---
title: Crude Oil Volatility Forecasting
url: https://www.ml-quant.com/papers/repec/wly-jforec-v-43-y-2024-i-5-p-1422-1446/
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:wly:jforec:v:43:y:2024:i:5:p:1422-1446
source_url: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1002%2Ffor.3077%3Bh%3Drepec%3Awly%3Ajforec%3Av%3A43%3Ay%3A2024%3Ai%3A5%3Ap%3A1422-1446
featured: 2024-09-25
citations: unknown
topic: Derivatives & Volatility
---


# Crude Oil Volatility Forecasting

The study shows that machine learning forecasts offer superior predictions for the volatility of WTI futures prices, resulting in economic benefits.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1002%2Ffor.3077%3Bh%3Drepec%3Awly%3Ajforec%3Av%3A43%3Ay%3A2024%3Ai%3A5%3Ap%3A1422-1446
- Identifier: RePEc:wly:jforec:v:43:y:2024:i:5:p:1422-1446
- Released: 2024-09-25
- First featured: Quant Letter No. 67 (2024-09-25): https://www.ml-quant.com/issues/2024-09-25/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Derivatives & Volatility

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