The bears tried to pull Bitcoin below the breakout level at $67,000 on Nov. 9 but they could not sustain the lower levels. The modest pullback indicates that bulls are buying on every minor dip.
Much like Dogecoin, it is cryptocurrency that was started off the back of an internet meme.
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Last year, a California man pleaded guilty to a mining fraud of at least $722 million through the BitClub Network. In February, a New York man pleaded guilty to running a Ponzi-like hedge crypto fund that stole about $90 million from more than 100 investors.
With all these shortcomings when put against most of the competition, Safemoon is definitely in trouble. There is a lot that Safemoon team needs to do to make the coin competitive. Otherwise, few people will be interested in this Safemoon. This means low demand, and that's how Safemoon's coin value will crumble.
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SafeMoon is available at dirt cheap price and the coin remains to be low-hanging fruit for investors. Even for a mere $10, investors can get more than 2.5 million tokens. Investors need to make use of the dip and add in bags of tokens, for when the coin reaches a milestone, their investment can spike tenfold.
Decentralized NFT Marketplace: The EverGrow team is also creating the world's first decentralized NFT lending platform. The platform will be based on BSC, which would enable NFT owners to easily borrow against their NFTs as collateral at reasonable interest rates without having to sell them. This will allow individuals to generate money just by lending their NFTs.
China’s crackdown has delivered a windfall to international groups that mint digital tokens
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The first cryptocurrency was bitcoin. The bitcoin domain was registered in 2008, but the first transaction took place in 2009. It was developed by someone called ‘Satoshi Nakamoto’. However, there is speculation that Nakamoto is a pseudonym as the bitcoin creator is notoriously secretive, and no one knows whether ‘he’ is a person or a group.
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Wavelets are wavelike functions used to transform signals into a representation which has time and frequency domain components. Visually wavelets appear as wave-like oscillations with an amplitude that starts at zero, increases, then returns to zero. Another way to consider a wavelet is as a bandpass filter, which can be applied to a time series under investigation, letting through only components of the time series within a finite range of frequencies to different extents depending on the energy spectrum of the wavelet. Wavelets take the form:
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