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    Evaluating risk in precious metal prices with generalised lambda, generalised pareto and generalised extreme value distributions

    Access Status
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    Authors
    Chinhamu, K.
    Huang, Chun-Kai
    Chikobvu, D.
    Date
    2017
    Type
    Journal Article
    
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    Citation
    Chinhamu, K. and Huang, C. and Chikobvu, D. 2017. Evaluating risk in precious metal prices with generalised lambda, generalised pareto and generalised extreme value distributions. South African Statistical Journal. 51 (1): pp. 159-182.
    Source Title
    South African Statistical Journal
    ISSN
    0038-271X
    URI
    http://hdl.handle.net/20.500.11937/67534
    Collection
    • Curtin Research Publications
    Abstract

    In this study we investigate the performance of the generalised lambda distribution (GLD), the generalised Pareto distribution (GPD) and the generalised extreme value distribution (GEVD) in modelling daily platinum, gold and silver price log-returns. Our primary goal is to compare GLD against GPD, and GEVD, in the estimation of Value-at-Risk (VaR) and expected shortfall (ES) as per the international Basel regulatory framework. Our analyses show that GPD and GLD generally outperform GEVD for VaR and ES estimation for negative precious metal returns. For gold, the GPD stands out as the most suitable model. For platinum, GPD and GLD are equally adequate,especially at the 1% VaR level. For silver, GLD is the most suitable at 1% VaR level, whereas GPD is the best model at 0.1%. This study has shown that GLD is a suitable model for extreme risk in precious metal prices and can be used for the estimation of VaR and ES values.

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