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Time-Series Analysis Of The Most Common Cryptocurrencies

Author

Listed:
  • Domagoj Sajter

    (J. J. Strossmayer University of Osijek)

Abstract

This paper aims to gain and improve understanding of the three most common cryptocurrencies (Bitcoin, Ethereum and Ripple) by applying standard econometric tools upon their time-series data. Cryptocurrencies’ returns are compared to six major stock indices: two American (S&P500 and Russell 2000), one European (Stoxx 600), one Japanese (Nikkei 225), one Chinese (Hong Kong Hang Seng) and a global index (S&P Global 1200). The findings indicate that observed cryptocurrencies could be regarded as a new asset class, a fully digital, sui-generis financial instruments, as they are not coherently connected to the stock market. However, allocating capital into cryptocurrencies remains in the domain of pure speculation due to their strong volatility.

Suggested Citation

  • Domagoj Sajter, 2019. "Time-Series Analysis Of The Most Common Cryptocurrencies," Economic Thought and Practice, Department of Economics and Business, University of Dubrovnik, vol. 28(1), pages 267-282, june.
  • Handle: RePEc:avo:emipdu:v:28:y:2019:i:1:p:267-282
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    References listed on IDEAS

    as
    1. Yukun Liu & Aleh Tsyvinski, 2018. "Risks and Returns of Cryptocurrency," NBER Working Papers 24877, National Bureau of Economic Research, Inc.
    2. Christian Masiak & Joern H. Block & Tobias Masiak & Matthias Neuenkirch & Katja N. Pielen, 2018. "The Market Cycles of ICOs, Bitcoin, and Ether," Research Papers in Economics 2018-04, University of Trier, Department of Economics.
    3. 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.
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    Cited by:

    1. Zdravka Aljinović & Branka Marasović & Tea Šestanović, 2021. "Cryptocurrency Portfolio Selection—A Multicriteria Approach," Mathematics, MDPI, vol. 9(14), pages 1-21, July.
    2. Zdravka Aljinoviæ & Tea Šestanoviæ & Blanka Škrabiæ Periæ, 2022. "A New Evidence of the Relationship between Cryptocurrencies and other Assets from the COVID-19 Crisis," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, vol. 70(7-8), pages 603-621, July.
    3. Tea Livaic & Ana Perisic, 2019. "What can Google Tell us about Bitcoin Trading Volume in Croatia? Evidence from the Online Marketplace Localbitcoins," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 17(4), pages 707-715.

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    More about this item

    Keywords

    blockchain; cryptocurrencies; time-series; financial markets;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G29 - Financial Economics - - Financial Institutions and Services - - - Other
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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