/portfolio-review

description: Review and analyze investment portfolio performance and allocation

Portfolio Review

📋 Data & Sources Header — Open Every Output With It

The first thing in the output is this provenance block, filled in — never left as placeholders. It is the standard documented on the [Data & Accuracy](https://yennanliu.github.io/InvestSkill/data-and-accuracy.html) page and the first thing `result-validator` looks for:

Data & Sources
  As of:      <date the figures represent, e.g. 2026-06-30>
  Source:     <primary docs — SEC EDGAR 10-K/10-Q, company IR, FRED, exchange data …>
  Retrieval:  <pasted by user | web/tool retrieval | model memory>
  Confidence: <HIGH | MEDIUM | LOW>

• `Retrieval: model memory` must be paired with `Confidence: LOW` — memory is a placeholder until confirmed against a primary source.
• Mixed sources: list each with its own as-of date rather than blending them.
• Sources disagree on the same figure (a closing price, a deal term): prefer the primary source (SEC filing, company release, exchange data) over an aggregator, then the most recent dated one. Show both values with their sources and dates, say which you used and why, and never average them.
• Data the user pasted is reported as `pasted by user`; do not upgrade its confidence beyond what the user's own source supports.

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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

1. **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

2. **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

3. **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

4. **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

1. **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%

2. **Geographic Diversification**

• US vs. international exposure (%)
• Country concentration risk — any single country > 20%?
• Currency exposure and hedging status

3. **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

4. **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

1. **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)

2. **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

3. **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?

4. **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

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