Forecasting value-at-risk of crude oil futures using a hybrid ARIMA-SVR-POT model

Forecasting the value at risk (VaR) of crude oil futures can be a challenging task for investors due to the high volatility of these prices. It is crucial to describe the return in the tail distribution, as extreme values can trigger larger price fluctuations and market risks. In this study, we prop...

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书目详细资料
Main Authors: Chen Zhang, Xinmiao Zhou
格式: 文件
语言:English
出版: Elsevier 2024-01-01
丛编:Heliyon
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在线阅读:http://www.sciencedirect.com/science/article/pii/S2405844023105664