---
title: Implied Roughness in Oil Volatility
url: https://www.ml-quant.com/papers/repec/taf-quantf-v-24-y-2024-i-3-4-p-347-363/
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:taf:quantf:v:24:y:2024:i:3-4:p:347-363
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1080%2F14697688.2023.2291081%3Bh%3Drepec%3Ataf%3Aquantf%3Av%3A24%3Ay%3A2024%3Ai%3A3-4%3Ap%3A347-363
featured: 2024-06-20
citations: unknown
topic: Derivatives & Volatility
---


# Implied Roughness in Oil Volatility

The article examines the roughness of oil market volatility using unspanned stochastic volatility models, demonstrating that adding an extra parameter indicating the volatility's roughness improves the calibration nearly tenfold.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1080%2F14697688.2023.2291081%3Bh%3Drepec%3Ataf%3Aquantf%3Av%3A24%3Ay%3A2024%3Ai%3A3-4%3Ap%3A347-363
- Identifier: RePEc:taf:quantf:v:24:y:2024:i:3-4:p:347-363
- Released: 2024-06-20
- First featured: Quant Letter No. 54 (2024-06-20): https://www.ml-quant.com/issues/2024-06-20/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Derivatives & Volatility

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