MCP For Claude Marketplace
Asset Correlation Matrix

Asset Correlation Matrix MCP Connector for Claude

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Calculate Pearson correlation between assets to identify diversification risks and hedging opportunities.

3 tools Official Updated Jun 28, 2026 Official Vinkius Partner
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This MCP server provides quantitative tools for financial analysis. Use compute_correlation_matrix to generate a Pearson correlation matrix from historical asset returns. You can then use identify_diversification_risks to find pairs with correlations above 0.8 that threaten portfolio diversification, or identify_hedge_opportunities to detect negatively correlated assets that serve as natural hedges.

correlationpearsonfinancehedgingdiversification

3 tools expose this connector's capabilities to your AI agent.

identify_diversification_risks

g., {"AAPL-MSFT": 0.9}) to find pairs with correlation > 0.8. Identifies pairs of assets with high correlation

compute_correlation_matrix

g., {"AAPL": [0.1, 0.2], "MSFT": [0.15, 0.25]}) and the maximum number of assets allowed. Computes a Pearson correlation matrix for provided asset returns

identify_hedge_opportunities

Identifies pairs of assets that act as hedges

See how to talk to your AI agent using Asset Correlation Matrix.

Calculate the correlation matrix for AAPL and MSFT with these returns: AAPL: [0.01, 0.02, -0.01], MSFT: [0.015, 0.025, -0.005].

The Pearson correlation coefficient between AAPL and MSFT is approximately 0.98.

Are there any diversification risks in this matrix: {"AAPL-MSFT": 0.95, "GOOGL-META": 0.4}

Yes, the pair AAPL-MSFT is identified as a diversification risk due to its high correlation of 0.95.

Find hedging opportunities in this matrix: {"GOLD-SPY": -0.3, "AAPL-MSFT": 0.8}

The pair GOLD-SPY is identified as a natural hedge opportunity with a correlation of -0.3.

Use the `compute_correlation_matrix` tool by providing a JSON string of asset returns, where each key is an asset name and the value is an array of historical returns.

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