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Blockchain mechanism and distributional characteristics of cryptos

Author

Listed:
  • Min-Bin Lin
  • Kainat Khowaja
  • Cathy Yi-Hsuan Chen
  • Wolfgang Karl Hardle
Abstract
We investigate the relationship between underlying blockchain mechanism of cryptocurrencies and its distributional characteristics. In addition to price, we emphasise on using actual block size and block time as the operational features of cryptos. We use distributional characteristics such as fourier power spectrum, moments, quantiles, global we optimums, as well as the measures for long term dependencies, risk and noise to summarise the information from crypto time series. With the hypothesis that the blockchain structure explains the distributional characteristics of cryptos, we use characteristic based spectral clustering to cluster the selected cryptos into five groups. We scrutinise these clusters and find that indeed, the clusters of cryptos share similar mechanism such as origin of fork, difficulty adjustment frequency, and the nature of block size. This paper provides crypto creators and users with a better understanding toward the connection between the blockchain protocol design and distributional characteristics of cryptos.

Suggested Citation

  • Min-Bin Lin & Kainat Khowaja & Cathy Yi-Hsuan Chen & Wolfgang Karl Hardle, 2020. "Blockchain mechanism and distributional characteristics of cryptos," Papers 2011.13240, arXiv.org, revised Aug 2021.
    • Handle: RePEc:arx:papers:2011.13240
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    References listed on IDEAS

    as
    1. Wolfgang Karl Härdle & Campbell R Harvey & Raphael C G Reule, 2020. "Understanding Cryptocurrencies," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 181-208.
    2. 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.
    3. Yhlas Sovbetov, 2018. "Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 2(2), pages 1-27.
    4. Iwamura, Mitsuru & Kitamura, Yukinobu & 北村, 行伸 & Matsumoto, Tsutomu & Saito, Kenji, 2019. "Can We Stabilize the Price of a Cryptocurrency?: Understanding the Design of Bitcoin and Its Potential to Compete with Central Bank Money," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 60(1), pages 41-60, June.
    5. Trimborn, Simon & Härdle, Wolfgang Karl, 2018. "CRIX an Index for cryptocurrencies," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 107-122.
    6. Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2018. "Understanding Latent Group Structure of Cryptocurrencies Market: A Dynamic Network Perspective," IRTG 1792 Discussion Papers 2018-032, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    7. Zimmerman, Peter, 2020. "Blockchain structure and cryptocurrency prices," Bank of England working papers 855, Bank of England.
    8. Wolfgang Karl Hardle & Campbell R. Harvey & Raphael C. G. Reule, 2020. "Editorial: Understanding Cryptocurrencies," Papers 2007.14702, arXiv.org.
    9. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "High frequency volatility co-movements in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 35-52.
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    Cited by:

    1. Ingo Weber & Mark Staples, 2022. "Programmable money: next-generation blockchain-based conditional payments," Digital Finance, Springer, vol. 4(2), pages 109-125, September.
    2. Zinovyev, Elizaveta & Reule, Raphael C. G. & Härdle, Wolfgang, 2021. "Understanding Smart Contracts: Hype or hope?," IRTG 1792 Discussion Papers 2021-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Wang, Yifu & Lu, Wanbo & Lin, Min-Bin & Ren, Rui & Härdle, Wolfgang Karl, 2024. "Cross-exchange crypto risk: A high-frequency dynamic network perspective," International Review of Financial Analysis, Elsevier, vol. 94(C).
    4. repec:wsr:ecbook:2022:i:viii-006 is not listed on IDEAS

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    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General

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