Quantile serial dependence in crude oil markets: evidence from improved quantilogram analysis with quantile wild bootstrapping

Jen-je Su, Adrian Cheung, Eduardo Roca

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

We examine the quantile serial dependence in crude oil prices based on the Linton and Whang’s quantile-based portmanteau test which we improved by means of quantile wild bootstrapping (QWB). Through Monte Carlo simulation, we find that the quantile wild bootstrap-based portmanteau test performs better than the bound testing procedure suggested by Linton and Whang. We apply the improved test to examine the efficiency of two crude oil markets–WTI and Brent. We also examine if the dependence is stable via rolling sample tests. Our results show that both WTI and Brent are serially dependent in all, except the median quantiles. These findings suggest that it may be misleading to examine the efficiency of crude oil markets in terms of mean (or median) returns only. These crude oil markets are relatively more serially dependent in non-median ranges.

Original languageEnglish
Pages (from-to)2817-2828
Number of pages12
JournalApplied Economics
Volume49
Issue number29
DOIs
Publication statusPublished - 2017

Keywords

  • Crude oil prices
  • efficiency
  • quantile serial dependence
  • quantilogram
  • wild bootstrapping

Fingerprint

Dive into the research topics of 'Quantile serial dependence in crude oil markets: evidence from improved quantilogram analysis with quantile wild bootstrapping'. Together they form a unique fingerprint.

Cite this