Anomaly prediction in XRP price with topological features
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866910060515426304 |
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| author | Donhauzer, Illia Cesana, Pierluigi Shirai, Tomoyuki Ikeda, Yuichi |
| author_facet | Donhauzer, Illia Cesana, Pierluigi Shirai, Tomoyuki Ikeda, Yuichi |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_18021 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Anomaly prediction in XRP price with topological features Donhauzer, Illia Cesana, Pierluigi Shirai, Tomoyuki Ikeda, Yuichi Statistical Finance 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. |
| title | Anomaly prediction in XRP price with topological features |
| topic | Statistical Finance |
| url | https://arxiv.org/abs/2603.18021 |