PredictLiquidate

Problem Statement

🧮 Project: DeFi Liquidation Risk Dashboard OverviewThe DeFi Liquidation Risk Dashboard helps users predict the probability of a leveraged DeFi position being liquidated over a chosen time horizon. It’s based on the model from the research paper “DeFi Liquidation Risk Modeling Using the Reflection Principle for Zero-Drift Brownian Motion”, where collateral prices are assumed to follow a Geometric Brownian Motion (GBM). By applying the reflection principle, the app computes the exact closed-form probability that an asset’s price crosses the liquidation threshold within a given time — without requiring any simulation or Monte Carlo estimation.How it worksUser InputsCurrent collateral price S0 S 0 ​Liquidation threshold Sliq S liq ​Volatility σ σ (annualized or custom)Time horizon t t (in days, hours, etc.)Mathematical Model The app uses the GBM-based formula from the paper:P(liquidation within t)=2 Φ ⁣(ln⁡(Sliq/S0)σt) P(liquidation within t)=2Φ( σ t

Solution

🧮 Project: DeFi Liquidation Risk Dashboard OverviewThe DeFi Liquidation Risk Dashboard helps users predict the probability of a leveraged DeFi position being liquidated over a chosen time horizon. It’s based on the model from the research paper “DeFi Liquidation Risk Modeling Using the Reflection Principle for Zero-Drift Brownian Motion”, where collateral prices are assumed to follow a Geometric Brownian Motion (GBM). By applying the reflection principle, the app computes the exact closed-form probability that an asset’s price crosses the liquidation threshold within a given time — without requiring any simulation or Monte Carlo estimation.How it worksUser InputsCurrent collateral price S0 S 0 ​Liquidation threshold Sliq S liq ​Volatility σ σ (annualized or custom)Time horizon t t (in days, hours, etc.)Mathematical Model The app uses the GBM-based formula from the paper:P(liquidation within t)=2 Φ ⁣(ln⁡(Sliq/S0)σt) P(liquidation within t)=2Φ( σ t