MCP For Claude Marketplace
Portfolio Sharpe Optimization

Portfolio Sharpe Optimization MCP Connector for Claude

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Deterministic capital allocation engine for maximizing Sharpe ratio in prediction markets.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

This MCP server provides a deterministic capital allocation engine designed for prediction market participants. It uses Markowitz mean-variance optimization to calculate the exact weights needed to maximize the Sharpe ratio across multiple bets. Users can utilize optimize_weights to find optimal capital distribution, get_efficient_frontier to visualize risk-return trade-offs, and analyze_risk_profile to estimate maximum drawdown and receive automated rebalancing triggers when positions exceed 20% of the total portfolio.

markowitzsharpe-ratioportfolio-managementprediction-marketscapital-allocation

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

analyze_risk_profile

Estimates the potential downside and provides rebalancing instructions

get_efficient_frontier

Generates a series of optimal portfolios to visualize the trade-off between risk and return

optimize_weights

Calculates the exact capital allocation required to maximize the portfolio's Sharpe ratio

See how to talk to your AI agent using Portfolio Sharpe Optimization.

Calculate the optimal weights for these three markets: EVs of 0.15, 0.20, and 0.10; variances of 0.05, 0.06, and 0.04; a correlation matrix of [[1,0,0],[0,1,0],[0,0,1]]; and 1000 total capital.

The optimal allocation for your $1000 capital is: Market 1: $350.50, Market 2: $420.25, Market 3: $229.25. This configuration maximizes your Sharpe ratio based on the provided parameters.

What is my expected maximum drawdown if my current weights are {'market_a': 500, 'market_b': 500} with EVs of [0.1, 0.12], variances of [0.05, 0.05], and zero correlation?

Based on your current holdings and market statistics, the estimated maximum drawdown is 8.4%.

Show me the efficient frontier for markets with EVs [0.2, 0.3], variances [0.04, 0.09], and a correlation of 0.2.

The efficient frontier has been calculated. The minimum variance portfolio offers an expected return of 0.22 with a volatility of 0.18, while the maximum return portfolio offers 0.30 with a volatility of 0.32.

The engine uses Markowitz mean-variance optimization to solve for weights that maximize the Sharpe ratio, considering the expected values, variances, and correlations of all provided markets.

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