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Tail risk, systemic risk and spillover risk of crude oil and precious metals

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  • Ahmed, Rizwan
  • Chaudhry, Sajid M.
  • Kumpamool, Chamaiporn
  • Benjasak, Chonlakan

Abstract

The relationship between oil prices and metal prices has been extensively investigated. However, the tail risk, systemic risk and spillover risk of oil prices have not been investigated via extreme value theory (EVT). We use this novel approach to determine the tail risk of oil, precious metals, how much risk they pose to the financial system and to what extent a shock in oil prices spill over to other precious metals as well as from the financial system. We use long time series of daily data from 1st January 1987 to 31st December 2021 as long time series is required for the EVT. The data is based on the total return index (RI) of four precious metals including gold, platinum, palladium and silver. Our results show that the tail risk of these metals is lower during the crisis period except the Covid-19 pandemic crisis. Most importantly, gold is a safer asset due to the lowest tail risk among four precious metals, indicating the claim that gold is a precious asset to mitigate the returns during market downturns and acts as a ‘safe haven’. Moreover, we also find that extreme systemic risk (tail-β) for crude oil and selected precious metals reduces during crisis period. This is also recognising the fact that these commodities act as a prospective asset for portfolio diversification to hedge against financial assets' volatility. Finally, the spillover risk among crude oil and selected precious metals varies over time, especially during the crisis period and crude oil is an important stimulator of the spillover risk for precious metals. By using our findings, financial market investors can improve their investment planning to attain the maximum advantage of portfolio diversification. Financial managers can further apply these results in forecasting to estimate future global oil market trends for improving their hedging skills and portfolio performance.

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  • Ahmed, Rizwan & Chaudhry, Sajid M. & Kumpamool, Chamaiporn & Benjasak, Chonlakan, 2022. "Tail risk, systemic risk and spillover risk of crude oil and precious metals," Energy Economics, Elsevier, vol. 112(C).
  • Handle: RePEc:eee:eneeco:v:112:y:2022:i:c:s0140988322002298
    DOI: 10.1016/j.eneco.2022.106063
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    3. Naeem, Muhammad Abubakr & Arfaoui, Nadia, 2023. "Exploring downside risk dependence across energy markets: Electricity, conventional energy, carbon, and clean energy during episodes of market crises," Energy Economics, Elsevier, vol. 127(PB).
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    5. Ghosh, Bikramaditya & Pham, Linh & Teplova, Tamara & Umar, Zaghum, 2023. "COVID-19 and the quantile connectedness between energy and metal markets," Energy Economics, Elsevier, vol. 117(C).
    6. Gong, Xiao-Li & Zhao, Min & Wu, Zhuo-Cheng & Jia, Kai-Wen & Xiong, Xiong, 2023. "Research on tail risk contagion in international energy markets—The quantile time-frequency volatility spillover perspective," Energy Economics, Elsevier, vol. 121(C).
    7. Dai, Zhifeng & Zhang, Xiaotong & Yin, Zhujia, 2023. "Extreme time-varying spillovers between high carbon emission stocks, green bond and crude oil: Evidence from a quantile-based analysis," Energy Economics, Elsevier, vol. 118(C).
    8. Guo, Yaoqi & Shi, Fengyuan & Lin, Boqiang & Zhang, Hongwei, 2023. "The impact of oil shocks from different sources on China's clean energy metal stocks: An analysis of spillover effects based on a time-varying perspective," Resources Policy, Elsevier, vol. 81(C).
    9. Alomari, Mohammad & Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Extreme return spillovers and connectedness between crude oil and precious metals futures markets: Implications for portfolio management," Resources Policy, Elsevier, vol. 79(C).
    10. Zhang, Hongwei & Zhang, Yubo & Gao, Wang & Li, Yingli, 2023. "Extreme quantile spillovers and drivers among clean energy, electricity and energy metals markets," International Review of Financial Analysis, Elsevier, vol. 86(C).

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    More about this item

    Keywords

    Risk management; Precious metals; Crude oil and tail risk;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products

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