DeFi Liquidation Risk Modeling Using Geometric Brownian Motion
Timofei Belenko, Georgii Vosorov
TL;DR
This paper introduces an analytical model using geometric Brownian motion to efficiently compute liquidation risk in DeFi stablecoin lending, replacing simulation-based methods with an exact, lightweight formula.
Contribution
It presents a novel analytical approach modeling collateral exchange rates as geometric Brownian motion for risk calculation in DeFi.
Findings
Provides a closed-form formula for liquidation probability
Reduces computational complexity compared to Monte Carlo simulations
Enhances risk assessment efficiency in DeFi platforms
Abstract
In this paper, we propose an analytical method to compute the collateral liquidation probability in decentralized finance (DeFi) stablecoin single-collateral lending. Our approach models the collateral exchange rate as a zero-drift geometric Brownian motion, and derives the probability of it crossing the liquidation threshold. Unlike most existing methods that rely on computationally intensive simulations such as Monte Carlo, our formula provides a lightweight, exact solution. This advancement offers a more efficient alternative for risk assessment in DeFi platforms.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsModeling, Simulation, and Optimization