---
title: Improved Cryptocurrency Volatility Predictions
url: https://www.ml-quant.com/papers/repec/eee-ecmode-v-144-y-2025-i-c-s0264999324003432/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:eee:ecmode:v:144:y:2025:i:c:s0264999324003432
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0264999324003432%3Bh%3Drepec%3Aeee%3Aecmode%3Av%3A144%3Ay%3A2025%3Ai%3Ac%3As0264999324003432
featured: 2025-02-05
citations: unknown
topic: Crypto & DeFi
---


# Improved Cryptocurrency Volatility Predictions

The study reveals that combining different forecasting models can greatly enhance the accuracy of predicting cryptocurrency volatility. This can provide crucial information for investors looking to improve risk management strategies in cryptocurrency markets.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0264999324003432%3Bh%3Drepec%3Aeee%3Aecmode%3Av%3A144%3Ay%3A2025%3Ai%3Ac%3As0264999324003432
- Identifier: RePEc:eee:ecmode:v:144:y:2025:i:c:s0264999324003432
- Released: 2025-02-05
- First featured: Quant Letter No. 84 (2025-02-05): https://www.ml-quant.com/issues/2025-02-05/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Crypto & DeFi

## Related

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