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 Oct 1, 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

identify_hedge_opportunities

Identifies pairs of assets that act as hedges

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

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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