Crypto jumps on U.S. CPI data as Trump urges Powell to cut interest rates

ambcryptoPublished on 2026-01-13Last updated on 2026-01-13

Abstract

The latest U.S. CPI data showed annual inflation steady at 2.7% in December, reinforcing expectations that the Federal Reserve may cut interest rates later in 2026. Core CPI rose 2.6% year-over-year, indicating persistent but stable underlying inflation. Shelter costs remained a key driver, rising 0.4% monthly. Following the report, the crypto market added roughly $27 billion, with Bitcoin climbing above $91,000. Former President Trump urged the Fed to cut rates, citing strong economic conditions. Stable inflation near the Fed’s target supports the case for eventual monetary easing, improving liquidity and benefiting risk assets like cryptocurrencies.

The cryptocurrency market added more than $26 billion in value on 13 January after the latest U.S. inflation data reinforced expectations that the Federal Reserve could begin cutting interest rates later this year.

The Bureau of Labor Statistics [BLS] reported on Tuesday that the Consumer Price Index [CPI] rose 0.3% in December. At the same time, annual inflation held steady at 2.7%, remaining close to the Federal Reserve’s long-term target.

The data showed that while inflation is no longer falling rapidly, price pressures have stabilised at levels that could allow policymakers to shift toward easing if economic growth slows.

Core CPI, which excludes food and energy, increased 0.2% month-over-month and 2.6% year-over-year. The move confirms that underlying inflation remains sticky but is no longer accelerating.

Shelter and services keep inflation elevated

The BLS said shelter costs rose 0.4% in December, remaining the single largest contributor to monthly inflation. Housing-related prices are still rising faster than most other categories, with shelter up 3.2% over the past year.

Services inflation also continued to outpace goods. The trend reflects ongoing wage and rent pressures in the U.S. economy, a key reason the Federal Reserve has been cautious about cutting rates too quickly.

Energy prices rise as gasoline falls in new CPI report

Energy prices were not the source of the latest inflation relief. The CPI report showed that the energy index rose 0.3% in December, as higher prices for electricity and energy services offset falling fuel costs.

Gasoline prices declined for the month, but that drop was insufficient to pull overall energy prices into deflation. This means inflation remains structurally supported by services and housing rather than being driven down by falling fuel prices.

Trump pushes Fed to cut rates post CPI report

The CPI release quickly sparked political reaction. President Donald Trump took to social media shortly after the data was published. He argued that the Federal Reserve should lower interest rates.

“Great (LOW!) Inflation numbers for the USA. That means that Jerome ‘Too Late’ Powell should cut interest rates, MEANINGFULLY!!!” Trump wrote, adding that economic growth remained strong alongside stable inflation.

While the Federal Reserve operates independently of political pressure, inflation running near 2.7% strengthens the case for eventual rate cuts if economic momentum cools.

Crypto market reacts to policy shift expectations

The crypto market responded positively to the inflation data. The total cryptocurrency market capitalization rose to around $3.12 trillion, up roughly $27 billion on the day, according to TradingView.

Bitcoin climbed back above $91,000, while Ethereum and major altcoins also advanced as investors increased exposure to risk assets.

Technically, the broader crypto market showed improving momentum following the CPI release. On the 12-hour chart, total market capitalisation pushed above short-term resistance, with MACD turning positive — a sign that upside momentum may be rebuilding.

Why CPI matters for Bitcoin

As institutional participation has grown through ETFs, derivatives, and macro-linked trading strategies, Bitcoin has become increasingly sensitive to U.S. inflation data.

Stable inflation near the Fed’s target allows:

  • Bond yields to ease
  • Liquidity conditions to loosen
  • Risk assets to attract capital

With the headline CPI holding at 2.7% and core inflation at 2.6%, markets are increasingly pricing in the possibility of a Federal Reserve pivot later in 2026. This backdrop has historically supported Bitcoin and other digital assets.

If inflation remains contained while growth slows, monetary policy may soon shift from restraint to stimulus, potentially providing a powerful tailwind for crypto markets.


Final Thoughts

  • U.S. inflation remained stable at 2.7%, increasing expectations that the Federal Reserve may begin cutting interest rates later in 2026.
  • Lower inflation reduces the need for tight monetary policy, improving liquidity conditions and making risk assets like Bitcoin more attractive.

Related Reads

Former CFTC Chairman, Circle President Tarbert: Preaching Long-Termism While Cashing Out $30 Million Himself

Former CFTC Chairman and Circle President Heath Tarbert has consistently advocated for a long-term vision in public, urging patience from investors as Circle’s stock price has fallen significantly from its peak. However, it has been revealed that since Circle’s IPO, Tarbert has continuously sold his CRCL shares through pre-arranged trading plans, cashing out approximately $30 million, without making any public market purchases. This contrast between his public messaging and personal actions has drawn criticism. Tarbert joined Circle in July 2023 as Chief Legal Officer, leveraging his regulatory experience to help guide the company through its IPO and expansion. Despite promoting stablecoins as long-term infrastructure, he established a 10b5-1 trading plan just before Circle went public, leading to substantial stock sales over the following year. In March 2026, he initiated another plan to sell more shares. His career trajectory highlights a pattern of moving between high-level regulatory roles and influential positions in the financial sector. After resigning as CFTC Chairman in early 2021, he joined Citadel Securities as Chief Legal Officer just 27 days later, during a period of intense regulatory scrutiny for the firm. He later joined Circle, aiding its efforts to navigate regulatory challenges for its public listing. While Tarbert's expertise in policy and compliance is valuable to companies like Circle, his actions—advocating long-term confidence while personally divesting—raise questions about the alignment between his public statements and his private financial decisions, leaving investors who followed his advice to bear the market risks.

marsbit5m ago

Former CFTC Chairman, Circle President Tarbert: Preaching Long-Termism While Cashing Out $30 Million Himself

marsbit5m ago

Gate Research Institute: The 'Wall Street-ization' Wave of Crypto Financial Products – Competition or Integration?

The article titled "Gate Research Institute: Are Crypto Financial Products Sparking a 'Wall Street' Wave—Competition or Convergence?" explores the evolving relationship between the crypto ecosystem and traditional finance (TradFi). The piece begins by reflecting on Bitcoin's original 2009 vision of decentralization, disintermediation, and moving away from banks. It then contrasts this with the 2024 landscape, where key crypto assets like Bitcoin are increasingly held through Wall Street products like ETFs issued by giants like BlackRock. The article questions whether this signifies that TradFi is systematically taking over the rights to issue, price, custody, and distribute crypto financial assets. The core argument is that this is not a zero-sum takeover but rather a bidirectional convergence where each side addresses the other's weaknesses. Crypto offers 24/7 global markets, programmable settlement, and open access but lacks compliant channels, institutional-grade custody, deep fiat liquidity, and mainstream distribution. TradFi possesses these but is constrained by legacy systems, limited operating hours, and slow settlement. Two primary convergence paths are highlighted: * **Path A (CEX to TradFi):** Exemplified by Gate, which has progressed from offering tokenized stocks and CFDs to providing direct, real stock trading (US, Hong Kong, South Korea) within its platform, using USDT. * **Path B (TradFi to Crypto):** Exemplified by Robinhood, which has integrated crypto trading, acquired exchanges like Bitstamp, and is moving traditional assets like stocks onto the blockchain via tokenization and its own Layer 2. Both paths are ultimately competing to become the next-generation, unified financial account—a "super account" where users can seamlessly trade cryptocurrencies, stocks, ETFs, RWA (Real World Assets), and tokenized treasury products in one interface. The growth of RWA and tokenized treasuries (e.g., BlackRock's BUIDL) is presented as the asset-layer fusion, providing stable, yield-bearing assets on-chain and acting as a bridge between the two worlds. In conclusion, the "Wall Street-ization" of crypto is framed as a mutual transformation. Decentralized ideals persist in the protocol layer, while at the application layer, a more efficient, global, and accessible unified capital market is emerging from this convergence. The future competition lies not between crypto exchanges and stockbrokers, but between platforms vying to offer the most comprehensive asset coverage, liquidity, and user experience within a single account.

marsbit10m ago

Gate Research Institute: The 'Wall Street-ization' Wave of Crypto Financial Products – Competition or Integration?

marsbit10m ago

Claude's Major New Feature: Screen Recording + Voice, Distilling Your Skills into AI Tasks in One Click

Claude has introduced a major new feature called "Record a Skill," available for Pro, Max, and Team users. This function, found in the Claude desktop app's CoWork menu, allows users to create reusable AI skills simply by recording their screen and providing voice narration while performing a task. Claude then automatically analyzes the recording and generates a functional Skill. A hands-on test confirmed the feature works seamlessly. Users start recording via the Skills manager, perform their workflow while verbally explaining the steps and logic, and avoid including sensitive information. After recording, Claude processes the content and creates the Skill, which can be saved and later invoked with a slash command (/). This eliminates the need for manual adjustments or writing complex instruction files. The innovation goes beyond mere efficiency. Previously, creating a Skill required writing a detailed SKILL.md file in Markdown—a significant barrier for non-technical users. "Record a Skill" bypasses this by directly capturing both actions and the implicit reasoning shared in the narration. This lowers the barrier to knowledge transfer and automation, addressing a core challenge in corporate knowledge management: the difficulty of getting experts to write and maintain documentation. However, the feature also highlights a shift in the nature of work. A case study from March 2026 showed a freelancer whose five-year client relationship was effectively replaced by a hand-coded Claude Skill automating their content workflow. With the even lower barrier of screen recording, the ability to distill personal expertise into automatable skills accelerates this trend. The "moat" for work is moving from simply knowing how to do a task to mastering tasks that are difficult or impossible to automate.

marsbit14m ago

Claude's Major New Feature: Screen Recording + Voice, Distilling Your Skills into AI Tasks in One Click

marsbit14m ago

Feeding AI "Noise" Can Also Boost Scores, This Work Enables Positive Transfer with Noise

Feeding "Noise" to AI Can Improve Performance: A Method Enables Positive Transfer from Noise This work, Semi-Supervised Noise Adaptation (SSNA), introduces a Noise Adaptation Framework (NAF) that challenges traditional transfer learning. Instead of requiring a labeled source domain of real data (e.g., images, text), NAF uses randomly generated Gaussian noise as the source. For a target task with C classes, it constructs C noise clusters by sampling from Gaussian distributions. Although this synthetic noise contains no semantic meaning, NAF trains it to form a discriminative class structure in a shared representation space—clustering same-class noise and separating different classes. The key is aligning this learned structure from the noise domain to the real, sparsely labeled target domain. A small number of target labels are still essential to establish the correspondence between noise clusters and actual classes. The training objective combines: 1) supervised loss on the few labeled target samples, 2) classification loss for the noise to build its structure, and 3) a distribution alignment loss (using Negative Domain Similarity) to minimize the gap between the noise and target domains in the shared space. Experiments show significant gains in few-label settings. With just 4 labels per class, NAF with a ResNet-18 backbone improves accuracy over a standard supervised baseline (ERM) by +12.35% on CIFAR-10, +7.61% on CIFAR-100, +4.38% on DTD-47, and +2.74% on Caltech-101. It also benefits fine-grained datasets and scales to ImageNet-1K (with 100 labels/class) and text classification (AG News). NAF can be integrated into existing semi-supervised methods like FixMatch for further gains. Ablation studies confirm the transferred benefit comes from the discriminative structure of the noise, not randomness itself. Collapsing all noise into a single point causes negative transfer, while increasing separation between noise cluster centers improves performance. The amount of noise per class is less critical once a basic structure forms. In conclusion, this work demonstrates that for positive transfer, the semantic content of source data may not be necessary. What can be effectively transferred is the *organizational structure* of categories within a representation space. This offers a promising alternative for scenarios where real source data is unavailable due to privacy, copyright, or procurement constraints.

marsbit15m ago

Feeding AI "Noise" Can Also Boost Scores, This Work Enables Positive Transfer with Noise

marsbit15m ago

Trading

Spot
活动图片