What drives cryptocurrency returns? A sparse statistical jump model approach

Research output: Contribution to conferenceAbstractpeer-review

Abstract

The statistical sparse jump model, a recently developed, robust and interpretable regime-switching model, is used to analyze the factors driving the return dynamics of the largest cryptocurrencies. This method simultaneously incorporates feature selection, parameter estimation, and state classification. A wide range of candidate features is considered, including cryptocurrency, sentiment, and financial market-based time series that are known to influence cryptocurrency returns. The empirical analysis demonstrates that a three-state model provides a good representation of the cryptocurrency return dynamics. The latent states are interpreted as a bull, neutral, and bear market regimes, respectively. Through the data-driven feature selection approach, the significant factors are identified, and insignificant ones are excluded. The results indicate that within the candidate features, the first moments of returns, features indicating trends and reversal signals, market activity, and public attention are key drivers of crypto market dynamics.
Original languageEnglish
Publication statusPublished - 2023 Aug 3
Event 6th International Conference on Econometrics and Statistics - Waseda Univeristy, Tokyo, Japan
Duration: 2023 Aug 12023 Aug 3
http://www.cmstatistics.org/EcoSta2023/index.php

Conference

Conference 6th International Conference on Econometrics and Statistics
Abbreviated title EcoSta 2023
Country/TerritoryJapan
CityTokyo
Period2023/08/012023/08/03
Internet address

Subject classification (UKÄ)

  • Economics

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