Is Donald Trump’s ‘15% growth’ forecast enough to save crypto in 2026?

ambcryptoPublished on 2026-02-11Last updated on 2026-02-11

So far in 2026, the crypto market has surprised many by rallying against expectations. What analysts had pegged as a year defined by regulatory clarity and a fundamental growth cycle has already started to shift.

After back-to-back red weekly sessions, most high-cap risk assets have retraced to pre-election levels, showing that confidence in the U.S. President Donald Trump’s pro-crypto stance is fading as investors face big losses.

Against this backdrop, Trump’s projection of 15% annual growth for 2026, ahead of Kevin Warsh’s Federal Reserve nomination, has split the market. The question now: Will this projection move the market, or is it just hype?

Crypto market on edge as 15% projection divides analysts

Market divergence is clear in how investors are reacting to the President.

A few months ago, even a single pro-crypto headline from President Trump could easily trigger a rally. This time, however, despite his bullish 15% growth projection, the total crypto market is still down 1.44% intraday.

For context, in a recent media interview, President Trump forecasted 15% annual U.S. economic growth. The key takeaway? His projection hinges on his Federal Reserve nominee, whom he sees as supportive of rate cuts.

The market reaction is split. Some analysts view this as a bullish signal for the Q4 crypto market cycle, seeing potential rate cuts as a boost ahead of the midterm elections and a base case for risk assets to finish 2026 strong.

Others are skeptical, noting that given current macro conditions, inflation could undermine the rate-cut thesis, making the 15% projection look “overly optimistic.” In short, a straight-line crypto rally is far from certain.

Naturally, the key question now: Will real data outpace the “hype” around President Trump’s Federal Reserve move, further shaking confidence in his pro-crypto stance and leaving the crypto market to close 2026 in the red?

Trump’s rate-cut optimism faces crypto reality

Bloomberg is drawing a sharp line between optimism and reality.

In a recent report, it pointed out that the U.S. debt-to-GDP ratio, at 120%, mirrors the post-World War II era, when the Federal Reserve bought back Treasuries to control yields, followed by a 20% rate hike to tackle inflation.

Against this backdrop, analysts view President Trump’s nomination of a new Fed Chair as largely inconsequential for markets. In short, the hard data runs counter to expectations of a bullish crypto market in 2026.

From late 2025 into 2026, the crypto market has shown what happens when expectations are missed. Massive green wicks (over $1 billion in daily long liquidations) have slammed the market, rattling investor confidence.

The result? Nearly $1 trillion wiped out in just a month, pushing risk assets back to pre-election levels as the market strayed from expectations of a bullish Q1 driven by regulatory clarity and following 2025’s 7% market dip.

According to AMBCrypto, this highlights why the debate around President Trump’s 15% growth projection matters. With data clearly working against this move, the crypto market now risks another wave of liquidations.

In turn, this puts the market’s 2026 rally on a more bearish footing.


Final Thoughts

  • President Trump’s 15% growth projection splits the crypto market as some see it as bullish for Q4, while others call it overly optimistic.
  • The crypto market faces downside risks, as data and liquidation pressure put the 2026 crypto rally on shaky footing.

Related Reads

STRC Loses Peg by 11%, Can Strategy's Perpetual Motion Machine Keep Running?

The article discusses the significant and concerning depegging of MicroStrategy's (MSTR) preferred stock, STRC. Designed to trade near its $100 target par value, STRC has recently fallen sharply, reaching a low of $83.26 and closing at $88.59, representing an over 11% discount. STRC is a core component of MicroStrategy's financial strategy. As a perpetual preferred stock, it allows the company to raise capital through an "at-the-market" (ATM) issuance program without diluting common shareholders (MSTR). This capital is primarily used to purchase Bitcoin, creating a "capital flywheel": issuing STRC → raising cash → buying BTC → increasing net assets → supporting STRC's value. The flywheel's operation depends on STRC maintaining its $100 price. To enforce this, MicroStrategy employs a dynamic dividend mechanism, recently raising the rate to 11.5% and increasing payout frequency. However, this has failed to halt the depegging, indicating market concerns extend beyond yield. Analysts cite two main reasons. First, technical factors like forced liquidations from leveraged arbitrage trades may have exacerbated the sell-off. Second, and more fundamentally, is waning confidence in MicroStrategy's financial resilience. A JPMorgan report highlighted the company's limited cash relative to its ~$1.7 billion annual dividend obligation, raising liquidity concerns. While MicroStrategy counters that its massive Bitcoin holdings provide decades of coverage, this argument relies on the potential need to sell BTC—a departure from its long-standing "never sell" narrative. The company's recent sale of a small amount of Bitcoin for "testing," despite being framed as minor, has intensified these fears. The persistent depegging threatens to cripple MicroStrategy's primary funding channel. If STRC remains discounted, the company's ability to fund further Bitcoin purchases weakens. Should cash reserves dwindle while financing is constrained, the market may increasingly price in the risk of MicroStrategy becoming a forced seller of Bitcoin to meet obligations. This shift from a major marginal buyer to a potential seller could pose significant downside risk to the broader Bitcoin market.

链捕手8m ago

STRC Loses Peg by 11%, Can Strategy's Perpetual Motion Machine Keep Running?

链捕手8m ago

Behind the AI Scorecards Lies a Chinese 'Question Setter'

Behind the AI scorecards that dominate industry discussions—benchmarks like MMLU-Pro, MMMU, and MMMU-Pro—stands a Chinese-Canadian researcher: Wenhu Chen. As an assistant professor at the University of Waterloo and founder of the TIGER Lab, Chen has become a key "exam-setter" for evaluating large language and multimodal models. Chen first gained broader recognition with MMLU-Pro, a more challenging and stable update to the popular MMLU benchmark. As top models like OpenAI’s o3 began achieving near-perfect scores on the original MMLU, it became difficult to distinguish their true capabilities. MMLU-Pro introduced more complex reasoning questions, expanded answer choices, and filtered out ambiguous or simple items, effectively reintroducing differentiation among state-of-the-art models. His work on MMMU addressed the evaluation of multimodal models, requiring them to integrate visual information (like charts, diagrams, or tables) with textual knowledge across diverse academic subjects. Even the strongest models initially scored only around 56-59%, highlighting significant room for improvement in genuine multimodal reasoning. MMMU-Pro further refined this by preventing models from bypassing visual cues. Chen’s research focus has long been on complex information understanding and reasoning. His background—including a PhD at UC Santa Barbara, research at Google/DeepMind on Gemini, and now a role in Meta’s superintelligence lab—provides deep insight into model development and their potential weaknesses. His TIGER Lab also builds models (e.g., for video understanding and generation), ensuring his evaluation benchmarks are grounded in practical challenges. While AI headlines often spotlight company leaders and product launches, Chen’s work exemplifies the critical, behind-the-scenes contributions of researchers crafting the rigorous standards that define and drive progress in AI capabilities.

marsbit1h ago

Behind the AI Scorecards Lies a Chinese 'Question Setter'

marsbit1h ago

STRC Unpegged by 11%, Can Strategy's Perpetual Motion Machine Keep Turning?

STRC, the perpetual preferred stock of MicroStrategy, is experiencing a persistent de-pegging from its target par value of $100, with the discount recently widening to over 11%. This de-anchoring challenges the core design of STRC, which was intended as a stable, income-oriented security operating near $100. As a crucial funding engine for MicroStrategy's Bitcoin acquisition strategy, STRC's price reflects market confidence in the company's entire capital model. The company's "capital flywheel" relies on issuing STRC at or above $100 via an At-the-Market (ATM) program to raise cash for buying Bitcoin, thereby boosting company equity and theoretically supporting STRC's value. A monthly adjustable dividend mechanism was designed to maintain this peg. Despite raising the dividend to 11.5% and increasing payment frequency, the de-pegging persists. Market concerns extend beyond technical factors like leveraged arbitrage unwinding. Analysts point to MicroStrategy's limited cash reserves relative to its ~$1.7 billion annual dividend obligation for preferred shares. While the company counters that its vast Bitcoin holdings could cover decades of payments, this argument hinges on the potential need to sell Bitcoin—a shift from its longstanding "hodl" narrative. The company's recent sale of a small amount of BTC, framed as a test, amplified these liquidity and strategy concerns. If STRC remains discounted, impairing MicroStrategy's ability to raise cheap capital, fears may grow that the company could sell more Bitcoin to meet obligations. This scenario could transform MicroStrategy from a major market buyer into a potential seller, posing significant downside risk for Bitcoin. The re-pegging of STRC is thus a key indicator for the health of MicroStrategy's capital structure and its market impact.

Odaily星球日报1h ago

STRC Unpegged by 11%, Can Strategy's Perpetual Motion Machine Keep Turning?

Odaily星球日报1h ago

Silicon Valley's Most Sought-After New Role Has Emerged

Silicon Valley's New Most Wanted Job: The Rise of the Forward Deployment Engineer The AI industry is witnessing a significant shift. The focus has moved from developing cutting-edge models to deploying them effectively within enterprises. This has made the "Forward Deployment Engineer" (FDE) a critical and highly sought-after role at major firms like OpenAI, Anthropic, and Google. For the past three years, the industry prioritized model scientists. However, companies are now facing a harsh reality: purchasing powerful AI tools does not guarantee productivity gains or organizational change. The biggest hurdle is not the technology itself, but integrating it into complex legacy systems, workflows, and corporate cultures. This includes challenges like data silos, compliance requirements, and internal resistance. The FDE role, pioneered by Palantir Technologies, addresses this "last-mile" problem. FDEs are deployed on-site with clients for extended periods. Their job is to deeply understand the client's specific organizational structure, processes, and pain points, then tailor and implement the AI solution accordingly. They combine skills in technology, project management, and organizational change. A clear signal of this trend emerged in May 2026 when three AI giants made major moves. Anthropic launched a $1.5B joint venture for enterprise deployment. OpenAI formed an independent deployment subsidiary, DeployCo, with over $4B in commitments and acquired a deployment consultancy. Google Cloud's CEO publicly announced a large-scale recruitment drive for FDEs. This shift represents a fundamental change in the software business model: from selling tools to selling guaranteed outcomes. FDEs are the agents of this change, responsible for delivering a working system within the production environment, not just a demo. Real-world cases, such as challenges at Goldman Sachs (compliance barriers) and Target (internal cultural resistance), illustrate that the primary obstacles to AI adoption are organizational, not technical. An FDE's value lies in navigating these human and procedural complexities to facilitate a successful "AI migration." In essence, as core AI technology becomes more accessible and affordable, the true premium is shifting to the human expertise required to understand organizations and drive change—making the FDE role pivotal for the next phase of the AI revolution.

marsbit1h ago

Silicon Valley's Most Sought-After New Role Has Emerged

marsbit1h ago

Trading

Spot
Futures
活动图片