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Anomaly prediction in XRP price with topological features

Illia Donhauzer, Pierluigi Cesana, Tomoyuki Shirai, Yuichi Ikeda

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.

Anomaly prediction in XRP price with topological features

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.
Paper Structure (7 sections, 11 equations, 2 figures, 5 tables)

This paper contains 7 sections, 11 equations, 2 figures, 5 tables.

Table of Contents

  1. Introduction
  2. Preliminaries
  3. Experiments
  4. Data and methodology
  5. Contribution of the topological features
  6. Conclusion
  7. Acknowledgment

Figures (2)

  • Figure 1: Motifs.
  • Figure 2: XRP price increments in the test set (blue line) and their predictions (orange curve), red dots denote weeks with anomalous price increments.