Interpretation of visual scalograms is subjective so it is desirable to find a more quantifiable way to validate the strengthening of coherence in bubble regimes. Fig 6 shows the wavelet coherence over time for the different period bands, in the case of the “new authors” factor for Ethereum. Coherence values, plotted on the vertical axis, vary between zero and one. Time is plotted on the horizontal axis. The areas of the price time series that are recorded as bubble-like regimes using the GSADF test are shaded red.
When some of the most respected people on Wall Street make comments like that, it “takes a huge element of mainstream out of the market,” says Innes. Essentially, these heavy hitters were telling their minions that bitcoin wasn’t worth their time.

Importantly, cryptocurrencies can be exchanged for fiat currencies in special online markets, meaning each has a variable exchange rate with major world currencies, such as the U.S. dollar, British pound, European euro, and Japanese yen.
Although this test successfully detects single isolated bubbles, Phillips, Shi, and Yu [24] acknowledge it may suffer from reduced discriminatory power when applied to time series with multiple occurrences of bubbles. To overcome this weakness, a further enhancement was proposed, as a new method, called a generalized supremum ADF (GSADF) test. This test allows both the start and end points of data subsets to vary, which in turn enables the identification of multiple bubble regimes in one observed time series. The GSADF test is defined by