IDEAS home Printed from https://ideas.repec.org/a/ces/ifofor/v21y2020i01p41-45.html
   My bibliography  Save this article

What Drives Bitcoins? A Comparative Study of Bitcoin Prices and Financial Asset Classes

Author

Listed:
  • Florian Bartholomae
  • Pierre Rafih

Abstract

No abstract is available for this item.

Suggested Citation

  • Florian Bartholomae & Pierre Rafih, 2020. "What Drives Bitcoins? A Comparative Study of Bitcoin Prices and Financial Asset Classes," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 21(01), pages 41-45, April.
    • Handle: RePEc:ces:ifofor:v:21:y:2020:i:01:p:41-45
    as

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/CESifo-Forum-2020-1-bartholomae-rafih-bitcoin-march.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cadsby, Charles Bram & Ratner, Mitchell, 1992. "Turn-of-month and pre-holiday effects on stock returns: Some international evidence," Journal of Banking & Finance, Elsevier, vol. 16(3), pages 497-509, June.
    2. Balcilar, Mehmet & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2017. "Can volume predict Bitcoin returns and volatility? A quantiles-based approach," Economic Modelling, Elsevier, vol. 64(C), pages 74-81.
    3. Kunkel, Robert A. & Compton, William S. & Beyer, Scott, 2003. "The turn-of-the-month effect still lives: the international evidence," International Review of Financial Analysis, Elsevier, vol. 12(2), pages 207-221.
    4. Blau, Benjamin M., 2018. "Price dynamics and speculative trading in Bitcoin," Research in International Business and Finance, Elsevier, vol. 43(C), pages 15-21.
    5. Katsiampa, Paraskevi, 2017. "Volatility estimation for Bitcoin: A comparison of GARCH models," Economics Letters, Elsevier, vol. 158(C), pages 3-6.
    6. Dyhrberg, Anne Haubo, 2016. "Hedging capabilities of bitcoin. Is it the virtual gold?," Finance Research Letters, Elsevier, vol. 16(C), pages 139-144.
    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. Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2022. "Semi-nonparametric risk assessment with cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 59(C).
    2. Kosc, Krzysztof & Sakowski, Paweł & Ślepaczuk, Robert, 2019. "Momentum and contrarian effects on the cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 691-701.
    3. Yaya, OlaOluwa S. & Ogbonna, Ahamuefula E. & Olubusoye, Olusanya E., 2019. "How persistent and dynamic inter-dependent are pricing of Bitcoin to other cryptocurrencies before and after 2017/18 crash?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    4. Kurka, Josef, 2019. "Do cryptocurrencies and traditional asset classes influence each other?," Finance Research Letters, Elsevier, vol. 31(C), pages 38-46.
    5. Boako, Gideon & Tiwari, Aviral Kumar & Roubaud, David, 2019. "Vine copula-based dependence and portfolio value-at-risk analysis of the cryptocurrency market," International Economics, Elsevier, vol. 158(C), pages 77-90.
    6. Achraf Ghorbel & Wajdi Frikha & Yasmine Snene Manzli, 2022. "Testing for asymmetric non-linear short- and long-run relationships between crypto-currencies and stock markets," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 387-425, September.
    7. 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.
    8. Parthajit Kayal & G. Balasubramanian, 2021. "Excess Volatility in Bitcoin: Extreme Value Volatility Estimation," IIM Kozhikode Society & Management Review, , vol. 10(2), pages 222-231, July.
    9. Li, Xiao & Wu, Ruoxi & Wang, Chen, 2024. "Impacts of bitcoin on monetary system: Is China's bitcoin ban necessary?," Research in International Business and Finance, Elsevier, vol. 69(C).
    10. Wei Zhang & Pengfei Wang & Xiao Li & Dehua Shen, 2018. "Some stylized facts of the cryptocurrency market," Applied Economics, Taylor & Francis Journals, vol. 50(55), pages 5950-5965, November.
    11. Inés Jiménez & Andrés Mora-Valencia & Trino-Manuel Ñíguez & Javier Perote, 2020. "Portfolio Risk Assessment under Dynamic (Equi)Correlation and Semi-Nonparametric Estimation: An Application to Cryptocurrencies," Mathematics, MDPI, vol. 8(12), pages 1-24, November.
    12. Hau, Liya & Zhu, Huiming & Shahbaz, Muhammad & Sun, Wuqin, 2021. "Does transaction activity predict Bitcoin returns? Evidence from quantile-on-quantile analysis," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    13. 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).
    14. Bouri, Elie & Gupta, Rangan & Lahiani, Amine & Shahbaz, Muhammad, 2018. "Testing for asymmetric nonlinear short- and long-run relationships between bitcoin, aggregate commodity and gold prices," Resources Policy, Elsevier, vol. 57(C), pages 224-235.
    15. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    16. Pal, Debdatta & Mitra, Subrata K., 2019. "Hedging bitcoin with other financial assets," Finance Research Letters, Elsevier, vol. 30(C), pages 30-36.
    17. Panagiotidis, Theodore & Stengos, Thanasis & Vravosinos, Orestis, 2019. "The effects of markets, uncertainty and search intensity on bitcoin returns," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 220-242.
    18. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
    19. Ángeles Cebrián-Hernández & Enrique Jiménez-Rodríguez, 2021. "Modeling of the Bitcoin Volatility through Key Financial Environment Variables: An Application of Conditional Correlation MGARCH Models," Mathematics, MDPI, vol. 9(3), pages 1-16, January.
    20. Canh, Nguyen Phuc & Wongchoti, Udomsak & Thanh, Su Dinh & Thong, Nguyen Trung, 2019. "Systematic risk in cryptocurrency market: Evidence from DCC-MGARCH model," Finance Research Letters, Elsevier, vol. 29(C), pages 90-100.

    More about this item

    Statistics

    Access and download statistics

    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:ces:ifofor:v:21:y:2020:i:01:p:41-45. 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: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/ifooode.html .

    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.