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Causal Inference in Econometrics pp 347–362Cite as

Modeling Co-Movement and Risk Management of Gold and Silver Spot Prices

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 622))

Abstract

This paper aims to model volatility and correlation dynamics in spot price returns of gold and silver, and examines the corresponding market risk management implications. VaR (value at risk) and ES (expected shortfall) are used to analyze the market risk associated with investments in gold and silver. Many GARCH family models are employed to describe the volatility. This work applied the copula based-GARCH model in the estimation of a portfolio VaR and ES composed of gold and silver spot prices. The empirical results exhibit that the NAGARCH and the TGARCH families performed better than other GARCH family members in describing the volatility of gold and silver returns, respectively. Furthermore, the time-varying T copula has the most appropriate performance in capturing the dependence structure between gold and silver returns. The out-of-sample forecast performance indicates that the time-varying T copula-based GARCH model can measure the VaR and ES with the accurate estimates of gold and silver.

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Authors and Affiliations

  1. Faculty of Economics, Chiang Mai University, Chiang Mai, 50200, Thailand

    Chen Yang, Songsak Sriboonchitta, Jirakom Sirisrisakulchai & Jianxu Liu

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  1. Chen Yang
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  2. Songsak Sriboonchitta
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  3. Jirakom Sirisrisakulchai
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  4. Jianxu Liu
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Correspondence to Jianxu Liu .

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Editors and Affiliations

  1. School of Knowledge Science, Japan Advanced Ins. of Sci. & Tech, Ishikawa, Japan

    Van-Nam Huynh

  2. Department of Computer Science, University of Texas at El Paso, El Paso, Texas, USA

    Vladik Kreinovich

  3. Faculty of Economics, Chiang Mai University, Chiangmai, Thailand

    Songsak Sriboonchitta

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Yang, C., Sriboonchitta, S., Sirisrisakulchai, J., Liu, J. (2016). Modeling Co-Movement and Risk Management of Gold and Silver Spot Prices. In: Huynh, VN., Kreinovich, V., Sriboonchitta, S. (eds) Causal Inference in Econometrics. Studies in Computational Intelligence, vol 622. Springer, Cham. https://doi.org/10.1007/978-3-319-27284-9_22

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  • DOI: https://doi.org/10.1007/978-3-319-27284-9_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27283-2

  • Online ISBN: 978-3-319-27284-9

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