A combined ETF of bitcoin and Ethereum was approved.
The investment fund managed by Bitwise received approval from the U.S. Securities and Exchange Commission (SEC). The U.S. Securities and Exchange Commission (SEC) has expedited the launch of a new spot cryptocurrency exchange-traded fund (ETF). This is one proposed by Bitwise, which invests directly in bitcoin (BTC) and ether (ETH). The approval occurred yesterday, 45 days after Bitwise submitted the ETF proposal to the SEC, a shorter time than the agency usually takes to give the green light. In fact, this was the first deadline of the four that the agency has to issue a verdict.
Misinterpretation of that newspaper; it mentioned on its account X that it will discontinue the Chivo wallet; it will no longer be mandatory to make payments with BTC, but it will still remain legal.
ElReyCripto
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Bearish
I will only tell you what I already know, and many believe it will go to 150k or 300k 🤣
Well, I am glad to know this news because $BTC will bleed out this year 🩸
And many of those who are investing in #BTC will end up sucking it up deliciously 🤣🤣
Pay attention! The last peak that bitcoin made a few days ago.. is a liquidity warning to everyone that this is the tip of the iceberg 🧊
So buckle up because this roller coaster is going down hard 🔻
#El Salvador reforms its Bitcoin law to comply with the IMF agreement.
The Salvadoran Parliament approves a key reform to the Bitcoin Law. Businesses are no longer required to accept BTC as a form of payment. The amendment was approved with 55 votes in favor and 2 against. The Parliament of El Salvador approved a project by Nayib Bukele to modify the Bitcoin Law and adapt it to the $1.4 billion agreement with the International Monetary Fund (IMF). The information was published by several international media. The reform, approved with 55 votes in favor and only 2 against, comes from a Congress dominated by Bukele's Nuevas Ideas party. With this change, businesses will no longer be required to accept BTC as a means of payment, but its use will be completely voluntary.
#The interest rate in the U.S. has been set; bitcoin reacts with volatility.
The U.S. Federal Reserve (Fed) made its monthly update on interest rates.
It has been determined that there will be no changes in the rates, at least for the next month. They remain at 4.50% annually.
Apparently, many investors and traders were hoping for a surprising cut in the interest rate (perhaps they believed that with Donald Trump at the helm of the Executive Power, there would be changes in the Fed's policies), and they were disappointed when it did not happen.
Half an hour after the interest rate decision was announced, Fed Chairman Jerome Powell held a press conference.
Furthermore, he clarified that "as the economy evolves, they will adjust monetary policy considering the employment situation." Powell stated: "If the labor market weakens more than expected, we could move more quickly in lowering interest rates." Finally, the Fed Chairman emphasized that reaching an inflation rate of 2% annually remains the goal.
In any case, bitcoin does not yet show a clear bullish or bearish trend. Probably in the next few hours, the ambivalent volatility will decrease and the market will define a direction. #Fed
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#Now the competition to surpass DeepSeek is also taking place in China itself: Alibaba has just announced Qwen2.5-Max
Dizzying days in the world of artificial intelligence (AI). When it seemed that American tech giants had no rivals capable of overshadowing them, DeepSeek caused a genuine earthquake. The excellent performance of the latest language models from the Chinese company translated into a direct threat to Silicon Valley firms, which lost billions of dollars in market value within hours.
Alibaba, in the race to surpass DeepSeek Things are moving very quickly in the field of AI. Alibaba, the e-commerce giant known as "the Chinese Amazon," has just launched its most advanced language model: Qwen2.5-Max. We are looking at a pre-trained alternative with 20 trillion tokens and improved through supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF).