Wavelet coherence plots as above highlight areas in the time-frequency space where the two series co-move. The warmer the colour, the higher the coherence (which can be interpreted as correlation) at that location in the time-frequency space; the colours used in this work range from dark blue (0, no coherence) to yellow (1, strong coherence). Statistically significant areas of coherence are surrounded by a thick black line.
However, about 310 users suffered a more serious breach, including the release of their names, birthdays, and zip codes.

We further explore the significance of cryptocurrency fundamentals at the aggregate market level using traditional asset pricing tests. For this analysis, we construct risk factors that are based on aggregate values of computing power and network. We denote the aggregate computing power factor with ACP and aggregate network factor with ANET. The innovation in constructing these factors is that we express them in cryptocurrency return units following the factor mimicking portfolio approach (Knez et al. 1994, Lamont 2001, Vassalou 2003).
Numerous others have also made their mark on the industry, some of whom Cointelegraph lists in its top 100 people in crypto and blockchain for 2021.