nixtla-correlation-mapper
Analyze multi-contract correlations for forecast-based hedge recommendations. Use when managing correlated assets. Trigger with 'analyze correlations' or 'suggest hedge'.
npx skills add majiayu000/claude-skill-registry --skill nixtla-correlation-mapper-intent-solutions-io-plugins-nixtla --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Nixtla Correlation Mapper Identifies correlations between multiple contracts and generates hedging strategies for portfolio risk management. ## Overview Analyzes relationships between assets in a portfolio to suggest hedging strategies. Takes CSV data with multiple time series, calculates correlation matrix, identifies significant relationships, and outputs hedge recommendations with visualizations. Generates correlation heatmap, rolling correlation plots, and hedge effectiveness charts. ## Prerequisites **Tools**: Read, Write, Bash, Glob, Grep **Environment**: None required (optional: `NIXTLA_TIMEGPT_API_KEY` for forecasted correlations) **Packages**: ```bash pip install pandas numpy scipy matplotlib seaborn ``` **Input Format**: CSV with columns: `unique_id` (contract identifier), `ds` (date), `y` (price/value) ## Instructions ### Step 1: Prepare Data Load multi-series contract data and calculate returns. Uses `{baseDir}/scripts/prepare_data.py`. ```bash python scripts/prepare_data.py contracts.csv --method log --output-dir results/ ``` **Output**: `prices_wide.csv`, `returns.csv` ### Step 2: Calculate Correlations Calculate correlation matrix and identify significant pairs. Us
- Overview
- Prerequisites
- Instructions
- Step 1: Prepare Data
- Step 2: Calculate Correlations
- Step 3: Generate Hedge Recommendations
- Step 4: Create Visualizations
- Step 5: Generate Report
- Output
- Error Handling
- Examples
- Example 1: Crypto Portfolio
- Example 2: Prediction Market Contracts
- Resources
pip install pandas numpy scipy matplotlib seaborn python scripts/prepare_data.py contracts.csv --method log --output-dir results/ python scripts/correlation_analysis.py \ python scripts/hedge_recommendations.py \ python scripts/visualize.py \ python scripts/generate_report.py \ python scripts/prepare_data.py portfolio.csv python scripts/correlation_analysis.py python scripts/hedge_recommendations.py python scripts/visualize.py
What does the nixtla-correlation-mapper skill do?
Analyze multi-contract correlations for forecast-based hedge recommendations. Use when managing correlated assets. Trigger with 'analyze correlations' or 'suggest hedge'.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill nixtla-correlation-mapper-intent-solutions-io-plugins-nixtla --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.