# Tcx Valuation

> Review valuation after research evidence exists. Use for valuation method selection, assumptions, market-implied expectations, scenario ranges, sensitivity, and valuation risk.

- Skill: `monarchjuno/tcx-valuation` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add monarchjuno/tcx-valuation`
- Raw SKILL.md: https://api.skillmd.com/api/skills/monarchjuno/tcx-valuation/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: monarchjuno (https://skillmd.com/u/monarchjuno)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/monarchjuno/tcx-valuation

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# Valuation Review

Use this skill after research evidence exists and the requested universe has a supportable valuation or scenario lens.

Universe method:

- Public equity: choose DCF, comps, reverse DCF, scenario, estimate revision, or event probability methods only when the evidence supports them.
- Treat a forward per-share DCF as decision-usable when current attributable
  evidence supports the cash-flow base, reinvestment/CAPEX, working-capital
  posture, net debt or cash, diluted shares, and the relevant forecast bridge.
  Prefer audited filings or issuer disclosures for historical accounting
  facts, but allow verified OpenBB/provider-normalized fundamentals, reputable
  consensus estimates, and credible secondary evidence when provider, period,
  units, adjustments, and material conflicts are checked. Missing
  source-of-record evidence lowers confidence or widens sensitivity unless the
  unresolved input drives the conclusion. When the overall foundation is
  materially insufficient, prefer a reverse DCF or market-implied expectation
  threshold, a clearly labeled scenario screen, or abstention. Do not publish
  a precise target merely because assumptions can be entered into a model.
- For each selected method, state why it fits the business, which driver it tests, and which sensitivity would break the conclusion.
- ETF/index: focus on exposure, constituent/benchmark, factor, flow, and valuation-through-holdings logic when data exists.
- Crypto, macro, FX, rates, commodities, options, and credit-sensitive workflows require instrument-specific methods; if the installed support cannot underwrite the method, produce a screen-grade valuation frame or support gap rather than a false precision model.
- Always state current price or market anchor source/as-of when the user asks for risk/reward, target, entry, or action.

Expected output:

- Universe and valuation method fit
- Valuation method used
- Key assumptions
- Market-implied expectation check
- Scenario range
- Sensitivity points
- Method-selection limits and key sensitivity table or notes
- Valuation risk
- What would change the valuation
- Source/as-of posture, unsupported assumptions, and model/readiness label

Decision quality fields when applicable:

- `evidence_grade`, `source_freshness`, `source_quality`
- `scenario_cases`, `contrary_evidence`, `update_triggers`
- `invalidation_conditions`, `decision_readiness`, `confidence`
- `forecast_required`, `forecast_allowed`, `forecast_block_reason`
- `forecast_target`, `forecast_horizon`, `probability`, `probability_range`
- `base_rate`, `evidence_ids`, `resolution_source`, `review_date`

Role-specific quality:

- Choose methods that fit the business and available evidence; do not force a framework.
- State why each method is appropriate or limited.
- Include at least downside/base/upside scenario logic when evidence allows.
- Identify scenario inputs, cost and capacity assumptions, and modeling choices explicitly in prose.
- Distinguish model output, derived calculation, consensus/provider data, user input, and PM judgment.
- Label reverse-DCF break-even assumptions and scenario screens explicitly;
  neither becomes audited intrinsic value without the missing foundation.
- Use `not-decision-ready` when a missing current price, base case, valid
  probability, source date, or instrument-specific assumption materially
  prevents decision support. Do not downgrade solely because adequate evidence
  is provider-derived or secondary.
- State parameter sensitivity and lower confidence when the valuation range depends on fragile inputs.
- Separate valuation output from portfolio or execution recommendation.
- State what evidence would most change the range.

Write outputs under `trading/reports/valuation/`.