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Component structure for nonstationary time series: Application to benchmark oil prices

*Corresponding author for this work
Scholary Output:
Contribution to journal
Article
Peer-review

Abstract

The oil market is characterized by several hundreds of different grades of crude extracted from various locations on the planet, but prices of those grades are structured with reference to only a handful of benchmark varieties. In this context, the ability to predict near term benchmark oil prices takes on special importance. In this paper, we explore an approach to model the benchmark oil price behaviors using a structure of permanent and transitory components. This initial attempt seems very encouraging at least with respect to one-week ahead forecast and deserves further investigation. In contrast to the equities, the weekly oil permanent components do not seem to be explainable by fundamental factors. However, the returns of the short-run, transitory oil components or cycles, which differ in terms of their degrees of persistence, are mostly affected by contagion spillovers and not by the fundamentals. Their volatilities vary slightly in terms of their sensitivity to major geopolitical events. The overall findings underscore the importance of benefiting more from spillover-catching strategies over diversification ones in the short-run.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 971-983 (13 pages)

Journal (Volume, Issue Number)

International Review of Financial Analysis (Volume 17, Issue 5)

Publication milestones

  • Published - 12/2008

Publication status

Published - 12/2008

ISSN

1057-5219

Publication IDs

  • Scopus: 54949158075

Publication metrics

Metrics

SciVal
FWCI
0.67
SciVal
Author count
3
SciVal
citations
15
SciVal
Paper percentile
69
Scopus
citations
Fractional count
1
Fractional count
0.33
Fractional count
2
Fractional count
0.67
Fractional count
1
Fractional count
1

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Citation count
16
Captures
29