plugins/wealth-management/skills/qualitative-valuation/SKILL.md
Assess business quality, competitive positioning, and sustainability of value creation beyond financial models. Use when the user asks about economic moats, competitive advantages, Porter's Five Forces, management quality, ESG integration, or business model analysis. Also trigger when users mention 'does this company have a moat', 'switching costs', 'network effects', 'brand value', 'management track record', 'capital allocation', 'insider ownership', 'red flags', or ask whether a company's advantage is durable.
npx skillsauth add joellewis/finance_skills qualitative-valuationInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
An economic moat is a structural advantage that protects a company's profits from competition. Five sources:
A moat claim is only as strong as its evidence. Do not award moat sources based on narrative — use the rubric below.
Anchor every claim in observable results, with retention and realized pricing as the strongest evidence:
| Claim | Qualifying evidence | Disqualifying signs | |-------|--------------------|---------------------| | Pricing power | Realized price increases at or above inflation with stable volumes and retention; gross margin held or expanded through input-cost cycles | Price increases followed by churn spikes; persistent discounting to hold share | | Switching costs | Gross retention >90% (>95% for enterprise) or net revenue retention >100%; multi-year contracts; implementations measured in quarters; deep data/workflow integration | High churn; month-to-month terms; easy data export and low migration cost | | Network effects | Unit economics measurably improve with scale (take rates, engagement, liquidity per user); winner-take-most share dynamics | User growth without any engagement, pricing, or cost benefit | | Brand (intangible asset) | Sustained price premium over comparable products for years | Awareness without a premium; growth dependent on promotional spend | | Cost advantage | Margins persistently above peers, traceable to scale, process, or resource access | One-off cost cuts; margin gap explained by product mix | | Management quality | Multi-year ROIC > WACC; buybacks executed below subsequent intrinsic value; acquisitions that met stated return targets | Serial dilutive M&A; buybacks concentrated at price peaks; recurring guidance misses |
Translate qualitative conclusions into explicit adjustments to discount rate, fade period, or terminal assumptions in quantitative valuation. These ranges are judgment calibrations, not formulas — document the specific evidence behind each adjustment:
| Finding | Calibrated adjustment | |---------|----------------------| | Wide-moat evidence (2+ reinforcing, retention-backed sources) | Discount rate -0.5 to -1.0pp, or terminal multiple +1-2 turns, or extend the above-WACC return fade to 15-20 years | | Narrow moat (one evidenced source) | Fade above-WACC returns over ~10 years; no discount-rate change | | No moat | Fade returns to WACC by terminal year; terminal growth at or below inflation | | Confirmed pricing power | Hold or modestly expand forecast margins; resist mean-reverting them prematurely | | Governance red flags (see checklist) | Discount rate +0.5 to +1.5pp, haircut management guidance, or walk away | | Material unmitigated ESG/regulatory exposure | Discount rate +0.5 to +1.5pp, or (often more transparent) probability-weight an impaired-earnings scenario | | Key-person or succession risk | Discount rate +0.25 to +0.75pp |
If combined adjustments exceed roughly 2pp on the discount rate in either direction, the qualitative overlay is driving the valuation — re-examine the base-case cash flow assumptions instead of stacking adjustments.
Any single flag warrants deeper investigation before relying on a valuation model:
Given:
Assess: Moat sources and width, using the evidence rubric
Solution:
Assessment: Narrow-to-wide moat. One moat source, but with unusually strong retention evidence; durability 15-20+ years barring a technology shift. Valuation-input mapping: extend the above-WACC return fade toward 15-20 years and hold forecast margins, but skip the full wide-moat discount-rate reduction because there is no second reinforcing source.
Given: Base cost of equity 9.0%. The company operates in a high-carbon industry with no transition plan; pending carbon-tax legislation could reduce EBIT by 15%. Governance is strong: independent board, aligned compensation, no red flags.
Calibrate: Adjusted cost of equity
Solution:
Adjusted cost of equity = 9.0% + 1.5% - 0.25% = 10.25%
Alternative (often more transparent): keep the 9% discount rate and probability-weight a scenario in which EBIT falls 15% when the carbon tax passes. Both approaches capture the same risk; do not apply both at once.
tools
Design, build, and optimize dashboards for RIA practice management with AUM tracking, revenue analytics, and KPI frameworks. Use when the user asks about tracking firm-level metrics, monitoring advisor productivity, measuring organic growth rate, analyzing client retention and attrition, building executive or branch manager views, setting up exception alerts for NIGO and operational items, benchmarking against industry peers, or designing role-based dashboard access. Also trigger when users mention 'how is the practice doing', 'revenue per advisor', 'client attrition', 'net new assets', 'effective fee rate', 'practice benchmarking', 'AUM growth decomposition', or 'advisor capacity'.
testing
Model, forecast, and interpret volatility using time-series models and options-implied measures. Use when the user asks about EWMA, GARCH models, implied volatility, volatility surfaces, volatility term structure, or the VIX. Also trigger when users mention 'volatility smile', 'volatility skew', 'realized vs implied vol', 'volatility risk premium', 'vol clustering', 'mean-reverting volatility', 'options pricing inputs', 'RiskMetrics', 'decay factor', or ask how to forecast future volatility for risk management.
testing
Execute a complete tax-loss harvesting workflow from candidate identification through post-harvest monitoring. Use when the user asks about finding TLH candidates, gain/loss budgeting, replacement security selection, wash-sale compliance, or harvest execution planning. Also trigger when users mention 'unrealized losses in my portfolio', 'swap ETFs for tax purposes', 'harvest losses before year-end', 'substantially identical security', 'wash-sale window', 'NIIT offset', 'loss carryforward', or ask how much tax they can save by harvesting.
testing
Maximizes after-tax returns through strategic asset location, gain/loss management, and withdrawal sequencing. Use when the user asks about asset location, Roth conversions, tax-efficient withdrawals, tax lot selection, or charitable giving with appreciated securities. Also trigger when users mention 'which account should I hold bonds in', 'tax drag', 'Roth vs Traditional', 'RMD planning', 'bracket stuffing', 'HIFO vs FIFO', or ask how to minimize taxes on investments. For tax-loss harvesting execution and wash-sale mechanics, see the tax-loss-harvesting skill.