Stochastic Dynamics of Ripple XRP for Cross-Border Settlement Optimization

TL;DR

This paper evaluates XRP's potential for cross-border payments using advanced stochastic models, revealing its distinct behavior from traditional assumptions and demonstrating improved remittance success through volatility-aware strategies.

Contribution

It introduces a comprehensive stochastic framework for XRP's cross-border settlement, incorporating regime-switching volatility and jump-diffusion models, and validates its effectiveness with empirical data.

Findings

XRP exhibits behavior significantly different from GBM assumptions.

Stochastic volatility with regime awareness improves corridor optimization.

Adding volatility feedback increases remittance success rates.

Abstract

The feasibility of XRP as a liquidity medium in cross-border transactions is assessed in this paper using a thorough stochastic framework. We use simulations of settlement latency, regime-switching volatility, and jump-diffusion models. The models are calibrated using historical data from public exchanges and RippleNet corridors, and they assess FX dynamics, liquidity depth, and tail risks in real-world scenarios. The behavior of XRP differs significantly from the conventional GBM assumptions, according to the results, and stochastic volatility with regime awareness provides a reliable path to corridor optimization. Our empirical validation shows that adding volatility feedback and routing adjustments significantly increases remittance success rates.