICKER}) — Precedent Transactions Analysis</h1>
<p>Generated: {date}</p>

<h2>Summary</h2>
{2-3 sentences: What do precedent transactions imply for this company's valuation? How does it compare to the current market price?}

<h2>Subject Company Overview</h2>
{Exchange, currency, industry, LTM Revenue and EBITDA with Daloopa citations}
{Note: "Revenue and EBITDA sourced from Daloopa where available"}

<h2>Selected Precedent Transactions</h2>
<table>
| Date | Acquirer | Target | EV ($M) | LTM Rev ($M) | LTM EBITDA ($M) | EV/Rev | EV/EBITDA | Consideration |
{data rows with Daloopa-cited financials, footnote superscripts, clickable acquirers}
| 75th Percentile | | | | | | XX.Xx | XX.Xx | |
| **Average** | | | | | | **XX.Xx** | **XX.Xx** | |
| **Median** | | | | | | **XX.Xx** | **XX.Xx** | |
| 25th Percentile | | | | | | XX.Xx | XX.Xx | |
</table>

<h2>Implied Valuation</h2>
<table>
| Methodology | Multiple | Subject Metric | Implied EV | Implied Equity | Implied Price | vs Current |
{valuation bridge using median and range multiples}
</table>

<h2>{Company Name} Acquisition History</h2>
<table>
| Date | Target | Deal Value | Consideration | Strategic Rationale |
{company's own M&A deals}
</table>

<h2>Deal Environment</h2>
<ul>{3-5 bullets on sector M&A trends, control premiums, takeout potential}</ul>

<h2>Sources</h2>
{Numbered footnote list — each deal with press release link, SEC filing, Daloopa data links}
{Data sourced from Daloopa attribution}

All financial figures from Daloopa must use citation format: <a href="https://daloopa.com/src/{fundamental_id}">$X.XX million</a>

Tell the user where the HTML report was saved.

Highlight: what precedent transactions imply about the company's takeout value, how it compares to the current market price, and whether the sector M&A environment supports deal activity.