---
title: Volatility Estimators for Cryptocurrencies
url: https://www.ml-quant.com/papers/repec/gam-jstats-v-6-y-2023-i-4-p-82-1370-d-1298480/
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:gam:jstats:v:6:y:2023:i:4:p:82-1370:d:1298480
source_url: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.mdpi.com%2F2571-905X%2F6%2F4%2F82%2Fpdf%3Bh%3Drepec%3Agam%3Ajstats%3Av%3A6%3Ay%3A2023%3Ai%3A4%3Ap%3A82-1370%3Ad%3A1298480
featured: 2023-12-20
citations: unknown
topic: Crypto & DeFi
---


# Volatility Estimators for Cryptocurrencies

The paper studies the realized volatility of cryptocurrencies, showing that the best predictors for Bitcoin and Ethereum come from 30-day implied volatility.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.mdpi.com%2F2571-905X%2F6%2F4%2F82%2Fpdf%3Bh%3Drepec%3Agam%3Ajstats%3Av%3A6%3Ay%3A2023%3Ai%3A4%3Ap%3A82-1370%3Ad%3A1298480
- Identifier: RePEc:gam:jstats:v:6:y:2023:i:4:p:82-1370:d:1298480
- Released: 2023-12-20
- First featured: Quant Letter No. 30 (2023-12-20): https://www.ml-quant.com/issues/2023-12-20/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Crypto & DeFi

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