Jump Volatility Forecasting for Crude Oil Futures Based on Complex Network and Hybrid CNN–Transformer Model

The crude oil futures market is highly susceptible to policy changes and international relations, which often trigger abrupt jumps in prices. The existing literature rarely considers jump volatility and the underlying impact mechanisms. This study proposes a hybrid forecasting model integrating a co...

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Bibliografiska uppgifter

Huvudupphov:	Yuqi He, Po Ning, Yuping Song
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	MDPI AG 2026-01-01
Serie:	Mathematics
Ämnen:	crude oil futures complex network jump volatility forecasting hybrid deep learning model
Länkar:	https://www.mdpi.com/2227-7390/14/2/258
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