Predicting energy futures high-frequency volatility using technical indicators: The role of interaction

Xue Gong, Xin Ye, Weiguo Zhang and Yue Zhang
Additional contact information
Yue Zhang: SAFTI - Shenzhen Audencia Financial Technology Institute

Post-Print from HAL

Abstract: In this paper, we investigate the predictability of technical indicators on energy futures volatility from the highfrequency and high-dimensional perspectives. We show that the technical indicators have significant impacts on crude oil and natural gas futures volatility based on in- and out-of-sample analysis. Further, we analyze the impacts of interactions among predictor variables on future volatility. Based on an improved conditional sure independence screening model, we find that the interactions contribute to the out-of-sample predictive power significantly. The improved model has robust and better forecasting performance relative to extant popular dimension reduction methods, forecast combination methods, and regularization methods. Moreover, we show that the out-of-sample predictability is robust during various periods. Finally, we show that technical indicators improve economic value in the crude oil market but the economic increment is not significant in the natural gas market.

Keywords: High-frequency data; Technical indicator; Futures volatility prediction; Interaction; Conditional sure independence screening (CSIS) (search for similar items in EconPapers)
Date: 2023-03
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Published in Energy Economics, 2023, 119, pp.106533. ⟨10.1016/j.eneco.2023.106533⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04232649

DOI: 10.1016/j.eneco.2023.106533

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD (hal@ccsd.cnrs.fr).