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Trading Risk Metrics

by raihanse43Updated May 4, 2026

Computes portfolio risk and performance metrics from CSV/JSON export files, including VaR/ES, Sharpe/Sortino ratios, drawdowns, concentration measures, and Markdown tear sheets. Processes data offline without external APIs. Quantitative analysts, portfolio managers, and traders use it to evaluate trading strategies and holdings directly from export data.

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Overview

The Trading Risk Metrics MCP server analyzes portfolio data from CSV or JSON files to produce risk and performance metrics. It calculates Value at Risk (VaR), Expected Shortfall (ES), Sharpe and Sortino ratios, drawdowns, and concentration metrics, outputting results as Markdown-formatted tear sheets. All computations run locally, requiring no external APIs or data connections.

Key Capabilities

  • VaR/ES: Estimates potential portfolio losses at specified confidence levels and average shortfall beyond VaR thresholds.
  • Sharpe/Sortino ratios: Quantifies risk-adjusted returns; Sharpe uses total volatility, Sortino targets downside deviation.
  • Drawdowns: Tracks maximum drawdown, average drawdown, and recovery periods from peak-to-trough declines.
  • Concentration: Measures exposure to single assets or sectors via metrics like Herfindahl index or top holdings percentages.
  • Markdown tear sheets: Compiles all metrics into readable, shareable reports with tables and summaries.

Use Cases

  1. A portfolio manager uploads a CSV of daily returns to compute VaR/ES and drawdowns, assessing tail risks before rebalancing.
  2. A quantitative trader processes JSON trade logs to calculate Sharpe/Sortino ratios, comparing strategy performance across periods.
  3. An individual investor analyzes holdings export for concentration metrics, identifying overexposure to specific stocks.
  4. A risk analyst generates Markdown tear sheets from historical data for internal reports on portfolio health.

Who This Is For

Quantitative analysts, portfolio managers, hedge fund risk teams, and self-directed traders who need precise, offline metric calculations from their own export files. Suited for those handling trade histories or position data without cloud dependencies.