/portfolio-manager

name: portfolio-manager
description: 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 assessment, performance evaluation, or rebalancing suggestions for their brokerage account.

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`.

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:**

Preferred: use mcp__alpaca__get_account_info to fetch:
- Account equity (total portfolio value)
- Cash balance
- Buying power
- Account status

Fallback REST endpoints:
- paper: https://paper-api.alpaca.markets/v2/account
- live:  https://api.alpaca.markets/v2/account
Headers:
- APCA-API-KEY-ID=$ALPACA_API_KEY
- APCA-API-SECRET-KEY=$ALPACA_SECRET_KEY

**1.2 Get Current Positions:**

Preferred: use mcp__alpaca__get_positions to fetch all holdings:
- Symbol ticker
- Quantity held
- Average entry price (cost basis)
- Current market price
- Current market value
- Unrealized P&L ($ and %)
- Position size as % of portfolio

Fallback REST endpoints:
- paper: https://paper-api.alpaca.markets/v2/positions
- live:  https://api.alpaca.markets/v2/positions

**1.3 Get Portfolio History (Optional):**

Preferred: use mcp__alpaca__get_portfolio_history for performance analysis:
- Historical equity values
- Time-weighted return calculation
- Drawdown analysis

Fallback REST endpoint:
- /v2/account/portfolio/history

**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 dimensio