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CRIX or evaluating blockchain based currencies

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  • Simon Trimborn
  • Wolfgang Karl Härdle

Abstract

The S&P500 or DAX30 are important benchmarks for the financial industry. These and other indices describe different compositions of certain segments of the financial markets. For currency markets, the IMF offers the index SDR. Prior to the Euro, the ECU existed, which was an index representing the development of European currencies. It is surprising, though, to see that the common index providers have not mapped emerging e-coins into an index yet because with cryptos like Bitcoin, a new kind of asset of great public interest has arisen. Index providers decide on a fixed number of index constituents which will represent the market segment. It is a huge challenge to set this fixed number and develop the rules to find the constituents, especially since markets change and this has to be taken into account. A method relying on the AIC is proposed to quickly react to market changes and therefore enable us to create an index, referred to as CRIX, for the cryptocurrency market. The codes used to obtain the results in this paper are available via www.quantlet.de .

Suggested Citation

  • Simon Trimborn & Wolfgang Karl Härdle, 2016. "CRIX or evaluating blockchain based currencies," SFB 649 Discussion Papers SFB649DP2016-021, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    • Handle: RePEc:hum:wpaper:sfb649dp2016-021
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Schilling, Linda & Uhlig, Harald, 2019. "Some simple bitcoin economics," Journal of Monetary Economics, Elsevier, vol. 106(C), pages 16-26.
    2. Trimborn, Simon & Härdle, Wolfgang Karl, 2018. "CRIX an Index for cryptocurrencies," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 107-122.
    3. Simon Trimborn & Mingyang Li & Wolfgang Karl Härdle, 2020. "Investing with Cryptocurrencies—a Liquidity Constrained Investment Approach," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 18(2), pages 280-306.
    4. Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2021. "VCRIX — A volatility index for crypto-currencies," International Review of Financial Analysis, Elsevier, vol. 78(C).
    5. Shi Chen & Cathy Yi-Hsuan Chen & Wolfgang Karl Hardle, 2020. "A first econometric analysis of the CRIX family," Papers 2009.12129, arXiv.org.
    6. Konstantin Häusler & Hongyu Xia, 2022. "Indices on cryptocurrencies: an evaluation," Digital Finance, Springer, vol. 4(2), pages 149-167, September.
    7. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Hou, Ai Jun & Wang, Weining, 2018. "Pricing Cryptocurrency options: the case of CRIX and Bitcoin," IRTG 1792 Discussion Papers 2018-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    8. Laura Alessandretti & Abeer ElBahrawy & Luca Maria Aiello & Andrea Baronchelli, 2018. "Anticipating Cryptocurrency Prices Using Machine Learning," Complexity, Hindawi, vol. 2018, pages 1-16, November.
    9. Stefan Cristian, 2018. "Tales from the crypt: might cryptocurrencies spell the death of traditional money? - A quantitative analysis -," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 12(1), pages 918-930, May.
    10. Shi Chen & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle & TM Lee & Bobby Ong, 2016. "A first econometric analysis of the CRIX family," SFB 649 Discussion Papers SFB649DP2016-031, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Hermann Elendner & Simon Trimborn & Bobby Ong & Teik Ming Lee, 2016. "The Cross-Section of Crypto-Currencies as Financial Assets: An Overview," SFB 649 Discussion Papers SFB649DP2016-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Nadler, Philip & Guo, Yike, 2020. "The fair value of a token: How do markets price cryptocurrencies?," Research in International Business and Finance, Elsevier, vol. 52(C).

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    More about this item

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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