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What drives gold returns? A decision tree analysis

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  • Malliaris, A.G.
  • Malliaris, Mary

Abstract

The behavior of gold as an investment asset has been researched extensively. For the very long run, that is several decades, gold does not outperform equities. However, for shorter periods, gold responds to fears of inflation, stock market corrections, currency crises and financial instabilities very vigorously. In this paper we follow a decision tree methodology to investigate the behavior of gold prices using both traditional financial variables such as equity returns, equity volatility, oil prices, and the euro. We also use the new Cleveland Financial Stress Index to investigate its effectiveness in explaining changes in gold prices. We find that gold returns depend on different determinants across various regimes.

Suggested Citation

  • Malliaris, A.G. & Malliaris, Mary, 2015. "What drives gold returns? A decision tree analysis," Finance Research Letters, Elsevier, vol. 13(C), pages 45-53.
  • Handle: RePEc:eee:finlet:v:13:y:2015:i:c:p:45-53 DOI: 10.1016/j.frl.2015.03.004
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    References listed on IDEAS

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    1. A. Malliaris & Mary Malliaris, 2013. "Are oil, gold and the euro inter-related? Time series and neural network analysis," Review of Quantitative Finance and Accounting, Springer, vol. 40(1), pages 1-14, January.
    2. Robert J. Barro & Sanjay Misra, 2016. "Gold Returns," Economic Journal, Royal Economic Society, vol. 126(594), pages 1293-1317, August.
    3. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2014. "The international business cycle and gold-price fluctuations," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 292-305.
    4. Ciner, Cetin & Gurdgiev, Constantin & Lucey, Brian M., 2013. "Hedges and safe havens: An examination of stocks, bonds, gold, oil and exchange rates," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 202-211.
    5. Mensi, Walid & Beljid, Makram & Boubaker, Adel & Managi, Shunsuke, 2013. "Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold," Economic Modelling, Elsevier, vol. 32(C), pages 15-22.
    6. Claude B. Erb & Campbell R. Harvey, 2013. "The Golden Dilemma," NBER Working Papers 18706, National Bureau of Economic Research, Inc.
    7. Nikolay Nenovsky & S. Statev, 2006. "Introduction," Post-Print halshs-00260898, HAL.
    8. Fama, Eugene F & French, Kenneth R, 1988. " Business Cycles and the Behavior of Metals Prices," Journal of Finance, American Finance Association, vol. 43(5), pages 1075-1093, December.
    9. Raj Aggarwal & Brian Lucey & Fergal O'Connor, 2015. "World Metal Markets," World Scientific Book Chapters,in: THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 10, pages 325-347 World Scientific Publishing Co. Pte. Ltd..
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    Citations

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    Cited by:

    1. Hoang, Thi-Hong-Van & Wong, Wing-Keung & Zhu, Zhenzhen, 2015. "Is gold different for risk-averse and risk-seeking investors? An empirical analysis of the Shanghai Gold Exchange," Economic Modelling, Elsevier, vol. 50(C), pages 200-211.
    2. repec:eee:jimfin:v:79:y:2017:i:c:p:203-217 is not listed on IDEAS
    3. El khamlichi, Abdelbari & HOANG, Thi Hong Van & Wong, Wing-Keung, 2017. "Is Gold Different for Islamic and Conventional Portfolios? A Sectorial Analysis," MPRA Paper 76282, University Library of Munich, Germany.
    4. Döpke, Jörg & Fritsche, Ulrich & Pierdzioch, Christian, 2017. "Predicting recessions with boosted regression trees," International Journal of Forecasting, Elsevier, pages 745-759.
    5. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2016. "Are precious metals a hedge against exchange-rate movements? An empirical exploration using bayesian additive regression trees," The North American Journal of Economics and Finance, Elsevier, vol. 38(C), pages 27-38.
    6. Joscha Beckmann & Theo Berger & Robert Czudaj & Thi-Hong-Van Hoang, 2017. "Tail dependence between gold and sectorial stocks in China: Perspectives for portfolio diversication," Chemnitz Economic Papers 012, Department of Economics, Chemnitz University of Technology, revised Jul 2017.
    7. Luo, Xingguo & Qin, Shihua & Ye, Zinan, 2016. "The information content of implied volatility and jumps in forecasting volatility: Evidence from the Shanghai gold futures market," Finance Research Letters, Elsevier, vol. 19(C), pages 105-111.
    8. Jörg Döpke & Ulrich Fritsche & Christian Pierdzioch, 2015. "Predicting Recessions in Germany With Boosted Regression Trees," Macroeconomics and Finance Series 201505, Hamburg University, Department Wirtschaft und Politik.
    9. Ftiti, Zied & Fatnassi, Ibrahim & Tiwari, Aviral Kumar, 2016. "Neoclassical finance, behavioral finance and noise traders: Assessment of gold–oil markets," Finance Research Letters, Elsevier, vol. 17(C), pages 33-40.

    More about this item

    Keywords

    Gold prices; Uncertainty; Decision tree analysis; Financial Stress Index;

    JEL classification:

    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G1 - Financial Economics - - General Financial Markets

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