IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v10y2022i5p107-d819454.html
   My bibliography  Save this article

A Systematic Literature Review of Volatility and Risk Management on Cryptocurrency Investment: A Methodological Point of View

Author

Listed:
  • José Almeida

    (ISEG—Lisbon School of Economics & Management, Universidade de Lisboa, Advance/CSG, 1200-781 Lisboa, Portugal)

  • Tiago Cruz Gonçalves

    (ISEG—Lisbon School of Economics & Management, Universidade de Lisboa, Advance/CSG, 1200-781 Lisboa, Portugal)

Abstract

In this study, we explore the research published from 2009 to 2021 and summarize what extant literature has contributed in the last decade to the analysis of volatility and risk management in cryptocurrency investment. Our samples include papers published in journals ranked across different fields in ABS ranked journals. We conduct a bibliometric analysis using VOSviewer software and perform a literature review. Our findings are presented in terms of methodologies used to model cryptocurrencies’ volatility and also according to their main findings pertaining to volatility and risk management in those assets and using them in portfolio management. Our research indicates that the models that consider the Markov-switching regime seem to be more consensual among the authors, and that the best machine learning technique performances are hybrid models that consider the support vector machines (SVM). We also argue that the predictability of volatility, risk reduction, and level of speculation in the cryptocurrency market are improved by the leverage effects and the volatility persistence.

Suggested Citation

  • José Almeida & Tiago Cruz Gonçalves, 2022. "A Systematic Literature Review of Volatility and Risk Management on Cryptocurrency Investment: A Methodological Point of View," Risks, MDPI, vol. 10(5), pages 1-18, May.
    • Handle: RePEc:gam:jrisks:v:10:y:2022:i:5:p:107-:d:819454
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/10/5/107/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-9091/10/5/107/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Akanksha Jalan & Roman Matkovskyy & Saqib Aziz, 2021. "The Bitcoin options market: A first look at pricing and risk," Applied Economics, Taylor & Francis Journals, vol. 53(17), pages 2026-2041, April.
    2. Hong, Yun & Li, Yi, 2020. "Housing prices and investor sentiment dynamics: Evidence from China using a wavelet approach," Finance Research Letters, Elsevier, vol. 35(C).
    3. Angerer, Martin & Hoffmann, Christian Hugo & Neitzert, Florian & Kraus, Sascha, 2021. "Objective and subjective risks of investing into cryptocurrencies," Finance Research Letters, Elsevier, vol. 40(C).
    4. Köchling, Gerrit & Schmidtke, Philipp & Posch, Peter N., 2020. "Volatility forecasting accuracy for Bitcoin," Economics Letters, Elsevier, vol. 191(C).
    5. Jiang, Shangrong & Li, Xuerong & Wang, Shouyang, 2021. "Exploring evolution trends in cryptocurrency study: From underlying technology to economic applications," Finance Research Letters, Elsevier, vol. 38(C).
    6. Ai Jun Hou & Weining Wang & Cathy Y H Chen & Wolfgang Karl Härdle, 2020. "Pricing Cryptocurrency Options," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 250-279.
    7. Acereda, Beatriz & Leon, Angel & Mora, Juan, 2020. "Estimating the expected shortfall of cryptocurrencies: An evaluation based on backtesting," Finance Research Letters, Elsevier, vol. 33(C).
    8. Kyriazis, Nikolaos & Papadamou, Stephanos & Corbet, Shaen, 2020. "A systematic review of the bubble dynamics of cryptocurrency prices," Research in International Business and Finance, Elsevier, vol. 54(C).
    9. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "Volatility spillover effects in leading cryptocurrencies: A BEKK-MGARCH analysis," Finance Research Letters, Elsevier, vol. 29(C), pages 68-74.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Balcilar, Mehmet & Ozdemir, Huseyin & Agan, Busra, 2022. "Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    2. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    3. Alessio Brini & Jimmie Lenz, 2024. "A Comparison of Cryptocurrency Volatility-benchmarking New and Mature Asset Classes," Papers 2404.04962, arXiv.org.
    4. Danai Likitratcharoen & Pan Chudasring & Chakrin Pinmanee & Karawan Wiwattanalamphong, 2023. "The Efficiency of Value-at-Risk Models during Extreme Market Stress in Cryptocurrencies," Sustainability, MDPI, vol. 15(5), pages 1-21, March.

    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. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    2. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    3. Cao, Guangxi & Xie, Wenhao, 2022. "Asymmetric dynamic spillover effect between cryptocurrency and China's financial market: Evidence from TVP-VAR based connectedness approach," Finance Research Letters, Elsevier, vol. 49(C).
    4. Klender Cortez & Martha del Pilar Rodríguez-García & Samuel Mongrut, 2020. "Exchange Market Liquidity Prediction with the K-Nearest Neighbor Approach: Crypto vs. Fiat Currencies," Mathematics, MDPI, vol. 9(1), pages 1-15, December.
    5. Peng‐Fei Dai & John W. Goodell & Luu Duc Toan Huynh & Zhifeng Liu & Shaen Corbet, 2023. "Understanding the transmission of crash risk between cryptocurrency and equity markets," The Financial Review, Eastern Finance Association, vol. 58(3), pages 539-573, August.
    6. Umar, Zaghum & Polat, Onur & Choi, Sun-Yong & Teplova, Tamara, 2022. "Dynamic connectedness between non-fungible tokens, decentralized finance, and conventional financial assets in a time-frequency framework," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    7. Li, Yue & Goodell, John W. & Shen, Dehua, 2021. "Comparing search-engine and social-media attentions in finance research: Evidence from cryptocurrencies," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 723-746.
    8. Goodell, John W. & Corbet, Shaen & Yadav, Miklesh Prasad & Kumar, Satish & Sharma, Sudhi & Malik, Kunjana, 2022. "Time and frequency connectedness of green equity indices: Uncovering a socially important link to Bitcoin," International Review of Financial Analysis, Elsevier, vol. 84(C).
    9. Boyi Li & Weixuan Xia, 2024. "Crypto Inverse-Power Options and Fractional Stochastic Volatility," Papers 2403.16006, arXiv.org.
    10. Kyriazis, Nikolaos & Papadamou, Stephanos & Tzeremes, Panayiotis & Corbet, Shaen, 2023. "Can cryptocurrencies provide a viable hedging mechanism for benchmark index investors?," Research in International Business and Finance, Elsevier, vol. 64(C).
    11. Bellón, Carlos & Figuerola-Ferretti, Isabel, 2022. "Bubbles in Ethereum," Finance Research Letters, Elsevier, vol. 46(PB).
    12. Shaen Corbet & John W. Goodell & Samet Gunay & Kerem Kaskaloglu, 2023. "Are DeFi tokens a separate asset class from conventional cryptocurrencies?," Annals of Operations Research, Springer, vol. 322(2), pages 609-630, March.
    13. Kyriazis, Nikolaos & Papadamou, Stephanos & Tzeremes, Panayiotis & Corbet, Shaen, 2023. "The differential influence of social media sentiment on cryptocurrency returns and volatility during COVID-19," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 307-317.
    14. ?ikolaos A. Kyriazis, 2021. "Impacts of Stock Indices, Oil, and Twitter Sentiment on Major Cryptocurrencies during the COVID-19 First Wave," Bulletin of Applied Economics, Risk Market Journals, vol. 8(2), pages 133-146.
    15. Lian, Yu-Min & Chen, Jun-Home, 2021. "Pricing virtual currency-linked derivatives with time-inhomogeneity," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 424-439.
    16. 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).
    17. Jiang, Yonghong & Wu, Lanxin & Tian, Gengyu & Nie, He, 2021. "Do cryptocurrencies hedge against EPU and the equity market volatility during COVID-19? – New evidence from quantile coherency analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    18. Ashok, Shruti & Corbet, Shaen & Dhingra, Deepika & Goodell, John W. & Kumar, Satish & Yadav, Miklesh Prasad, 2022. "Are energy markets informationally smarter than equity markets? Evidence from the COVID-19 experience," Finance Research Letters, Elsevier, vol. 47(PB).
    19. Corbet, Shaen & Katsiampa, Paraskevi & Lau, Chi Keung Marco, 2020. "Measuring quantile dependence and testing directional predictability between Bitcoin, altcoins and traditional financial assets," International Review of Financial Analysis, Elsevier, vol. 71(C).
    20. Wang, Yi-Ran & Ma, Chao-Qun & Ren, Yi-Shuai, 2022. "A model for CBDC audits based on blockchain technology: Learning from the DCEP," Research in International Business and Finance, Elsevier, vol. 63(C).

    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:gam:jrisks:v:10:y:2022:i:5:p:107-:d:819454. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.