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Is Bitcoin an emerging market? A market efficiency perspective

Mateusz Skwarek

Mateusz Skwarek

Poznań University of Economics and Business, Institute of Accounting and Finance ManagementPoznań, Poland
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Skwarek, Mateusz
  
04 set 2023
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Pubblicato online: 04 set 2023
Pagine: 219 - 236
DOI: https://doi.org/10.2478/ceej-2023-0013
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© 2023 Mateusz Skwarek, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

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

BTC MSCI Emerging Markets
Mean 0.0029 1.78E-05
Median 0.0026 4.55E-04
Maximum 0.4848 5.58E-02
Minimum -0.6639 -6.94E-02
Std. Dev. 0.0558 0.0101
Skewness -1.0666 -0.5098
Kurtosis 23.3798 8.0321
ADF -11.764*** -14.166***
Observations 2835 2835
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Economia e business, Economia politica, Teoria economica, sistemi e strutture, Microeconomia, Macroeconomia, Politica economica
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