We explore the evolution of the informational efficiency in 45 cryptocurrency markets and 16 international stock markets before and during COVID-19 pandemic. The measures of Largest Lyapunov Exponent (LLE) based on the Rosenstein's method and Approximate Entropy (ApEn), which are robust to small samples, are applied to price time series in order to estimate degrees of stability and irregularity in cryptocurrency and international stock markets. The amount of regularity infers on the unpredictability of fluctuations. The t-test and F-test are performed on estimated LLE and ApEn. In total, 36 statistical tests are performed to check for differences between time periods (pre- versus during COVID-19 pandemic samples) on the one hand, as well as check for differences between markets (cryptocurrencies versus stocks), on the other hand. During the COVID-19 pandemic period it was found that (a) the level of stability in cryptocurrency markets has significantly diminished while the irregularity level significantly augmented, (b) the level of stability in international equity markets has not changed but gained more irregularity, (c) cryptocurrencies became more volatile, (d) the variability in stability and irregularity in equities has not been affected, (e) cryptocurrency and stock markets exhibit a similar degree of stability in price dynamics, whilst finally (f) cryptocurrency exhibit a low level of regularity compared to international equity markets. We find that cryptos showed more instability and more irregularity during the COVID-19 pandemic compared to international stock markets. Thus, from an informational efficiency perspective, investing in digital assets during big crises as the COVID-19 pandemic, could be considered riskier as opposed to equities.

我们探讨了在COVID-19大流行之前和期间，在45个加密货币市场和16个国际股票市场中信息效率的演变。基于Rosenstein方法的最大Lyapunov指数（LLE）和对小样本具有鲁棒性的近似熵（ApEn）的度量被应用于价格时间序列，以估计加密货币和国际股票市场的稳定和不规则程度。规律性推断出波动的不可预测性。该牛逼-测试和˚F-test在估计的LLE和ApEn上执行。总共进行了36种统计检验，一方面检查时间段之间（COVID-19大流行样本之前或期间）之间的差异，另一方面检查市场之间的差异（加密货币与股票之间的差异）。在COVID-19大流行期间，我们发现（a）加密货币市场的稳定水平已大大降低，而违规水平则显着增加，（b）国际股票市场的稳定水平并未改变，但出现了更多的违规行为， （c）加密货币变得更加动荡，（d）稳定性和股票不规则性的变化未受到影响，（e）加密货币和股票市场在价格动态方面表现出相似的稳定性，而最后（f）加密货币与国际股票市场相比表现出较低的规律性。我们发现，与国际股票市场相比，COVID-19大流行期间加密货币显示出更多的不稳定性和更多的不规则性。因此，从信息效率的角度来看，在重大危机（COVID-19大流行）中投资数字资产可被视为比股票更具风险。