IDEAS home Printed from https://ideas.repec.org/a/scn/00rbes/y2018i3p65-78.html
   My bibliography  Save this article

Анализ рисков криптовалют и способы их минимизации в современных рыночных условиях // Analysis of Cryptocurrency Risks and Methods of their Mitigation in Contemporary Market Conditions

Author

Listed:
  • E. Nadyrova

    (Financial University)

  • Е. Надырова

    (Финансовый университет)

Abstract

In the course of the research, we identified seven risk groups, analyzed their influence, and formulated possible measures of the risk mitigation. For initial coin offerings projects, we formulated a special risk-assessment scoring system based on a 100-point scale. Investment risks (volatility) were one of the main issues. The only effective option of risk-management here is risk aversion - the refusal of any interaction with the cryptocurrency market. On the other hand, traditional risk management method of diversification has proved its worth and viability on empirical studies of portfolio investments. The portfolio should not be mostly “crypto” but rather it should also consist of traditional assets. It is necessary to consider the opportunity to quit the cryptocurrency market for a short period of time, to prevent the harmful consequences of dramatic price shifts. В ходе исследования автором статьи были идентифицированы семь групп рисков, проанализировано их влияние, сформулированы возможные меры по снижению всех видов рисков. Для проектов первичных размещений криптоактивов сформулирована специальная система оценки рисков, основанная на 100-балльной шкале. Инвестиционный риск (волатильность) был одним из основных объектов исследования. Единственным эффективным вариантом управления данным видом риска является отказ от любого взаимодействия с криптовалютным рынком. С другой стороны, традиционный метод управления рисками - диверсификация портфельных инвестиций - доказал свою ценность и жизнеспособность. Портфель не должен ограничиваться только криптовалютой, а обязательно должен включать в себя и традиционные виды активов. Необходимо также рассматривать возможность выхода с криптовалютного рынка на некоторый период времени, чтобы иметь возможность предотвратить опасные последствия резких скачков цен.

Suggested Citation

  • E. Nadyrova & Е. Надырова, 2018. "Анализ рисков криптовалют и способы их минимизации в современных рыночных условиях // Analysis of Cryptocurrency Risks and Methods of their Mitigation in Contemporary Market Conditions," Review of Business and Economics Studies // Review of Business and Economics Studies, Финансовый Университет // Financial University, vol. 6(3), pages 65-78.
    • Handle: RePEc:scn:00rbes:y:2018:i:3:p:65-78
    as

    Download full text from publisher

    File URL: https://rbes.fa.ru/jour/article/viewFile/94/94.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Luisanna Cocco & Michele Marchesi, 2016. "Modeling and Simulation of the Economics of Mining in the Bitcoin Market," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-31, October.
    2. Antonakakis, Nikolaos & Cunado, Juncal & Filis, George & Gabauer, David & Perez de Gracia, Fernando, 2018. "Oil volatility, oil and gas firms and portfolio diversification," Energy Economics, Elsevier, vol. 70(C), pages 499-515.
    3. Bertrand K. Hassani, 2016. "Scenario Analysis in Risk Management," Springer Books, Springer, number 978-3-319-25056-4, December.
    4. Corbet, Shaen & Meegan, Andrew & Larkin, Charles & Lucey, Brian & Yarovaya, Larisa, 2018. "Exploring the dynamic relationships between cryptocurrencies and other financial assets," Economics Letters, Elsevier, vol. 165(C), pages 28-34.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Noureddine Benlagha & Wael Hemrit, 2022. "Does economic policy uncertainty matter to explain connectedness within the international sovereign bond yields?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(1), pages 1-21, January.
    2. Elsayed, Ahmed H. & Nasreen, Samia & Tiwari, Aviral Kumar, 2020. "Time-varying co-movements between energy market and global financial markets: Implication for portfolio diversification and hedging strategies," Energy Economics, Elsevier, vol. 90(C).
    3. David Gabauer, 2020. "Volatility impulse response analysis for DCC‐GARCH models: The role of volatility transmission mechanisms," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 788-796, August.
    4. Yousaf, Imran & Yarovaya, Larisa, 2022. "Static and dynamic connectedness between NFTs, Defi and other assets: Portfolio implication," Global Finance Journal, Elsevier, vol. 53(C).
    5. Esparcia, Carlos & Escribano, Ana & Jareño, Francisco, 2024. "Assessing the crypto market stability after the FTX collapse: A study of high frequency volatility and connectedness," International Review of Financial Analysis, Elsevier, vol. 94(C).
    6. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
    7. Li, Zhenghui & Mo, Bin & Nie, He, 2023. "Time and frequency dynamic connectedness between cryptocurrencies and financial assets in China," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 46-57.
    8. BenMabrouk, Houda & Sassi, Syrine & Soltane, Feriel & Abid, Ilyes, 2024. "Connectedness and portfolio hedging between NFTs segments, American stocks and cryptocurrencies Nexus," International Review of Financial Analysis, Elsevier, vol. 91(C).
    9. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Oxley, Les & Xu, Danyang, 2021. "Pandemic-related financial market volatility spillovers: Evidence from the Chinese COVID-19 epicentre," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 55-81.
    10. Bouri, Elie & Lucey, Brian & Roubaud, David, 2020. "Cryptocurrencies and the downside risk in equity investments," Finance Research Letters, Elsevier, vol. 33(C).
    11. Akhtaruzzaman, Md & Boubaker, Sabri & Sensoy, Ahmet, 2021. "Financial contagion during COVID–19 crisis," Finance Research Letters, Elsevier, vol. 38(C).
    12. Białkowski, Jędrzej, 2020. "Cryptocurrencies in institutional investors’ portfolios: Evidence from industry stop-loss rules," Economics Letters, Elsevier, vol. 191(C).
    13. Duan, Kun & Zhao, Yanqi & Urquhart, Andrew & Huang, Yingying, 2023. "Do clean and dirty cryptocurrencies connect with financial assets differently? The role of economic policy uncertainty," Energy Economics, Elsevier, vol. 127(PA).
    14. Kayani, Umar Nawaz & Hassan, M. Kabir & Moussa, Faten & Hossain, Gazi Farid, 2023. "Oil in crisis: What can we learn," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).
    15. Malfuzi, A. & Mehr, A.S. & Rosen, Marc A. & Alharthi, M. & Kurilova, A.A., 2020. "Economic viability of bitcoin mining using a renewable-based SOFC power system to supply the electrical power demand," Energy, Elsevier, vol. 203(C).
    16. Syed Zwick, Hélène & Syed, Sarfaraz Ali Shah, 2019. "Bitcoin and gold prices: A fledging long-term relationship," MPRA Paper 92512, University Library of Munich, Germany.
    17. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2020. "Dynamic frequency connectedness between oil and natural gas volatilities," Economic Modelling, Elsevier, vol. 84(C), pages 181-189.
    18. Bouri, Elie & Gabauer, David & Gupta, Rangan & Tiwari, Aviral Kumar, 2021. "Volatility connectedness of major cryptocurrencies: The role of investor happiness," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    19. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    20. Giacomo di Tollo & Joseph Andria & Gianni Filograsso, 2023. "The Predictive Power of Social Media Sentiment: Evidence from Cryptocurrencies and Stock Markets Using NLP and Stochastic ANNs," Mathematics, MDPI, vol. 11(16), pages 1-18, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:scn:00rbes:y:2018:i:3:p:65-78. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Алексей Скалабан (email available below). General contact details of provider: http://rbes.fa.ru/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.