CRIX an Index for cryptocurrencies

Arbeitspapier

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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: IRTG 1792 Discussion Paper ; No. 2020-009

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Model Construction and Estimation ; Model Evaluation, Validation, and Selection ; General Financial Markets: General (includes Measurement and Data)
• Thema: Index construction ; Model selection ; Bitcoin ; Cryptocurrency ; CRIX ; Altcoin

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Trimborn, Simon ; Härdle, Wolfgang Karl
• Ereignis: Veröffentlichung
• (wer): Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series"
• (wo): Berlin
• (wann): 2020

Weitere Informationen

• Handle: http://hdl.handle.net/10419/230815
• Letzte Aktualisierung: 10.03.2025, 11:41 MEZ