US President Donald Trump Announces Credit Card Rate Cuts, How Does it Affect Crypto Investments?

TheNewsCrypto2026-01-10 tarihinde yayınlandı2026-01-10 tarihinde güncellendi

Özet

US President Donald Trump has announced a proposal to cap credit card interest rates at 10%, along with other measures like cutting home loan rates and removing taxes on car loans. While these announcements could potentially free up finances for crypto investments, they require congressional approval. The crypto market is currently experiencing volatility, with BTC and ETH seeing minor declines. Additionally, spot Bitcoin and Ether ETFs have recorded consecutive days of outflows. Investors are advised to conduct thorough research before making any crypto investments.

US President Donald Trump has announced rate cuts on credit cards, bringing them down significantly for citizens. This in addition to cutting home loan rates and removing tax on American car loans. These are expected to collectively influence crypto investments – thereby impacting crypto prices.

Announcements by US President Donald Trump

US President Donald Trump has made several announcements; however, three of them have drawn a lot of attention in the context of crypto investments. The most recent announcement pertains to capping the interest rate on credit cards. Trump has said that credit card rates will be capped to 10% for one year starting from January 20, 2026, bringing them down from 20-30%.

However, a fact check on X by its AI tool, Grok, has highlighted that this could be a proposal or call for action. This is based on the principle that capping credit card interest rates requires congressional legislation. Interestingly, the announcement comes days after Trump tabled his plan to lower housing costs for Americans and implement no tax on American cars.

What Happens to Crypto Investments?

Global crypto markets are holding volatility with a dip of 0.84% in the market cap. This is mainly in consideration of a delay in the court’s verdict on tariffs and the announcement of the unemployment rate. The possibility of capping credit card rates, along with other announcements, does open the possibility to save finances and divert them to the crypto market. The Federal Reserve cutting rate at the January 27-28 meeting could further facilitate allocation to the segment.

For now, the likes of BTC and ETH are down by 0.36% and 0.77% over the last 24 hours, respectively. Bitcoin tokens are trading at $90,529.63, and Ether is exchanging hands at $3,087.63 when the article is being written. It is recommended to do thorough research and risk assessment before crypto investments.

ETFs’ Performance

Spot Bitcoin ETF and Spot Ether ETF noted significant outflows on January 09, 2026 – making it the 4th consecutive time for BTC ETF and the 3rd consecutive day for ETH ETF. Outward movement was $250 million for Spot Bitcoin ETF and $93.8 million for Spot Ether ETF.

Their respective historical cumulative inflows now stand at $56.38 billion and $12.45 billion. Suffice to say, volatility is impacting their ETF products in the market as well.

Highlighted Crypto News Today:

Momentum Tension for PUMP: Break Toward $0.0030 or Another Fade Lower?

Tagscrypto investments.TRUMP

İlgili Sorular

QWhat specific announcements did US President Donald Trump make regarding credit card rates and other financial measures?

AUS President Donald Trump announced a cap on credit card interest rates at 10% for one year starting from January 20, 2026, down from 20-30%. He also announced cuts to home loan rates and the removal of tax on American car loans.

QAccording to the article, how might Trump's announcements potentially affect crypto investments?

AThe announcements could lead to individuals saving money on credit card interest, home loans, and car loans, which might then be diverted into the crypto market. A potential Federal Reserve rate cut could further facilitate allocation to crypto investments.

QWhat was the performance of Bitcoin and Ethereum at the time the article was written?

AAt the time the article was written, Bitcoin (BTC) was down 0.36% trading at $90,529.63, and Ethereum (ETH) was down 0.77% trading at $3,087.63 over the last 24 hours.

QWhat was the trend in Spot Bitcoin and Spot Ether ETF flows on January 09, 2026?

AOn January 09, 2026, Spot Bitcoin ETFs saw outflows of $250 million (the 4th consecutive day of outflows), and Spot Ether ETFs saw outflows of $93.8 million (the 3rd consecutive day of outflows).

QWhat important point did the fact check by Grok on X highlight about Trump's credit card rate cap announcement?

AThe fact check by Grok on X highlighted that capping credit card interest rates requires congressional legislation, suggesting that Trump's announcement could be a proposal or a call for action rather than an immediate, executable policy.

İlgili Okumalar

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

AI is reshaping the labor market's value proposition. The traditional four-year college degree is losing its appeal as a guaranteed career path, while skilled blue-collar trades like electricians, welders, and plumbers are experiencing historic demand and wage premiums. This shift is driven by dual pressures: AI's displacement of certain white-collar roles and a booming need for physical infrastructure and data center construction. Data confirms the trend. In the U.S., vocational school revenue surged, and a significant portion of recent layoffs are AI-related. Surveys show a majority of Gen Z adults plan to pursue blue-collar work, citing better job security against AI automation. Vocational education interest has exploded recently. Experts cite a psychological shift as younger generations seek tangible, AI-resistant careers and avoid high student debt. In many cases, salaries for skilled trades now match or exceed those requiring a bachelor's degree. In South Korea, semiconductor vocational high schools boast near-total employment, with graduates securing high-paying roles at companies like Samsung. The shortage is structural, exacerbated by a retiring baby boomer workforce and massive infrastructure projects. Companies like JPMorgan Chase, Meta, and Lowe's are investing heavily in training programs. However, overcoming historical stigma and a "perception gap" around trade careers remains a key challenge to closing the talent gap.

marsbit1 saat önce

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

marsbit1 saat önce

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbit1 saat önce

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbit1 saat önce

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbit1 saat önce

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

marsbit1 saat önce

İşlemler

Spot
活动图片