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Is Bitcoin an emerging market? A market efficiency perspective Cover

Is Bitcoin an emerging market? A market efficiency perspective

Central European Economic Journal
Volume 10 (2023): Issue 57 (January 2023)
By: Mateusz SkwarekORCID  
Open Access
|Sep 2023

Figures & Tables

Figure 1.

Hurst exponents of daily returns for Bitcoin and the MSCI Emerging Markets IndexNote: The date denotes the endpoints of the sliding windows. The red and blue lines mean Hurst exponents for Bitcoin and MSCI Emerging Markets Index, respectively. The dashed line denotes an efficient market – the value of the Hurst exponent is 0.5. Source: Own work
Hurst exponents of daily returns for Bitcoin and the MSCI Emerging Markets IndexNote: The date denotes the endpoints of the sliding windows. The red and blue lines mean Hurst exponents for Bitcoin and MSCI Emerging Markets Index, respectively. The dashed line denotes an efficient market – the value of the Hurst exponent is 0.5. Source: Own work

Figure 2.

Dynamic correlation between Bitcoin and MSCI Emerging Markets Index using R/S at different lengths of the rolling window: 251 (Panel A), 126 (Panel B)Note: Black and grey lines indicate correlation coefficients and p-values, respectively. The horizontal red line means p-values at 10%. Rolling window sizes are 251 (Panel A) and 126 Hurst exponents (Panel B). The date corresponds to the endpoints of the sliding windows for the correlation coefficient. Source: Own calculations
Dynamic correlation between Bitcoin and MSCI Emerging Markets Index using R/S at different lengths of the rolling window: 251 (Panel A), 126 (Panel B)Note: Black and grey lines indicate correlation coefficients and p-values, respectively. The horizontal red line means p-values at 10%. Rolling window sizes are 251 (Panel A) and 126 Hurst exponents (Panel B). The date corresponds to the endpoints of the sliding windows for the correlation coefficient. Source: Own calculations

Figure 3.

Dynamic correlation on the first differences of Hurst exponents between Bitcoin and MSCI Emerging Markets IndexNote: Black and grey lines indicate correlation coefficients and p-values respectively. The horizontal red line means p-values at 10%. Rolling window sizes are 251 (Panel A) and 126 Hurst exponents (Panel B). The date corresponds to the endpoints of the sliding windows for the correlation coefficient. Source: Own calculation
Dynamic correlation on the first differences of Hurst exponents between Bitcoin and MSCI Emerging Markets IndexNote: Black and grey lines indicate correlation coefficients and p-values respectively. The horizontal red line means p-values at 10%. Rolling window sizes are 251 (Panel A) and 126 Hurst exponents (Panel B). The date corresponds to the endpoints of the sliding windows for the correlation coefficient. Source: Own calculation

Figure 4.

Dynamic Kendall correlation between Bitcoin and MSCI Emerging Markets Index using R/S at different lengths of the rolling window: 251 (Panel A), 126 (Panel B)Note: Black and grey lines indicate correlation coefficients and p-values, respectively. The horizontal red line means p-values at 10%. Rolling window sizes are 251 (Panel A) and 126 Hurst exponents (Panel B). The date corresponds to the endpoints of the sliding windows for the correlation coefficient. Source: Own work
Dynamic Kendall correlation between Bitcoin and MSCI Emerging Markets Index using R/S at different lengths of the rolling window: 251 (Panel A), 126 (Panel B)Note: Black and grey lines indicate correlation coefficients and p-values, respectively. The horizontal red line means p-values at 10%. Rolling window sizes are 251 (Panel A) and 126 Hurst exponents (Panel B). The date corresponds to the endpoints of the sliding windows for the correlation coefficient. Source: Own work

Figure 5.

Dynamic correlation between Bitcoin and MSCI Emerging Markets Index using DFA at different lengths of the rolling window: 251 (Panel A), 126 (Panel B)Note: Black and grey lines indicate correlation coefficients and p-values, respectively. The horizontal red line means p-values at 10%. Rolling window sizes are 251 (Panel A) and 126 Hurst exponents (Panel B). The date corresponds to the endpoints of the sliding windows for the correlation coefficient. Source: Own calculations
Dynamic correlation between Bitcoin and MSCI Emerging Markets Index using DFA at different lengths of the rolling window: 251 (Panel A), 126 (Panel B)Note: Black and grey lines indicate correlation coefficients and p-values, respectively. The horizontal red line means p-values at 10%. Rolling window sizes are 251 (Panel A) and 126 Hurst exponents (Panel B). The date corresponds to the endpoints of the sliding windows for the correlation coefficient. Source: Own calculations

Figure 6.

Dynamic Spearman correlation between Bitcoin and MSCI Emerging Markets Index based on Hurst exponents using R/S, DFA and First differences of Hurst exponents in the rolling window of 251 observationsNote: Blue and red lines indicate correlation coefficients based on Hurst exponents using R/S and DFA, respectively. The green line means correlation coefficients based on the first differences of Hurst exponents using R/S. The grey colour indicates the range of the correlation values (minimum, maximum) relative to the time point (x-axis). The correlation coefficients located in the area between two horizontal black dashed lines are statistically insignificant (p-values less than 10%). The date corresponds to the endpoints of the sliding windows for the correlation coefficient. Source: Own calculation
Dynamic Spearman correlation between Bitcoin and MSCI Emerging Markets Index based on Hurst exponents using R/S, DFA and First differences of Hurst exponents in the rolling window of 251 observationsNote: Blue and red lines indicate correlation coefficients based on Hurst exponents using R/S and DFA, respectively. The green line means correlation coefficients based on the first differences of Hurst exponents using R/S. The grey colour indicates the range of the correlation values (minimum, maximum) relative to the time point (x-axis). The correlation coefficients located in the area between two horizontal black dashed lines are statistically insignificant (p-values less than 10%). The date corresponds to the endpoints of the sliding windows for the correlation coefficient. Source: Own calculation

Descriptive statistics for the logarithmic return series of Bitcoin (BTC) and the MSCI Emerging Markets Index from 13 September 2011 to 11 August 2022

BTCMSCI Emerging Markets
Mean0.00291.78E-05
Median0.00264.55E-04
Maximum0.48485.58E-02
Minimum-0.6639-6.94E-02
Std. Dev.0.05580.0101
Skewness-1.0666-0.5098
Kurtosis23.37988.0321
ADF-11.764***-14.166***
Observations28352835
DOI: https://doi.org/10.2478/ceej-2023-0013 | Journal eISSN: 2543-6821 | Journal ISSN: 2544-9001
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Language: English
Page range: 219 - 236
Published on: Sep 4, 2023
Published by: Faculty of Economic Sciences, University of Warsaw
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
bitcoin,
market efficiency,
emerging stock markets,
long-range dependence,
Hurst exponent
Related subjects:
Business and economics,
Political economics,
Economic theory, systems and structures,
Microeconomics,
Macroeconomics,
Economic policy

© 2023 Mateusz Skwarek, published by Faculty of Economic Sciences, University of Warsaw
This work is licensed under the Creative Commons Attribution 4.0 License.

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