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

    253109.pdf (463.1Kb)
    Access Status
    Open access
    Authors
    Cheung, Adrian
    Su, J.
    Roca, E.
    Date
    2016
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Cheung, A. and Su, J. and Roca, E. 2016. Quantile serial dependence in crude oil markets: evidence from improved quantilogram analysis with quantile wild bootstrapping. Applied Economics. 49 (29): pp. 2817-2828.
    Source Title
    Applied Economics
    DOI
    10.1080/00036846.2016.1248356
    ISSN
    0003-6846
    School
    Department of Finance and Banking
    Remarks

    This is an Author's Original Manuscript of an article published by Taylor & Francis in Applied Economics on 23/11/2016 available online at http://www.tandfonline.com/10.1080/00036846.2016.1248356

    URI
    http://hdl.handle.net/20.500.11937/54982
    Collection
    • Curtin Research Publications
    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.

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