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CRIX or evaluating blockchain based currencies

Author

Listed:
  • Trimborn, Simon
  • Härdle, Wolfgang Karl

Abstract

The S&P500 or DAX30 are important benchmarks for the financial industry. The first mimics the performance of the major US on the NYSE, AMEX and NASDAQ, while the second does the same for the German Prime Share sector. These and other indices describe different compositions of certain segments of the financial markets. It is surprising, though, to see that emerging e-coins have not been mapped into an index yet because with cryptos like Bitcoin, a new kind of asset of great public interest has arisen. One difficulty is that data sources are scarce and an effort has to be made to collect data with the necessary frequency. Another one is buried in the construction of indices. Usually, the index provider decides 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. For volatile markets like the crypto market, having a fixed number of index constituents is an even stronger constraint since the liquidity changes very frequently. 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. For further investigation of the new methodology, an application to the German and Mexican stock markets is provided. The results show that this methodology provides a more accurate benchmark compared to the DAX and IPC, the current market indices for Germany and Mexico. The codes used to obtain the results in this paper are available via www.quantlet.de.

Suggested Citation

  • Trimborn, Simon & Härdle, Wolfgang Karl, 2016. "CRIX or evaluating blockchain based currencies," SFB 649 Discussion Papers 2016-021, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Handle: RePEc:zbw:sfb649:sfb649dp2016-021
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    References listed on IDEAS

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    2. Ilyas Agakishiev & Wolfgang Karl Härdle & Denis Becker & Xiaorui Zuo, 2025. "Regime switching forecasting for cryptocurrencies," Digital Finance, Springer, vol. 7(1), pages 107-131, March.

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    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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