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Risk Valuation of Precious Metal Returns by Histogram Valued Time Series

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Predictive Econometrics and Big Data (TES 2018)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 753))

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Abstract

The price of precious metals is highly volatile and it can bring both risk and fortune to traders and investors, and therefore should be examined. In this paper, we introduce an approach to fitting a Copula-GARCH to valued time series and apply this methodology to the daily histogram returns of precious metals consisting of gold, silver, and platinum. The study also conducts a simulation study to confirm the accuracy of the model and the result shows that our model performs well. In the empirical study, our results suggest investing on gold and platinum in high proportion while silver is not recommended for inclusion in the precious metal portfolio. Moreover, precious metal portfolio of the intraday 30-min returns gives lower risk when compared with portfolio of the intraday 60-min returns. Therefore, investors should not hold assets for long period of time because the long-term holding is likely to face a higher risk.

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Author information

Authors and Affiliations

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

    Pichayakone Rakpho, Woraphon Yamaka & Roengchai Tansuchat

  2. Center of Excellence in Econometrics, Chiang Mai University, Chiang Mai, 50200, Thailand

    Woraphon Yamaka & Roengchai Tansuchat

Authors
  1. Pichayakone Rakpho
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  2. Woraphon Yamaka
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  3. Roengchai Tansuchat
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Corresponding author

Correspondence to Roengchai Tansuchat .

Editor information

Editors and Affiliations

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

    Vladik Kreinovich

  2. International College, Chiang Mai University, Chiang Mai, Thailand

    Songsak Sriboonchitta

  3. International College, Chiang Mai University, Chiang Mai, Thailand

    Nopasit Chakpitak

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Rakpho, P., Yamaka, W., Tansuchat, R. (2018). Risk Valuation of Precious Metal Returns by Histogram Valued Time Series. In: Kreinovich, V., Sriboonchitta, S., Chakpitak, N. (eds) Predictive Econometrics and Big Data. TES 2018. Studies in Computational Intelligence, vol 753. Springer, Cham. https://doi.org/10.1007/978-3-319-70942-0_39

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  • DOI: https://doi.org/10.1007/978-3-319-70942-0_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70941-3

  • Online ISBN: 978-3-319-70942-0

  • eBook Packages: EngineeringEngineering (R0)

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