Anomaly prediction in XRP price with topological features

TL;DR

This paper explores how topological features of XRP transaction graphs can improve the prediction of extreme price movements in the cryptocurrency market.

Contribution

It introduces a novel approach using topological properties of transaction graphs to forecast anomalous XRP price surges, enhancing prediction accuracy.

Findings

Topological features correlate with extreme XRP price movements.

Using these features improves anomaly prediction performance.

Topological analysis offers valuable insights into cryptocurrency price dynamics.

Abstract

The aim of this research is to study XRP cryptoasset price dynamics, with a particular focus on forecasting atypical price movements. Recent studies suggest that topological properties of transaction graphs are highly informative for understanding cryptocurrency price behavior. In this work, we show that specific topological properties of the XRP transaction graphs provide important information about extreme XRP price surges, and can be used for more competitive prediction of anomalous price dynamics.