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Out-of-sample prediction of the oil futures market volatility: A comparison of new and traditional combination approaches

Yaojie Zhang, Feng Ma and Yu Wei

Energy Economics, 2019, vol. 81, issue C, 1109-1120

Abstract: This paper aims to use both the standard and iterated combination approaches to accurately predict the oil futures market volatility. We further make a comprehensive comparison of the out-of-sample forecasting performance between the two paired combination approaches. According to both the Diebold-Mariano test and model confidence set test, the iterated combination approach generates significantly more accurate volatility forecasts than the standard counterpart. The Direction-of-Change test suggests that the iterated combination approach also has substantially higher directional accuracy. We document that these results are robust to various settings. Furthermore, a mean-variance investor can obtain sizeable economic gains when she uses the iterated combination forecasts instead of the standard ones to allocate her portfolio.

Keywords: Oil futures market; Volatility forecasting; Forecast combination; Iterated combination; Asset allocation (search for similar items in EconPapers)
JEL-codes: C53 C58 G11 G17 Q47 (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:81:y:2019:i:c:p:1109-1120

DOI: 10.1016/j.eneco.2019.05.018

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Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

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