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How Sentinel Works

🚀 In One Minute​

Sentinel provides risk insights through a straightforward simulation approach:

  • We run a what-if exercise on future prices for supported perpetual contracts.
  • We use a standard baseline model (called GBM) that replays "typical" up-and-down moves from the last 180 days.
  • We simulate holding a position for 10 days (240 hours).
  • We support Linear (USD/USDT-margined) and Inverse (coin-margined) contracts.
  • We include funding costs by taking the latest rate posted by the exchange in the most recent funding interval and applying it during the simulation.
caution

Bottom line: It's a scenario tool, NOT a prediction. It helps you see a range of possible outcomes, NOT the future.

Monte Carlo Simulations Explained​

Sentinel uses Monte Carlo simulations to provide risk insights. Here's how it works:

  1. Multiple Price Paths: We generate thousands of randomized price paths based on historical volatility.
  2. Statistical Analysis: We analyze these paths to calculate probabilities of different outcomes.
  3. Comprehensive Results: The results are summarized to show liquidation probabilities and potential PnL ranges.

We run 7,500 simulations for each analysis, which provides a robust statistical foundation for our risk metrics while maintaining computational efficiency.

Technical Foundation​

Our simulations are built on established financial risk models with specific parameters:

  • Model: Geometric Brownian Motion (GBM) - a standard model for simulating asset price movements
  • Calibration: Parameters are calibrated using the last 180 days of market data
  • Time Horizon: All simulations project outcomes over a 10-day (240-hour) period
  • Funding Rates: We incorporate the latest published funding rate from the exchange

The model captures the typical volatility patterns seen in crypto markets while maintaining computational efficiency.