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Czasopisma
Central European Economic Journal
Tom 10 (2023): Zeszyt 57 (January 2023)
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Is Bitcoin an emerging market? A market efficiency perspective
Mateusz Skwarek
Mateusz Skwarek
| 04 wrz 2023
Central European Economic Journal
Tom 10 (2023): Zeszyt 57 (January 2023)
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Data publikacji:
04 wrz 2023
Zakres stron:
219 - 236
DOI:
https://doi.org/10.2478/ceej-2023-0013
Słowa kluczowe
bitcoin
,
market efficiency
,
emerging stock markets
,
long-range dependence
,
Hurst exponent
© 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
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
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
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
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
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
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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