When the market adjusts, the price shoots up. Large holders of that crypto can then cash in on the gains by dumping their coins, bringing the price down. Although exchanges know about these methods, stopping them isn’t all that simple, as the perpetrators know how to stay under the radar.
For the sake of clarity an explicit definition of short, medium, and long term is required. In this work short term refers to the 2–4 and 4–8 day period bands. Medium term refers to the 8–16 and 16–32 day bands. Long term will be used to refer to the 32–64, 64–128, 128–256 and 256–512 day bands. The short, medium, and long term bands will be considered separately to begin with, and then considered collectively alongside the results of the GSADF bubble test.

We set the stage for our formal econometric analysis by providing some graphical evidence. For example, in Figure 1, we see a close mapping of the prices of Bitcoin and Ethereum with their respective computing power values. Moreover, in Figure 2, we observe an even stronger mapping of the prices of Bitcoin and Ethereum with their respective network values. Interestingly, these graphs also show that when prices significantly exceed the trend in computing power or network (as was the case in late 2017), prices eventually fall and trace the trend in fundamentals. The convergence of prices to the trend with fundamentals suggests that fundamentals are the ultimate, long-run determinants of prices.
As this platform does business as a separate entity from Binance, the users’ digital assets will be stored in Binance.US wallets only.