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Impact of Oil Price Shocks on Crypto and Conventional Financial Assets during Financial Crises: Evidence from the Russian Financial Market

Author

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  • Mirzat Ullah

    (Graduate School of Economics and Management, Ural Federal University, Yekaterinburg 620002 Russia; & School of Management Sciences, Ghulam Ishaq Khan (GIK) Institute of Engineering Sciences and Technology, Topi, Swabi, Pakistan)

  • Kazi Sohag

    (Graduate School of Economics and Management, Ural Federal University, Yekaterinburg 620002 Russia)

  • Farrukh Nawaz

    (Faculty of Business Studies, Arab Open University (AOU), Riyadh, Saudi Arabia)

  • Oleg Mariev

    (Graduate School of Economics and Management, Ural Federal University, Yekaterinburg 620002 Russia)

  • Umar Kayani

    (College of Business, Al Ain University, Abu Dhabi, United Arab Emirates)

  • Igor Mayburov

    (Graduate School of Economics and Management, Ural Federal University, Yekaterinburg 620002 Russia)

  • Svetlana Doroshenko

    (Graduate School of Economics and Management, Ural Federal University, Yekaterinburg 620002 Russia)

Abstract

This study offers a multidimensional solution to mitigate the risk raised due to oil price volatility for navigating investments within the Russian financial landscape. This study assesses spillover effects between crypto assets and traditional financial assets encompassing equities, bonds, precious metals, foreign currency reserves, and crude oil prices. It adopts a significant temporal perspective to assess the potential ramifications of various financial crises, including global health crises and regional conflicts, on oil prices. Utilizing a daily frequency dataset spanning from January 1, 2018, to December 30, 2023, this study investigates the contagion effects of financial crises across normal, bullish, and bearish market conditions. It introduces oil price shocks for the first time to effectively gauge the impact of exogenous shocks on both crypto and conventional asset classes. Additionally, the study employs Cross Quantilogram (CQ) and TVP-VAR spillover estimation techniques to examine interconnectedness among the underlined assets. Furthermore, the study utilizes the quantile wavelet coherence estimation model to unveil volatility patterns, laying the groundwork for hypotheses related to diversification, hedging, and safe-haven investment strategies among the assets. The findings underscore the effectiveness of crypto assets in diversifying risk and serving as a hedge, particularly evident during crises, leading to heightened volatility. Conversely, government-owned bonds exhibit the lowest resilience to external shocks. Moreover, the dynamic interconnectedness among assets provides guidance to investors for implementing the proposed hypotheses that underscores the importance of prudent asset allocation policies for risk management, optimizing portfolio utilization.

Suggested Citation

  • Mirzat Ullah & Kazi Sohag & Farrukh Nawaz & Oleg Mariev & Umar Kayani & Igor Mayburov & Svetlana Doroshenko, 2024. "Impact of Oil Price Shocks on Crypto and Conventional Financial Assets during Financial Crises: Evidence from the Russian Financial Market," International Journal of Energy Economics and Policy, Econjournals, vol. 14(4), pages 472-483, July.
    • Handle: RePEc:eco:journ2:2024-04-43
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    References listed on IDEAS

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    2. Farrukh Nawaz & Mrestyal Khan & Umar Kayani & Indry Aristianto Pradipta & Aulia Luqman Aziz, 2024. "Impact of Volatility Spillovers upon Electric Utilities during the Russia-Ukraine Conflict," International Journal of Energy Economics and Policy, Econjournals, vol. 14(6), pages 597-604, November.

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    More about this item

    Keywords

    Oil Price Shocks; Crypto Assets; Conventional Assets; Hedging; Diversification; Safe-Haven Investment Strategies;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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