Equity Valuation Framework

Use this skill as the "rules of the game" for valuation decisions and report standardization.

Scope and role

• Purpose: transform already-fetched data into a professional valuation view.
• This skill does not fetch data.
• Upstream data should come from:
• vnstock-free-expert for company/price/ratio inputs
• nso-macro-monitor, us-macro-news-monitor, vn-market-news-monitor for macro/news context

When to trigger

• User asks: "value this stock", "is it cheap/expensive", "best stock between A/B/C", "give me bull/base/bear", "build an investment memo".
• User requests a decision-ready report, not only raw metrics.

Required input contract

{
  "ticker": "HPG",
  "as_of_date": "YYYY-MM-DD",
  "currency": "VND",
  "financials": {
    "income_statement": {},
    "balance_sheet": {},
    "cash_flow": {},
    "ratios": {}
  },
  "price_history": {
    "daily": [],
    "returns": {
      "1m": null,
      "3m": null,
      "6m": null,
      "12m": null
    }
  },
  "peer_set": ["AAA", "BBB"],
  "macro_snapshot": {},
  "news_digest": {},
  "metadata": {
    "source": "kbs|vci",
    "data_quality_notes": []
  }
}

Execution workflow (ordered)

• Validate input bundle completeness and freshness.
• Run the data quality gate and assign initial confidence.
• Select valuation modules based on available data (Multiples, DCF, sector adaptation).
• Build bull/base/bear scenarios with explicit assumptions.
• Triangulate fair value, define safety zone, and list key risks.
• Apply confidence rubric and disclose gaps that can change conclusions.
• Return the report using the required section order.

Data quality gate (must run first)

• Check freshness: state report periods and price cutoff date.
• Check completeness: identify missing key lines (revenue, EBIT, net income, CFO, debt, equity, shares).
• Check consistency: basic identity checks (assets = liabilities + equity if available).
• Mark confidence tier:
• High: complete + recent + internally consistent.
• Medium: minor gaps, valuation still usable.
• Low: major gaps; only directional view allowed.

Shared confidence rubric (required)

• High: valuation triangulation is valid (>= 2 robust methods), assumptions are explicit, and key inputs are complete.
• Medium: only one robust method is usable or moderate gaps require wider valuation ranges.
• Low: major input gaps/quality issues force directional valuation only (no precise fair-value claim).

• Confidence level.
• Which modules were actually run (Multiples, DCF, sector adaptations).
• Critical missing inputs that would most likely change fair value.

Valuation modules

1) Relative valuation (Multiples)

• Core multiples:
• P/E (earnings-based)
• P/B (capital-intensive, banks/financials)
• EV/EBITDA (operating comparison)
• Optional: EV/Sales, P/CF
• Compare across:
• peer median / percentile
• company 3-5y own history
• Normalize for one-off items when possible.
• Output:
• implied value range per multiple
• weighted relative-value estimate

2) DCF valuation

• Model setup:
• Forecast horizon: 5-10 years (default 5 if uncertain)
• Revenue growth path by scenario
• Margin path (EBIT/FCF margin)
• Reinvestment assumptions
• WACC with explicit inputs (risk-free, ERP, beta, debt cost)
• Terminal value: Gordon or exit multiple (state choice)
• Mandatory sensitivity grid:
• WACC ±100 bps
• terminal growth ±50 bps
• Output:
• base/bull/bear fair value
• sensitivity table

3) Sector-specific adaptation

• Prioritize: P/B, ROE, asset quality proxies, capital adequacy proxies, funding cost/NIM proxies.
• De-emphasize EV/EBITDA.
• Evaluate sustainability of ROE and provisioning pressure.

• Use cycle-aware assumptions:
• normalized margin, not peak margin
• conservative terminal assumptions
• Add cycle-risk note as first-class risk item.

Quality and business resilience checklist

• Moat and pricing power
• Governance and capital allocation
• Earnings quality (cash conversion, accrual risk)
• Balance-sheet risk (leverage, maturity risk)
• Cyclicality and external dependency
• Execution track record

Scenario framework (required)

• Bull: better macro + execution upside
• Base: most likely path under current conditions
• Bear: macro/industry shock + execution shortfall

• Key assumptions
• Expected fundamental trajectory
• Implied fair value range
• Probability weight (optional but preferred)

Margin of safety rule

• Define Fair Value range from module triangulation.
• Define Safety Zone below fair value (default 15-30% depending on confidence and cyclicality).
• Avoid absolute buy/sell commands.
• Use language: "appears undervalued / fairly valued / stretched" and "requires margin-of-safety discipline".

Decision policy (how to conclude)

• valuation outputs (multiples + DCF if valid)
• business quality checklist
• macro/news constraints

• Trigger to add risk (what would increase conviction)
• Trigger to reduce risk
• Invalidation (what would make the thesis wrong)
• Horizon (ngắn/trung/dài)

• Attractive (valuation discount + acceptable quality/risk)
• Watchlist (mixed signals, wait for trigger)
• Caution (valuation unsupported or risk too high)

Required report output template

• Executive Summary
• One paragraph: current valuation stance and why.
• What Data Was Used
• Source, as-of date, statement periods, peer set.
• Core Thesis (Bull / Base / Bear)
• Key drivers by scenario.
• Valuation Work
• Multiples table (current vs peer vs implied)
• DCF summary (if run)
• Sensitivity table
• Business Quality Assessment
• Checklist table with evidence lines.
• Risk Register
• Ranked risks with impact, probability, and monitoring trigger.
• Fair Value and Safety Zone
• Fair value range and margin-of-safety zone with rationale.
• Confidence and Gaps
• Confidence level and exact missing data that could change the view.
• Disclaimer
• Educational analysis only, not personalized investment advice.

Formatting standards

• Use simple language and explain terms briefly.
• State all critical assumptions explicitly.
• Distinguish facts vs assumptions vs inference.
• Do not hide data gaps; surface them early.
• Keep numbers auditable and unit-consistent (VND bn/trn, %, x).

Minimal scoring rubric (optional but recommended)

• Valuation 40%
• Quality 35%
• Momentum/Revision 15%
• Risk penalty 10%

Fail-safe behavior

• downgrade confidence
• skip fragile modules (e.g., DCF)
• deliver directional valuation only
• list exact data needed for full valuation

Trigger examples

• "Value HPG with bull/base/bear and margin of safety."
• "Compare VCB vs BID valuation and explain the thesis."
• "Prepare a structured valuation memo with sensitivity table and risk register."