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Measuring the response of gold prices to uncertainty: an analysis beyond the mean

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posted on 2018-10-22, 08:26 authored by Jamal Bouoiyour, Refk Selmi, Mark Wohar
This paper provides an innovative perspective on the role of gold as a hedge and safe haven. We use a quantile-on-quantile regression approach to capture the dependence structure between gold returns and changes in uncertainty under different gold market conditions, while considering the nuances of uncertainty levels. To capture the core uncertainty effects on gold returns, a dynamic factor model is used. This technique allows summarizing the impact of six different indexes (namely economic, macroeconomic, microeconomic, monetary policy, financial and political uncertainties) within one aggregate measure of uncertainty. In doing so, we show that the gold's role as a hedge and safe haven cannot be assumed to hold at all times. This ability seems to be sensitive to the gold's various market states (bearish, normal or bullish) and to whether the uncertainty is low, middle or high. Interestingly, we find a positive and strong relationship between gold returns and the uncertainty composite indicator when the uncertainty attains its highest level and under normal gold market scenario. This suggests that holding a diversified portfolio composed of gold could help protecting against exposure to uncertain risks.

History

School

  • Business and Economics

Department

  • Business

Published in

Economic Modelling

Citation

BOUOIYOUR, J., SELMI, R. and WOHAR, M.E., 2018. Measuring the response of gold prices to uncertainty: an analysis beyond the mean. Economic Modelling, 75, pp.105-116.

Publisher

© Elsevier

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2018-06-15

Publication date

2018

Notes

This paper was accepted for publication in the journal Economic Modelling and the definitive published version is available at https://doi.org/10.1016/j.econmod.2018.06.010

ISSN

0264-9993

Language

  • en

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