Einstein Research — Portfolio Risk Analyzer
by @clawdiri-ai
Performs a comprehensive, portfolio-level risk analysis. Calculates VaR (Value at Risk), max drawdown, correlation matrix, stress tests against historical cr...
clawhub install einstein-research-portfolio-risk-dv📖 About This Skill
id: 'einstein-research-portfolio-risk' name: 'Einstein Research — Portfolio Risk Analyzer' description: 'Performs a comprehensive, portfolio-level risk analysis. Calculates VaR (Value at Risk), max drawdown, correlation matrix, stress tests against historical crises, and identifies concentration risks. Use when asked about portfolio risk, drawdown, hedging, or stress testing.' version: '1.0.0' author: 'DaVinci' last_amended_at: null trigger_patterns: [] pre_conditions: git_repo_required: false tools_available: [] expected_output_format: 'natural_language'
Portfolio Risk Analyzer
Overview
This skill performs a comprehensive, portfolio-level risk analysis. It goes beyond individual position risk to quantify systemic and correlated risks across the entire portfolio.
Core Features:
When to Use This Skill
Explicit Triggers:
Implicit Triggers:
Workflow
Step 1: Ingest Portfolio Data
The analysis requires the current portfolio holdings, typically from a CSV or JSON file.
Input Format (portfolio.json):
{
"positions": [
{ "ticker": "AAPL", "quantity": 100, "avg_price": 150.00 },
{ "ticker": "TSLA", "quantity": 50, "avg_price": 200.00 },
{ "ticker": "SPY", "quantity": 200, "avg_price": 400.00 }
],
"cash": 25000
}
Step 2: Execute the Risk Analysis Script
The portfolio-risk-analyzer CLI tool runs the full analysis suite.
portfolio-risk-analyzer run \
--portfolio path/to/portfolio.json \
--benchmark SPY
The script performs the following calculations: 1. Fetches historical price data for all positions. 2. Calculates daily returns for each position and the total portfolio. 3. VaR: - *Parametric*: Assumes normal distribution of returns. - *Historical*: Uses the actual distribution of historical returns. - *Monte Carlo*: Simulates thousands of possible future return paths. 4. Max Drawdown: Finds the largest peak-to-trough decline in the portfolio's history. 5. Correlation: Computes the correlation matrix for all positions. 6. Stress Tests: Re-prices the portfolio based on the returns of historical crisis periods. 7. Concentration: Calculates weights by position, sector, and factor.
Step 3: Analyze the Output
The script generates a detailed report in both JSON and Markdown formats.
JSON Output (risk_report_YYYY-MM-DD.json):
Markdown Report (risk_report_YYYY-MM-DD.md):
Step 4: Present Findings to User
Synthesize the key findings from the Markdown report into a clear, actionable summary. Start with the most critical information (like high concentration or poor stress test results) and provide concrete suggestions for risk mitigation.