npx claudepluginhub daloopa/plugin --plugin daloopaThis skill uses the workspace's default tool permissions.
Build a trading comparables analysis for the company specified by the user: $ARGUMENTS
Values companies relative to peers using price multiples (PE, PBV, EV/EBITDA, EV/Sales) via four-step framework with peer comparison and sector regression approaches.
Builds comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel format for public company valuation and peer benchmarking.
Estimates intrinsic value of stocks and companies using DCF, dividend discount models, comparable multiples, and residual income. Useful for fair value analysis, sensitivity testing, and over/undervaluation checks.
Share bugs, ideas, or general feedback.
Build a trading comparables analysis for the company specified by the user: $ARGUMENTS
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:
Look up the company by ticker using discover_companies. Capture:
company_idlatest_calendar_quarter — anchor for all period calculations below (see ../data-access.md Section 1.5)latest_fiscal_quarter../data-access.md Section 4.5Based on the company's business model, sector, size, and competitive landscape, identify 5-10 comparable companies. Consider:
Prioritize relevance over size matching. A direct competitor at a different scale is more useful than a similar-sized company in a different industry.
List the peer tickers and briefly justify each selection (1 sentence).
Calculate 4 quarters backward from latest_calendar_quarter. Pull from Daloopa for the target company:
For each peer, get trading multiples and current quote (see ../data-access.md Section 2):
If market data is unavailable, note that peer multiples cannot be sourced and provide a framework for manual completion.
If a peer ticker fails (delisted, no data), drop it and note why.
For each peer that is available in Daloopa:
latest_calendar_quarter. Pull revenue, operating income, net income for those periods.For peers not in Daloopa, rely on market data multiples only (see ../data-access.md Section 2) and note the data source limitation.
For each company (target + all peers available in Daloopa), discover and pull company-specific operational KPIs. Use the sector taxonomy below to know what to search for:
Pull the same 4 calendar quarters for each peer. Not all peers will have the same KPIs — build a sparse matrix and note which are comparable across the group vs company-specific.
Add KPI columns to the comps table in Section 6 where comparable metrics exist (e.g., subscriber growth, ARPU, units alongside P/E and EV/EBITDA). This shows whether valuation premiums are supported by operational outperformance.
Create the main comparables table with these columns: | Company | Ticker | Mkt Cap | EV | P/E | Fwd P/E | EV/EBITDA | P/S | Rev Growth | Op Margin | Net Margin | FCF Yield |
Sort by market cap descending. Include:
Apply peer group median and mean multiples to the target's fundamentals:
| Methodology | Peer Median Multiple | Target Metric | Implied Value |
|---|---|---|---|
| P/E | XX.Xx | $X.XX EPS | $XXX |
| EV/EBITDA | XX.Xx | $XXX EBITDA | $XXX |
| P/S | XX.Xx | $XXX Revenue | $XXX |
| FCF Yield | X.X% | $XXX FCF | $XXX |
For each:
Compute range (min to max implied price) and central tendency.
If consensus estimates are available (see ../data-access.md Section 3):
If consensus data is not available, use trailing multiples only and note the limitation.
Assess whether the target trades at a premium or discount to peers:
Be honest about whether the premium is truly justified:
Save to reports/{TICKER}_comps.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.
Structure the report with these sections:
<h1>{Company Name} ({TICKER}) — Comparable Companies Analysis</h1>
<p>Generated: {date}</p>
<h2>Summary</h2>
{2-3 sentences: Where does the company trade relative to peers? Is it cheap or expensive and why?}
<h2>Peer Group Selection</h2>
<table>
| Peer | Ticker | Rationale |
{table with justification for each peer}
</table>
<h2>Comparables Table</h2>
<table>
| Company | Ticker | Mkt Cap | P/E | Fwd P/E | EV/EBITDA | P/S | Rev Growth | Op Margin |
{full comps table with target highlighted}
| **Peer Median** | | | XX.Xx | XX.Xx | XX.Xx | XX.Xx | X.X% | X.X% |
| **Peer Mean** | | | XX.Xx | XX.Xx | XX.Xx | XX.Xx | X.X% | X.X% |
| **{TICKER}** | | | **XX.Xx** | **XX.Xx** | **XX.Xx** | **XX.Xx** | **X.X%** | **X.X%** |
</table>
<h2>Target vs Peer Premium/Discount</h2>
<table>
| Multiple | Target | Peer Median | Premium/Discount |
{table showing where target is rich/cheap}
</table>
<h2>Implied Valuation</h2>
<table>
| Methodology | Multiple | Target Metric | Implied Price | vs Current |
{table with implied values}
</table>
<table>
| **Valuation Range** | **Low** | **Median** | **High** |
| Implied Price | $XXX | $XXX | $XXX |
| vs Current Price | -X% | +X% | +X% |
</table>
<h2>Premium/Discount Justification</h2>
{Analysis of whether current premium/discount is warranted}
<h2>Peer Operational KPIs</h2>
<table>
| KPI | {TICKER} | Peer 1 | Peer 2 | ... | Peer Median |
{KPI comparison table — sparse where data unavailable, footnoted}
</table>
<h2>Key Observations</h2>
<ul>{3-5 bullet points on relative valuation, standout metrics, peer group dynamics, KPI differentiation}</ul>
All financial figures from Daloopa must use citation format: <a href="https://daloopa.com/src/{fundamental_id}">$X.XX million</a>
Tell the user where the HTML report was saved.
Highlight: where the stock trades relative to peers (premium/discount), the implied valuation range, and the most relevant multiple for this company.