portfolio-review
Skill0 starsChanged 3 months agoMITView on GitHub
Review and analyze investment portfolio performance and allocation
15 other projects use a version of this.
Adopted by
Most recently taken up by
- CSPulse/customer-success-skillstheir own version, first seen Nov 8, 2026
- PatrickSUDO/fadacai-portfoliotheir own version, first seen Nov 6, 2026
- rgourley/quant-garagetheir own version, first seen Nov 1, 2026
- Shubhamkumartrichy/claude-trading-skills-indiatheir own version, first seen Nov 1, 2026
- JasmineNy/codex-skills-portfoliotheir own version, first seen Oct 20, 2026
- monellonasti/portfolio-pipelinetheir own version, first seen Oct 17, 2026
Other versions15 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 15
- digitalinnovationone/dio-agent★ 2.8ksame name
- PatrickSUDO/fadacai-portfolio★ 145same name
- Shubhamkumartrichy/claude-trading-skills-india★ 56same name
- nimadorostkar/Claude-Skills-collection★ 33same name
- Mozurok/fhorja.dev★ 10same name
- rgourley/quant-garage★ 7same name
- CSPulse/customer-success-skills★ 2same name
- ryanbaumann/fieldwork★ 2same name
- shashu10/personal-finance-skills★ 2same name
- tusharagg1/aifolimizer★ 2same name
5 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository26 other files it gives its agents.
- 10k-digestSkill
- bear-caseSkill
- catalyst-calendarSkill
- chart-masterSkill
- competitor-analysisSkill
- dcf-valuationSkill
- dividend-analysisSkill
- earnings-call-analysisSkill
- economics-analysisSkill
- financial-report-analystSkill
- full-reportSkill
- fundamental-analysisSkill
- industry-mapSkill
- insider-tradingSkill
- institutional-ownershipSkill
- options-analysisSkill
- position-ladderSkill
- report-generatorSkill
- research-bundleSkill
- result-validatorSkill
- sector-analysisSkill
- short-interestSkill
- stock-evalSkill
- stock-screenerSkill
- stock-valuationSkill
- technical-analysisSkill
The file
We split this skill into the rules it gives an agent
9 rules. 0 are common, 9 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 14 edited versions we read keep these.
9
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 11
Start with a high-level summary before diving into details:
- Distinctive: line 182
Do not repurchase the same or substantially identical security within 30 days before or after the sale.
- Distinctive: line 243
Use the factor tilts to explain return difference from benchmark.
- Distinctive: line 254
No action if drift is within tolerance band
- Distinctive: line 268
Before executing any rebalance, verify it clears the cost hurdle:
- Distinctive: line 297
Use new cash contributions to buy underweight assets first
- Distinctive: line 300
If still needed, sell overweight positions (minimize short-term gains)
- Distinctive: line 394
Before finalizing the analysis, verify:
- Distinctive: line 405
All analysis concludes with this standardized block:
“Common” is measured: kept by at least 6 in 10 of the 14 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Portfolio Review
Comprehensive portfolio analysis and optimization recommendations.
Phase 1 — Portfolio Snapshot
Start with a high-level summary before diving into details:
- Total portfolio value and cash position
- Number of holdings and average position size
- Date range of analysis
- Investor profile: risk tolerance (conservative / moderate / aggressive), time horizon, income vs. growth objective
Phase 2 — Performance Analysis
- Absolute Returns
- YTD, 1Y, 3Y, 5Y total return
- Compare against relevant benchmarks (S&P 500, Russell 2000, custom blended benchmark)
- Annualized return vs. benchmark — outperformance or underperformance in basis points
- Risk-Adjusted Returns
- Sharpe ratio (excess return per unit of total risk)
- Sortino ratio (penalizes only downside volatility)
- Calmar ratio (annualized return / max drawdown)
- Information ratio vs. benchmark
- Drawdown Analysis
- Maximum drawdown: peak-to-trough magnitude and duration
- Recovery period after each significant drawdown
- Drawdown frequency over the analysis window
- Compare portfolio drawdown vs. benchmark during market stress periods
- Volatility Metrics
- Annualized standard deviation of returns
- Beta vs. S&P 500 (market sensitivity)
- Tracking error vs. benchmark
- Upside capture / downside capture ratios
Phase 3 — Asset Allocation Review
- Current Allocation Breakdown
- Asset class weights: equities, fixed income, cash, REITs, commodities, alternatives
- Equity sub-breakdown: US large cap, US small/mid cap, international developed, emerging markets
- Compare current weights to target/policy weights — flag deviations > 5%
- Geographic Diversification
- US vs. international exposure (%)
- Country concentration risk — any single country > 20%?
- Currency exposure and hedging status
- Sector and Industry Weights
- GICS sector breakdown vs. S&P 500 sector weights
- Overweight / underweight sectors and the investment thesis behind each
- Cyclical vs. defensive balance relative to current macro environment
- Market Cap Distribution
- Large cap / mid cap / small cap split
- Growth vs. value tilt (P/E, P/B relative to benchmark)
- Quality factor exposure (ROE, balance sheet strength)
Phase 4 — Holdings Review
- Individual Position Analysis
- Position size as % of portfolio — flag any > 10% single-stock concentration
- Contribution to total return (winners vs. laggards)
- Unrealized gain/loss and holding period (tax impact)
- Position Sizing Discipline
- Largest 5 positions — are sizes justified by conviction and risk/reward?
- Smallest positions — are they too small to be meaningful?
- Kelly criterion or volatility-scaled sizing check
- Overlap and Redundancy
- Identify pairs of holdings with > 0.7 correlation
- ETF overlap analysis — holdings duplicated across ETFs
- Factor overlap: are multiple positions expressing the same single bet?
- Cost Efficiency
- Weighted average expense ratio for ETF/fund holdings
- Estimated annual trading cost drag
- Tax lot optimization — identify specific lots to sell for tax efficiency
Phase 5 — Concentration Risk Scoring
Score each concentration dimension independently, then aggregate:
Single-Stock Concentration
| Position Weight | Score | Status |
| < 5% | 0 | OK |
| 5%–10% | 1 | Monitor |
| 10%–15% | 2 | Warning |
| 15%–20% | 3 | High Risk |
| > 20% | 5 | Red Flag — immediate review required |
Sector Concentration
| Largest Sector Weight | Score | Status |
| < 20% | 0 | Diversified |
| 20%–25% | 1 | Slight tilt |
| 25%–30% | 2 | Elevated |
| 30%–40% | 3 | Warning |
| > 40% | 5 | Concentration risk — rebalance urged |
Factor Concentration
| Factor Tilt Condition | Score | Note |
| Mixed factors | 0 | Balanced |
| Mild single-factor tilt | 1 | Acceptable with thesis |
| Strong single-factor tilt (>70% one factor) | 3 | Vulnerable to factor drawdown |
| Pure single-factor portfolio (>90%) | 5 | Maximum factor risk |
Common factor concentration traps: all high-growth names (P/E > 40), all micro/small-cap, all rate-sensitive (long-duration bonds + REITs + utilities together).
Aggregate Concentration Score
- 0–2: Well-diversified
- 3–5: Moderate concentration — monitor
- 6–9: High concentration — rebalance
- 10+: Critical — urgent review
Phase 6 — Correlation & Diversification Analysis
Measuring Diversification Benefit
Portfolio volatility reduction vs. average asset volatility signals diversification quality. If portfolio vol ≈ average position vol, diversification benefit is near zero.
Diversification Ratio = (Weighted average individual vol) / (Portfolio vol)
- Ratio > 1.5: Good diversification
- Ratio 1.2–1.5: Moderate
- Ratio < 1.2: Poor — holdings move together
Pairwise Correlation Heatmap Template
For each pair of top-10 holdings, estimate 1-year rolling correlation:
AAPL MSFT GOOGL AMZN NVDA JPM XOM GLD
AAPL 1.00 0.85 0.82 0.79 0.76 0.42 0.15 -0.10
MSFT 0.85 1.00 0.84 0.80 0.78 0.41 0.14 -0.12
GOOGL 0.82 0.84 1.00 0.81 0.73 0.39 0.12 -0.09
AMZN 0.79 0.80 0.81 1.00 0.70 0.37 0.10 -0.08
NVDA 0.76 0.78 0.73 0.70 1.00 0.35 0.11 -0.07
JPM 0.42 0.41 0.39 0.37 0.35 1.00 0.48 0.05
XOM 0.15 0.14 0.12 0.10 0.11 0.48 1.00 0.30
GLD -0.10 -0.12 -0.09 -0.08 -0.07 0.05 0.30 1.00Color code: > 0.75 = HIGH (red), 0.50–0.75 = MODERATE (yellow), < 0.50 = LOW (green)
Effective Number of Positions (ENP)
ENP = 1 / sum(wi²) where wi = weight of position i
Interpretation:
- ENP ≈ actual N: equal-weight, low correlation — true diversification
- ENP << actual N: dominated by a few large/correlated positions
- Target ENP: at least 0.6 × actual number of holdings
Correlated Cluster Identification
Group holdings with pairwise correlation > 0.75 into clusters. Each cluster behaves as a single economic bet. Example clusters: Big Tech, Energy Majors, Regional Banks, Long-Duration Fixed Income.
Actionable rule: no single cluster should exceed 35% of portfolio weight.
Phase 7 — Tax-Loss Harvesting Opportunities
Identification Criteria
Screen all positions for:
- Unrealized loss > 10% of cost basis
- Position held > 30 days (avoid wash-sale complications)
- Realized gains available to offset in the current tax year
Wash-Sale Rule (30-Day Rule)
Do not repurchase the same or substantially identical security within 30 days before or after the sale. Alternatives to maintain exposure during the 30-day window: sell XOM, buy CVX; sell QQQ, buy VGT; sell one S&P 500 ETF for another.
Net Tax Benefit Calculation
Gross Tax Saving = Realized Loss × Marginal Tax Rate
Transaction Cost = (Bid-Ask Spread + Commission) × 2
Net Benefit = Gross Tax Saving − Transaction Cost
Harvest if: Net Benefit > 0 AND loss > $500 minimum thresholdTax-Loss Harvest Decision Table
| Condition | Action |
| Unrealized loss > 10%, gains to offset, loss > $500 | Harvest — sell and replace with correlated substitute |
| Unrealized loss 5–10%, gains to offset | Evaluate: transaction cost vs. tax saving |
| Unrealized loss > 10%, no offsetting gains | Hold or carry forward — harvest at year-end if gains materialize |
| Position held < 30 days | Wait for 30-day window to avoid wash-sale |
| Loss < $500 | Skip — transaction costs exceed benefit |
| Short-term gain offset | Priority harvest — short-term rates are higher |
Annual Harvest Tracking
Maintain a log: position, cost basis, current value, loss amount, harvest date, replacement security, re-entry date. Review in October before year-end to maximize benefit.
Phase 8 — Factor Exposure Analysis
Six-Factor Portfolio Map
For each holding, estimate factor scores (1–5 scale, 3 = neutral):
| Factor | Measurement Proxy | Low (1–2) | Neutral (3) | High (4–5) |
| Value | P/E, P/B vs. sector | Expensive | Fair | Cheap |
| Growth | Revenue/EPS CAGR 3Y | < 5% | 5–15% | > 15% |
| Momentum | 12-1 month return | Bottom quartile | Middle | Top quartile |
| Quality | ROE, Debt/EBITDA | Low ROE, high debt | Average | High ROE, low debt |
| Low-Vol | 1Y realized vol | High vol | Average | Low vol |
| Size | Market cap | Mega-cap | Mid-cap | Small-cap |
Portfolio-Level Factor Score
Weight each holding's factor score by portfolio weight. Compare to S&P 500 baseline (all factors = 3.0):
Factor Portfolio Score Benchmark Active Tilt
Value 2.1 3.0 -0.9 (Growth tilt)
Growth 4.2 3.0 +1.2 (Strong growth)
Momentum 3.8 3.0 +0.8 (Slight momentum)
Quality 3.5 3.0 +0.5 (Slight quality)
Low-Vol 2.3 3.0 -0.7 (Higher volatility)
Size 2.4 3.0 -0.6 (Large-cap tilt)Unintended Factor Tilt Detection
Flag when any active tilt exceeds ±1.0: this signals an unintended concentration that may not be in the investment thesis. Common unintended tilts: growth investors inadvertently loading up on momentum; dividend investors loading up on low-vol (rate sensitive); index investors with large-cap tilt through tech sector overweight.
Benchmark Factor Comparison
Use the factor tilts to explain return difference from benchmark. Growth tilt +1.2 in a value-outperforming market explains underperformance. Momentum tilt in a mean-reverting market increases drawdown risk.
Phase 9 — Rebalancing Decision Framework
When to Rebalance
Three trigger systems — use the one matching the investor's approach:
- Threshold-Based (Recommended for most investors)
- Rebalance when any asset class drifts > 5% from target weight
- Individual stock position drifts > 3% from target
- No action if drift is within tolerance band
- Calendar-Based
- Review quarterly; rebalance only if drift > 3%
- Annual full rebalance regardless of drift
- Simpler but may miss significant mid-quarter moves
- Factor-Based
- Rebalance when portfolio factor score diverges > 1.5 from target
- Triggered by momentum factor decay (top-quartile stocks reversing)
- Suitable for factor-aware investors
Cost-Benefit Analysis
Before executing any rebalance, verify it clears the cost hurdle:
Expected Drift Cost (annual) = Excess vol from drift × Sharpe ratio penalty
Transaction Cost = Commission + (Bid-Ask Spread × Trade Size) + Tax Impact
Rebalance if: Drift Cost > Transaction Cost × 2 (safety margin)Rule of thumb: do not rebalance positions with < $2,000 drift — transaction costs exceed benefit.
Rebalancing Decision Flowchart
START
|
v
Is drift > threshold?
NO --> Monitor next period
YES --> Is account taxable?
YES --> Are there harvesting opportunities?
YES --> Combine harvest + rebalance
NO --> Evaluate tax cost of rebalance
Tax cost > drift benefit? --> Delay
Tax cost < drift benefit? --> Rebalance
NO --> Rebalance immediately (no tax friction)Tax-Smart Rebalancing Order
- Use new cash contributions to buy underweight assets first
- Reinvest dividends into underweight positions
- Harvest losses in overweight positions to fund purchases
- If still needed, sell overweight positions (minimize short-term gains)
Phase 10 — Drawdown & Risk Budget Analysis
Per-Position Maximum Drawdown
For each holding, calculate the worst peak-to-trough decline over the analysis window:
| Position | Max Drawdown | Recovery Time | Current From Peak | Risk Level |
| Example | -35% | 14 months | -8% | Medium |
Flag positions with max drawdown > 50%: high-volatility securities require smaller position sizes to avoid outsized portfolio impact.
Portfolio-Level Value at Risk (VaR)
95% VaR (1-day): the loss not exceeded on 95% of trading days.
Parametric VaR (simplified) = Portfolio Value × Portfolio Daily Vol × 1.645
Example: $500,000 portfolio, daily vol 0.9% → 95% VaR = $500,000 × 0.009 × 1.645 = $7,403/day
Report also: 99% VaR (multiply by 2.326 / 1.645) and 10-day VaR (multiply by √10).
Contribution to Portfolio Volatility
Each position's marginal contribution to total portfolio volatility:
Marginal Vol Contribution (i) = weight(i) × Cov(i, portfolio) / Portfolio Vol
% Vol Contribution = Marginal Vol Contribution / Portfolio Vol × 100Target: no single position contributes > 20% of total portfolio volatility unless it is a deliberate high-conviction overweight.
Risk Budget Allocation Table
| Position | Weight % | Vol Contribution % | Risk Budget Used | Status |
| Ideal | ≤ 10% | ≤ 15% | ≤ budget | OK |
| Flag | > 10% | > 20% | Over budget | Trim |
Stress Test Scenarios
Apply historical shock scenarios to estimate portfolio impact:
- 2022 Rate Shock: tech -35%, bonds -15%, energy +50%
- 2020 COVID Crash: market -34% in 33 days, recovery 5 months
- 2008 GFC: market -57%, credit spreads +500bps
- 2000 Dot-com: tech -78% over 2.5 years
For each scenario: estimate portfolio decline, identify worst-hit positions, confirm portfolio can withstand the scenario without forcing a distressed sale.
Phase 11 — Optimization Recommendations
- Rebalancing Actions
- List all positions with > 2% drift from target weight
- Priority order: largest drift first
- Tax-aware rebalancing: prioritize tax-loss harvesting in taxable accounts
- Proposed trades: ticker, action (buy/sell/trim), target weight, estimated proceeds
- Diversification Improvements
- Specific gaps to fill (e.g., no international exposure, no inflation hedge)
- Correlation-reduction swaps: replace redundant holdings with uncorrelated alternatives
- Alternative asset candidates if appropriate (gold, TIPS, REITs, private credit proxies)
- Underperformer Review
- For each position underperforming benchmark by > 10% over 1Y:
- Is the original thesis intact?
- Has fundamentals deteriorated or is this a temporary setback?
- Hold / average down / exit decision with rationale
- For each position underperforming benchmark by > 10% over 1Y:
- Upgrade Candidates
- Positions to add based on current conviction and valuation
- New opportunities that fit the portfolio's existing factor tilts
- Cost reduction opportunities (replace active fund with cheaper ETF equivalent)
Output Format
Deliver the review as a structured report with these sections:
- Executive Summary (3–5 bullet points: biggest strengths and risks)
- Performance Scorecard (table: metric | portfolio | benchmark | delta)
- Allocation Heat Map (sector/geography breakdown in table form)
- Concentration Risk Score (aggregate score with dimension breakdown)
- Factor Exposure Summary (six-factor table vs. benchmark)
- Holdings Table (position | weight | 1Y return | vol contribution % | status: hold/trim/exit)
- Tax-Loss Harvest Candidates (position | unrealized loss | estimated tax saving)
- Risk Budget Table (position | weight | vol contribution | status)
- Action List (prioritized, with expected portfolio impact)
- Implementation Roadmap (immediate / 30-day / 90-day actions)
Focus on actionable insights aligned with the investor's stated objectives and risk tolerance. Flag any positions or allocations that conflict with the investor profile.
Data Verification
Before finalizing the analysis, verify:
- Position weights sum to 100% (or account for cash)
- Return figures use total return (dividends reinvested)
- Benchmark used matches portfolio's investment universe
- Correlation estimates based on at least 1 year of data
- Tax calculations use correct marginal rate for the investor
- Factor scores sourced from consistent data provider
- VaR calculation uses current portfolio weights, not stale data
Standard Signal Output
All analysis concludes with this standardized block:
╔══════════════════════════════════════════════╗
║ INVESTMENT SIGNAL ║
╠══════════════════════════════════════════════╣
║ Signal: BULLISH / NEUTRAL / BEARISH ║
║ Confidence: HIGH / MEDIUM / LOW ║
║ Horizon: SHORT / MEDIUM / LONG-TERM ║
║ Score: X.X / 10 ║
╠══════════════════════════════════════════════╣
║ Action: BUY / HOLD / SELL ║
║ Conviction: STRONG / MODERATE / WEAK ║
╚══════════════════════════════════════════════╝Score Guide: 8.0–10.0 Strongly Bullish | 6.0–7.9 Moderately Bullish | 4.0–5.9 Neutral | 2.0–3.9 Moderately Bearish | 0.0–1.9 Strongly Bearish Confidence: HIGH (strong data, clear signals) | MEDIUM (mixed signals) | LOW (limited data, conflicting signals) Horizon: SHORT-TERM (1 week–3 months) | MEDIUM-TERM (3 months–1 year) | LONG-TERM (1+ years)
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