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On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree

Author

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  • Philippe Charlot

    () (LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - UN - Université de Nantes)

  • Vêlayoudom Marimoutou

    () (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - ECM - Ecole Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique - AMU - Aix Marseille Université - EHESS - École des hautes études en sciences sociales)

Abstract

This study examines the volatility and correlation and their relationships among the euro/US dollar exchange rates, the S&P500 equity indices, and the prices of WTI crude oil and the precious metals (gold, silver, and platinum) over the period 2005 to 2012. Our model links the univariate volatilities with the correlations via a hidden stochastic decision tree. The ensuing Hidden Markov Decision Tree (HMDT) model is in fact an extension of the Hidden Markov Model (HMM) introduced by Jordan et al. (1997). The architecture of this model is the opposite that of the classical deterministic approach based on a binary decision tree and, it allows a probabilistic vision of the relationship between univariate volatility and correlation. Our results are categorized into three groups, namely (1) exchange rates and oil, (2) S&P500 indices, and (3) precious metals. A switching dynamics is seen to characterize the volatilities, while, in the case of the correlations, the series switch from one regime to another, this movement touching a peak during the period of the Subprime crisis in the US, and again during the days following the Tohoku earthquake in Japan. Our findings show that the relationships between volatility and correlation are dependent upon the nature of the series considered, sometimes corresponding to those found in econometric studies, according to which correlation increases in bear markets, at other times differing from them.

Suggested Citation

  • Philippe Charlot & Vêlayoudom Marimoutou, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Working Papers hal-00980125, HAL.
  • Handle: RePEc:hal:wpaper:hal-00980125
    Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-00980125
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    Cited by:

    1. Behmiri, Niaz Bashiri & Manera, Matteo & Nicolini, Marcella, 2016. "Understanding Dynamic Conditional Correlations between Commodities Futures Markets," ESP: Energy Scenarios and Policy 232223, Fondazione Eni Enrico Mattei (FEEM).
    2. Davide, Marinella & Vesco, Paola, 2016. "Alternative Approaches for Rating INDCs: a Comparative Analysis," MITP: Mitigation, Innovation,and Transformation Pathways 232716, Fondazione Eni Enrico Mattei (FEEM).
    3. Marinella Davide & Paola Vesco, 2016. "Alternative Approaches for Rating INDCs: a Comparative Analysis," Working Papers 2016.18, Fondazione Eni Enrico Mattei.
    4. Elina Pradkhan, 2016. "Information Content of Trading Activity in Precious Metals Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(5), pages 421-456, May.
    5. Behmiri, Niaz Bashiri & Manera, Matteo, 2015. "The role of outliers and oil price shocks on volatility of metal prices," Resources Policy, Elsevier, vol. 46(P2), pages 139-150.
    6. repec:eee:finana:v:52:y:2017:i:c:p:316-332 is not listed on IDEAS
    7. Mehmet Balcilar & Zeynel Abidin Ozdemir, 2018. "The volatility effect on precious metals prices in a stochastic volatility in mean model with time-varying parameters," Working Papers 15-34, Eastern Mediterranean University, Department of Economics.
    8. repec:eee:jrpoli:v:52:y:2017:i:c:p:427-434 is not listed on IDEAS
    9. repec:eee:finana:v:52:y:2017:i:c:p:292-308 is not listed on IDEAS
    10. Reboredo, Juan C. & Ugolini, Andrea, 2016. "The impact of downward/upward oil price movements on metal prices," Resources Policy, Elsevier, vol. 49(C), pages 129-141.
    11. Kuruppuarachchi, Duminda & Premachandra, I.M., 2016. "Information spillover dynamics of the energy futures market sector: A novel common factor approach," Energy Economics, Elsevier, vol. 57(C), pages 277-294.

    More about this item

    Keywords

    Multivariate GARCH; Dynamic correlations; Regime switching; Hidden Markov; Decision tree;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G1 - Financial Economics - - General Financial Markets
    • G0 - Financial Economics - - General

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