For upcoming projects, DogeZilla is planning to launch an NFTs Invasion Series in early 2022.
As we don’t know exactly how to classify them, it’s difficult to attribute a direct causality to a specific factor and a crypto’s rise or dive in value.
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China’s crackdown has delivered a windfall to international groups that mint digital tokens
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“That’s one of the things we truly focused on, providing a means in which the community could talk to the team,” Karony said. This included ask-me-anything sessions held on Discord for the curious to learn more.
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Although analysis of a single factor and cryptocurrency combination, as above, is of interest, more general findings across multiple cryptocurrency/factor combinations can also be pursued. Fig 7 shows, for each cryptocurrency and factor combination, the mean coherence values during the bubble and non-bubble regimes. Each horizontal subplot shows a different coherence period band, from the lowest period band (2–4 days) at the top to the highest period band (256–512 days) at the bottom. As the duration of data for each cryptocurrency varies, certain ranges are left blank when that cryptocurrency does not have enough data to produce values for such bands.
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In the short term, situations occur where the factors lead the price and where the factors lag the price. However in most cases, the factor lags the price in the short term (seen by upward facing arrows near the top of each scalogram). This is understandable given short term changes appear likely to be the result of particular events, as discussed above. It is likely the market price will reflect the event quicker than social media; social media may experience a longer interval of discussion and activity relating to the original event and resulting price change.
NYC is getting its own city coin in line with the incoming mayor's crypto hub vision
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Turning to the relationships between different cryptocurrencies, significant coherence is observed in the medium and long term between Bitcoin and Litecoin, which it is believed is due to their similarity. It is seen that short term correlations between the cryptocurrencies considered here are dependent again on news items and market wide events. We want your feedback. Do these Subject Areas make sense for this article? Click the target next to the incorrect Subject Area and let us know. Thanks for your help!
We should also point out that if we had been given labels on the Y-axis (which obviously we are not), it might become clear that these “daily Covid cases” refer to US Covid cases. Because while a US chart looks exactly like the one above, a chart showing worldwide Covid cases doesn’t; instead it looks like this (according to Google):