Comprehensive portfolio analysis using Alpaca MCP Server integration to fetch holdings and positions, then analyze asset allocation, risk metrics, individual stock positions, diversification, and generate rebalancing recommendations. Use when user requests portfolio review, position analysis, risk a

Portfolio Manager Overview Analyze and manage investment portfolios by integrating with Alpaca MCP Server to fetch real time holdings data, then performing comprehensive analysis covering asset allocation, diversification, risk metrics, individual position evaluation, and rebalancing recommendations. Generate detailed portfolio reports with actionable insights. This skill leverages Alpaca's brokerage API through MCP (Model Context Protocol) to access live portfolio data, ensuring analysis is based on actual current positions rather than manually entered data. When to Use Invoke this skill when the user requests: "Analyze my portfolio" "Review my current positions" "What's my asset allocation?" "Check my portfolio risk" "Should I rebalance my portfolio?" "Evaluate my holdings" "Portfolio performance review" "What stocks should I buy or sell?" Any request involving portfolio level analysis or management Prerequisites Alpaca MCP Server Setup This skill requires Alpaca MCP Server to be configured and connected. The MCP server provides access to: Current portfolio positions Account equity and buying power Historical positions and transactions Market data for held securities MCP Server Tools Used: get account info Fetch account equity, buying power, cash balance get positions Retrieve all current positions with quantities, cost basis, market value get portfolio history Historical portfolio performance data Market data tools for price quotes and fundamentals If Alpaca MCP Server is not connected, inform the user and provide setup instructions from references/alpaca mcp setup.md . REST Fallback Connection Check Run the connection check from the repository root. Use paper credentials first; never paste credentials into a report or commit them to the repository. The command writes a redacted diagnostic summary to stdout and returns zero only when the account and positions endpoints succeed. It does not create a report file or place orders. Workflow Step 1: Fetch Portfolio Data via Alpaca MCP or REST fallback Use Alpaca MCP Server tools to gather current portfolio information when available. In scheduled Hermes jobs, MCP tools may not be exposed even when Alpaca credentials are present; in that case, use the Alpaca REST API directly with ALPACA API KEY , ALPACA SECRET KEY , and ALPACA PAPER . 1.1 Get Account Information: 1.2 Get Current Positions: 1.3 Get Portfolio History (Optional): Scheduled job fallback discipline: Clearly label the source as Alpaca REST fallback rather than MCP. Use ALPACA PAPER=true to choose paper endpoint; otherwise use live endpoint. Still validate that long market value plus cash approximately reconciles to equity, and highlight margin/leverage if long market value equity . For weekly core portfolio cron jobs, compute exposure using equity as the denominator as well as gross market value: gross long exposure = long market value / equity , cash pct = cash / equity , and explicitly flag margin funded portfolios when gross exposure is materially above 100% or cash is negative. Do not let sector weights look benign by using only gross long denominator when the account is levered. When the request emphasizes dividend holdings or forced review triggers, build normalized monitor input from the live holdings and hand it to kanchi dividend review monitor rather than treating dividend review as a narrative only section. Also build tax planning input for kanchi dividend us tax accounting when account location notes are requested; label it degraded if account type or holding period windows are unavailable. Data Validation: Verify all positions have valid ticker symbols Confirm market values sum to approximate account equity Check for any stale or inactive positions Handle edge cases (fractional shares, options, crypto if supported) Step 2: Enrich Position Data For each position in the portfolio, gather additional market data and fundamentals: 2.1 Current Market Data: Real time or delayed price quotes Daily volume and liquidity metrics 52 week range Market capitalization 2.2 Fundamental Data: Use WebSearch or available market data APIs to fetch: Sector and industry classification Key valuation metrics (P/E, P/B, dividend yield) Recent earnings and financial health indicators Analyst ratings and price targets Recent news and material developments 2.3 Technical Analysis: Price trend (20 day, 50 day, 200 day moving averages) Relative strength Support and resistance levels Momentum indicators (RSI, MACD if available) Step 3: Portfolio Level Analysis Perform comprehensive portfolio analysis using frameworks from reference files: 3.1 Asset Allocation Analysis Read references/asset allocation.md for allocation frameworks Analyze current allocation across multiple dimensions: By Asset Class: Equities vs Fixed Income vs Cash vs Alternatives Compare to target allocation for user's risk profile Assess if allocation matches investment goals By Sector: Technology, Healthcare, Financials, Consumer, etc. Identify sector concentration risks Compare to benchmark sector weights (e.g., S&P 500) By Market Cap: Large cap vs Mid cap vs Small cap distribution Concentration in mega caps Market cap diversification score By Geography: US vs International vs Emerging Markets Domestic concentration risk assessment Output Format (illustrative values): 3.2 Diversification Analysis Read references/diversification principles.md for diversification theory Evaluate portfolio diversification quality: Position Concentration: Identify top holdings and their aggregate weight Flag if any single position exceeds 10 15% of portfolio Calculate Herfindahl Hirschman Index (HHI) for concentration measurement Sector Concentration: Identify dominant sectors Flag if any sector exceeds 30 40% of portfolio Compare to benchmark sector diversity Correlation Analysis: Estimate correlation between major positions Identify highly correlated holdings (potential redundancy) Assess true diversification benefit Number of Positions: Optimal range: 15 30 stocks for individual portfolios Flag if under diversified (<10 stocks) or over diversified ( 50 stocks) Output (illustrative values): 3.3 Risk Analysis Read references/portfolio risk metrics.md for risk measurement frameworks Calculate and interpret key risk metrics: Volatility Measures: Estimated portfolio beta (weighted average of position betas) Individual position volatilities Portfolio standard deviation (if historical data available) Downside Risk: Maximum drawdown (from portfolio history) Current drawdown from peak Positions with significant unrealized losses Risk Concentration: Percentage in high volatility stocks (beta 1.5) Percentage in speculative/unprofitable companies Leverage usage (if applicable) Tail Risk: Exposure to potential black swan events Single stock concentration risk Sector specific event risk Output (illustrative values): 3.4 Performance Analysis Evaluate portfolio performance using available data: Absolute Returns: Overall portfolio unrealized P&L ($ and %) Best performing positions (top 5 by % gain) Worst performing positions (bottom 5 by % loss) Time Weighted Returns (if history available): YTD return 1 year, 3 year, 5 year annualized returns Compare to benchmark (S&P 500, relevant index) Position Level Performance: Winners vs Losers ratio Average gain on winning positions Average loss on losing positions Positions near 52 week highs/lows Output (illustrative values): Step 4: Individual Position Analysis For key positions (top 10 15 by portfolio weight), perform detailed analysis: Read references/position evaluation.md for position analysis framework For each significant position: 4.1 Current Thesis Validation: Why was this position initiated? (if known from user context) Has the investment thesis played out or broken? Recent company developments and news 4.2 Valuation Assessment: Current valuation metrics (P/E, P/B, etc.) Compare to historical valuation range Compare to sector peers Overvalued / Fair / Undervalued assessment 4.3 Technical Health: Price trend (uptrend, downtrend, sideways) Position relative to moving averages Support and resistance levels Momentum status 4.4 Position Sizing: Current weight in portfolio Is size appropriate given conviction and risk? Overweight or underweight vs optimal 4.5 Action Recommendation: HOLD Position is well sized and thesis intact ADD Underweight given opportunity, thesis strengthening TRIM Overweight or valuation stretched SELL Thesis broken, better opportunities elsewhere Output per position (illustrative values): Step 5: Rebalancing Recommendations Read references/rebalancing strategies.md for rebalancing approaches Generate specific rebalancing recommendations: 5.1 Identify Rebalancing Triggers: Positions that have drifted significantly from target weights Sector/asset class allocations requiring adjustment Overweight positions to trim (exceeded threshold) Underweight areas to add (below threshold) Tax considerations (capital gains implications) 5.2 Develop Rebalancing Plan: Positions to TRIM: Overweight positions ( threshold deviation from target) Stocks that have run up significantly (valuation concerns) Concentrated positions exceeding 15 20% of portfolio Positions with broken thesis Positions to ADD: Underweight sectors or asset classes High conviction positions currently underweight New opportunities to improve diversification Cash Deployment: If excess cash ( 10% of portfolio), suggest deployment Prioritize based on opportunity and allocation gaps 5.3 Prioritization: Rank rebalancing actions by priority: 1. Immediate Risk reduction (trim concentrated positions) 2. High Priority Major allocation drift ( 10% from target) 3. Medium Priority Moderate drift (5 10% from target) 4. Low Priority Fine tuning and opportunistic adjustments Output (illustrative values): Step 6: Generate Portfolio Report Create comprehensive markdown report saved to repository root: Filename: portfolio analysis YYYY MM DD.md Report Structure: Step 7: Interactive Follow up Be prepared to answer follow up questions: Common Questions: "Why should I sell [SYMBOL]?" Explain specific concerns (valuation, thesis breakdown, concentration) Provide supporting data Offer alternative positions if applicable "What should I buy instead?" Suggest specific stocks to improve allocation Explain how they address portfolio gaps Provide brief investment thesis "What's my biggest risk?" Identify primary risk factor (concentration, sector exposure, volatility) Quantify the risk Suggest mitigation strategies "How does my portfolio compare to [benchmark]?" Compare allocation, sector weights, risk metrics Highlight key differences Assess if differences are justified "Should I rebalance now or wait?" Consider market conditions, tax implications, transaction costs Provide timing recommendation with rationale "Can you analyze [specific position] in more detail?" Perform deep dive analysis using us stock analysis skill if needed Integrate findings back into portfolio context Analysis Frameworks Target Allocation Templates This skill includes reference allocation models for different investor profiles: Read references/target allocations.md for detailed models: Conservative (Capital preservation, income focus) Moderate (Balanced growth and income) Growth (Long term capital appreciation) Aggressive (Maximum growth, high risk tolerance) Each model incl

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