bull-bear

Build a bull/bear/base case scenario framework 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:

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

2. Historical Financial Baseline

Calculate 8 quarters backward from latest_calendar_quarter. Pull:

• Revenue
• Gross Profit / Gross Margin %
• Operating Income / Operating Margin %
• EBITDA (if not reported, compute as Operating Income + D&A — label "(calc.)")
• Net Income
• Diluted EPS
• Operating Cash Flow
• CapEx
• Free Cash Flow (compute as OCF - CapEx — label "(calc.)")
• Segment-level revenue breakdowns
• Geographic revenue breakdowns

Compute trailing 4-quarter totals for revenue, EBITDA, net income, EPS, and FCF — these are the baseline the scenarios build from.

Flag any one-time items that distort quarters.

3. Key Operating KPIs

First, think about what the most important KPIs are for THIS specific company based on its business model and what drives its valuation. For example:

• SaaS/cloud: ARR, net revenue retention, RPO/cRPO, customers >$100K
• Consumer tech: DAU/MAU, ARPU, engagement metrics, installed base, paid subscribers
• E-commerce/marketplace: GMV, take rate, active buyers/sellers, order frequency
• Retail: same-store sales, store count, average ticket, transactions
• Telecom/media: subscribers, churn, ARPU, content spend
• Hardware: units shipped, ASP, attach rate
• Financial services: AUM, NIM, loan growth, credit quality metrics
• Pharma/biotech: pipeline stage, patient starts, scripts, market share

Search for those specific KPIs by name and pull them. These are the building blocks for bottoms-up scenario math.

Also pull capital allocation data: share count, buyback amounts, dividends.

4. Qualitative Research

Search SEC filings/documents across multiple queries. If any search returns empty, try alternative keywords before giving up.

• Risk factors: Try "risk", "uncertainty", "challenge"; fallback to "adverse", "headwind"
• Growth drivers: Try "growth", "opportunity", "expansion"; fallback to "momentum", "strong demand"
• Competitive dynamics: Try "competition", "market share"; fallback to "competitive"
• Management outlook: Try "outlook", "guidance", "expect"; fallback to "anticipate", "forward"
• Capital allocation: Try "repurchase", "dividend"; fallback to "buyback", "capital return"
• Macro/regulatory: Try "tariff", "regulatory"; fallback to "geopolitical", "compliance"

5. Consensus Positioning (if available)

If consensus estimates are available (see ../data-access.md Section 3), note:

• Where consensus revenue/EPS sits relative to your base case
• Whether the market is positioned closer to your bull or bear case
• Recent estimate revision trends (optimistic vs pessimistic drift)

If consensus data is not available, skip this section.

6. Construct Three Scenarios

For each scenario, build a bottoms-up revenue model showing key segment or product-level assumptions (e.g., units x ASP, subscribers x ARPU, segment growth rates). Don't just state a revenue range — show the math that gets there.

Bull Case

• Identify the most favorable realistic trajectory
• Key assumptions: revenue acceleration, margin expansion, KPI improvement, favorable macro/competitive shifts
• Quantify using historical highs and growth rates as anchors
• Show segment-level build: what needs to go right in each business line
• List specific catalysts that could drive this outcome
• Consider how capital allocation (buybacks) amplifies EPS upside

Base Case

• Extrapolate current trends forward
• Key assumptions: continuation of recent growth rates, stable margins, steady KPI progression
• This should be the "most likely" scenario grounded in the last 4-8 quarters of data
• Show segment-level build using current trend rates
• Reference historical analogs if applicable (e.g., prior product cycles, similar macro environments)

Bear Case

• Identify realistic downside risks
• Key assumptions: revenue deceleration, margin compression, KPI deterioration, competitive/macro headwinds
• Quantify using historical lows, risk factor analysis, and specific cost headwinds from filings (e.g., tariff drag, regulatory impact)
• Show segment-level build: what breaks in each business line
• List specific risks that could drive this outcome
• Consider how capital allocation behavior changes in a downturn (buybacks may accelerate at lower prices)

Probability Weighting

Don't default to 25/50/25. Assign probabilities informed by the most recent data points:

• If recent results are accelerating, weight bull higher
• If macro headwinds are intensifying, weight bear higher
• Explain your reasoning for the weighting

Be honest about which scenario is most likely. Don't default to a bullish framing or split the difference to seem balanced. If the data suggests the bear case is more probable, say so clearly. If the bull case requires multiple things to go right simultaneously, acknowledge that compounds the risk. The reader needs your honest assessment, not diplomatic equivocation.

7. Save Report

Save to reports/{TICKER}_bull_bear.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:

• Company overview and current state summary
• Historical financial data table (8 quarters, Daloopa citations, including computed EBITDA/FCF)
• Trailing 4-quarter totals as the scenario baseline
• Segment and geographic revenue tables
• KPI trends table
• Capital allocation summary (buybacks, dividends, share count)
• Three scenario sections each with:
  • Key assumptions (bulleted)
  • Bottoms-up segment revenue build
  • Implied revenue/margin/EPS trajectory
  • Implied KPI trajectory
  • Catalysts / risks specific to that scenario
• Probability-weighted summary with reasoning
• Key risk factors and growth drivers from filings (with document citations)
• Summary comparison table across scenarios
• Key swing factors section — the 3-5 variables that most determine which scenario plays out

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

Tell the user where the HTML report was saved.

Highlight: which scenario you believe is most likely and why, the key swing factors between bull and bear cases, and where you think the market is currently positioned (closer to bull, base, or bear). If the current stock price implies an overly optimistic or pessimistic scenario, flag it.