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CRIX an index for cryptocurrencies

Author

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  • Simon Trimborn
  • Wolfgang Karl Hardle

Abstract

The cryptocurrency market is unique on many levels: Very volatile, frequently changing market structure, emerging and vanishing of cryptocurrencies on a daily level. Following its development became a difficult task with the success of cryptocurrencies (CCs) other than Bitcoin. For fiat currency markets, the IMF offers the index SDR and, prior to the EUR, the ECU existed, which was an index representing the development of European currencies. Index providers decide on a fixed number of index constituents which will represent the market segment. It is a challenge to fix a number and develop rules for the constituents in view of the market changes. In the frequently changing CC market, this challenge is even more severe. 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. CRIX is chosen by model selection such that it represents the market well to enable each interested party studying economic questions in this market and to invest into the market. The diversified nature of the CC market makes the inclusion of altcoins in the index product critical to improve tracking performance. We have shown that assigning optimal weights to altcoins helps to reduce the tracking errors of a CC portfolio, despite the fact that their market cap is much smaller relative to Bitcoin. The codes used here are available via www.quantlet.de.

Suggested Citation

  • Simon Trimborn & Wolfgang Karl Hardle, 2020. "CRIX an index for cryptocurrencies," Papers 2009.09782, arXiv.org.
  • Handle: RePEc:arx:papers:2009.09782
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    References listed on IDEAS

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    1. Wilko Bolt & Maarten R.C. Van Oordt, 2020. "On the Value of Virtual Currencies," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(4), pages 835-862, June.
    2. Wilko Bolt & Maarten R.C. Van Oordt, 2020. "On the Value of Virtual Currencies," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(4), pages 835-862, June.
    3. Horton, Nicholas J. & Kleinman, Ken P., 2007. "Much Ado About Nothing: A Comparison of Missing Data Methods and Software to Fit Incomplete Data Regression Models," The American Statistician, American Statistical Association, vol. 61, pages 79-90, February.
    4. Elendner, Hermann & Trimborn, Simon & Ong, Bobby & Lee, Teik Ming, 2016. "The cross-section of crypto-currencies as financial assets: An overview," SFB 649 Discussion Papers 2016-038, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. Kanazawa, Yuichiro, 1993. "Hellinger distance and Kullback--Leibler loss for the kernel density estimator," Statistics & Probability Letters, Elsevier, vol. 18(4), pages 315-321, November.
    7. Härdle, Wolfgang Karl & Trimborn, Simon, 2015. "CRIX or evaluating blockchain based currencies," SFB 649 Discussion Papers 2015-048, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Sha Wang & Jean-Philippe Vergne, 2017. "Buzz Factor or Innovation Potential: What Explains Cryptocurrencies’ Returns?," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-17, January.
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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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