Cryptocurrencies and Long-Range Trends

Monica Alexiadou, Emmanouil Sofianos, Periklis Gogas and Theophilos Papadimitriou
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Monica Alexiadou: Department of Economics, Democritus University of Thrace, 69100 Komotini, Greece

IJFS, 2023, vol. 11, issue 1, 1-17

Abstract: In this study we investigate possible long-range trends in the cryptocurrency market. We employed the Hurst exponent in a sample covering the period from 1 January 2016 to 26 March 2021. We calculated the Hurst exponent in three non-overlapping consecutive windows and in the whole sample. Using these windows, we assessed the dynamic evolution in the structure and long-range trend behavior of the cryptocurrency market and evaluated possible changes in their behavior towards an efficient market. The innovation of this research is that we employ the Hurst exponent to identify the long-range properties, a tool that is seldomly used in analysis of this market. Furthermore, the use of both the R/S and the DFA analysis and the use of non-overlapping windows enhance our research’s novelty. Finally, we estimated the Hurst exponent for a wide sample of cryptocurrencies that covered more than 80% of the entire market for the last six years. The empirical results reveal that the returns follow a random walk making it difficult to accurately forecast them.

Keywords: cryptocurrencies; time series; autocorrelation; Hurst exponent; Rescaled Range Analysis; Detrended Fluctuation Analysis (search for similar items in EconPapers)
JEL-codes: F2 F3 F41 F42 G1 G2 G3 (search for similar items in EconPapers)
Date: 2023
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