Adaptive market hypothesis: An empirical analysis of time –varying market efficiency of cryptocurrencies

Figures & data

Figure 1. Prices of Cryptocurrencies

Table 1. Summary statistics of cryptocurrencies returns

	Bitcoin	Litecoin	Monaro	Stellar
Mean	2309.499	31.093	53.957	0.073
Median	606.075	4.235	6.170	0.003
Maximum	19,497.40	358.340	469.200	0.896
Minimum	68.430	1.160	0.223	0.001
Std. Dev.	3416.512	53.793	89.162	0.131
Skewness	2.004	2.7140	2.075	2.105
Kurtosis	6.912	10.971	7.013	7.551
Jarque-Bera	2711*	8037*	2340*	2579*
	(0.000)	(0.000)	(0.000)	(0.000)
ADF test	−8.4410*	−2.676***	−13.51*	−9.126*
	(0.000)	(0.078)	(0.000)	(0.000)
Ljung-Box Q(20)	55.873$†$	48.310$†$	27.267	37.442$†$
ARCH-LM	321.503$†$	297.946$†$	6.992	279.534$†$
Observations	2074	2074	1685	1610

Notes: JB: the Jarque–Bera test statistic of normality has critical value of 5.9569. Q (20): the Ljung–Box test statistic testing for the presence of no autocorrelation in return has critical value of 31.4. ARCH-LM: the test statistic for the presence of heteroscedasticity has critical value of 31.4 at lag 20. The test statistics for most of the tests exceed the critical value, leading to a rejection of the null-hypothesis. * $†$ Rejection of null hypothesis at 5% level of significance.

Figure 2. P-values of Dominguez-Lobato test of Bitcoin

Figure 3. P-value of Generalized Spectral Test of Bitcoin

Figure 4. Stats of Automatic Portmanteau Test of Bitcoin

Figure 5. P-values of Dominguez-Lobato Test of Monero

Figure 6. P-values of Generalized Spectral test of Monero

Figure 7. Stats of Automatic Portmanteau Test of Monero

Figure 8. P-values of Dominguez-Lobato test of Litecoin

Figure 9. P-value of Generalized Spectral Test of Litecoin

Figure 10. Stats of Automatic Portmanteau Test of Litecoin

Figure 11. P-values of Dominguez–Lobato Test of Steller

Figure 12. P-values of Generalized Spectral Test

Figure 13. Stats of Automatic Portmanteau Test of Steller