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Forecasting the oil futures price volatility: Large jumps and small jumps

Jing Liu, Feng Ma, Ke Yang and Yaojie Zhang

Energy Economics, 2018, vol. 72, issue C, 321-330

Abstract: Macro news drives jumps, however, a jump does not seem to improve the predictability of the simple heterogeneous autoregressive realized volatility model (HAR-RV) in the oil futures market. This paper provides a new insight and seeks to investigate whether truncated jumps can help improve the forecasting ability compared to that achieved using the HAR-RV model and its various extensions with jumps. Our results provide strong evidence that the models incorporating both large and small jumps gain a significantly superior forecasting ability. Specifically, including small jumps in a high-frequency model significantly improves the forecast accuracy at the 1-day forecasting horizon, while including both large and small jumps can achieve a higher forecast accuracy at the weekly and monthly horizons. These findings reveal that considering the decomposed jumps with a certain threshold can increase the forecast accuracy of the corresponding model.

Keywords: Volatility forecasting; oil futures price; Large and small jumps; Predictive evaluation (search for similar items in EconPapers)
JEL-codes: C22 C32 C52 C53 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
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DOI: 10.1016/j.eneco.2018.04.023

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