Gold breaks KEY support with 3.7% drop – Will crypto face pressure next?

ambcryptoPublicado a 2026-03-21Actualizado a 2026-03-21

Resumen

The latest inflation report, with February's hotter-than-expected PPI, triggered a 3.7% drop in gold, breaking key support. This sell-off is attributed to a stronger U.S. dollar and rising Treasury yields, making traditional safe havens more attractive. Historically, a stronger DXY negatively impacts risk assets like crypto. Bitcoin is currently stagnant near $70k with negative funding rates and declining capital inflows, indicating a bearish bias. The falling Coinbase Premium Index and increased short positions suggest a crypto downturn may already be priced in, especially given macro pressures and the historical inverse correlation between DXY and BTC.

The latest inflation report has clearly shaken things up in this market cycle.

To put it in context, February’s PPI, released on the 18th of March, came in hotter than expected, signaling that U.S. inflation is still sticky. The reaction was almost instant. Gold, for instance, dropped 3.74%, slicing through the $5k support level, a move that caught many traders off guard.

The logic here is straightforward: Historically, during times of geopolitical instability, investors flocked to gold as a hedge against inflation. But what’s interesting now is that this pattern seems to be shifting. So far, this move hasn’t spilled over into crypto, though that doesn’t mean a crash is off the table.

To see why, you need to look at a couple of key things.

First, the gold sell-off is tied to the U.S. dollar getting stronger. With the Fed keeping interest rates steady and U.S. debt now over $39 trillion, Treasury yields are starting to look a lot more attractive. In fact, yields have jumped nearly 10% since the war kicked off, which is clearly pulling attention away from gold.

On the crypto side, history tells a familiar story. A stronger DXY usually means less love for risk assets. That means when geopolitical tensions rise, risk assets start to feel less appealing. Meanwhile, a stronger dollar pulls capital into bonds, which feel safer and now offer higher returns thanks to rising yields.

In this context, the falling Coinbase Premium Index (CPI) is already hinting at this shift, showing why crypto could eventually follow gold’s lead.

Rising Bitcoin shorts: Is a crypto crash already priced in?

Crowded trades during volatile markets can be a double-edged sword.

Currently, crypto is stuck chopping in a tight range, with Bitcoin [BTC] hovering around the $70k mark and no big capital inflows in sight. Naturally, liquidity clusters are stacking up at different price levels, hinting that traders are gearing up for a potential move.

Backing this up, Glassnode data shows perpetual funding is still firmly negative, confirming the bearish bias in directional premium. Put simply, even though BTC has bounced off the lows, traders are still leaning short, which keeps the market primed for a potential squeeze-driven upside.

But here’s where it gets interesting: The recent gold sell-off adds a twist, showing just how exposed the crypto market still is. With rising yields pulling capital back into traditional safe havens, and the Federal Reserve brushing off any talk of interest rate cuts, crypto traders are left navigating a tricky setup.

In this context, the rising Bitcoin shorts don’t feel like a fluke.

Instead, they’re looking more like strategic positioning. With the Coinbase Premium Index falling, limited capital inflows, BTC stuck near resistance, and a shifting macro backdrop, everything points to a bearish bias in both technicals and fundamentals. Bottom line? A crypto crash already looks priced in, and with the historical DXY-BTC correlation, it wouldn’t be surprising if history repeats itself.

Final Summary

Rising yields and a firmer DXY are pulling capital into safe havens, shaking confidence in gold.
With Bitcoin near resistance, falling CPI, and bearish technicals, a crypto crash may already be priced in.

Preguntas relacionadas

QWhat was the immediate market reaction to the hotter-than-expected February PPI report released on March 18th?

AThe reaction was almost instant. Gold, for instance, dropped 3.74%, slicing through the $5k support level.

QAccording to the article, what two key factors are pulling attention and capital away from gold?

AThe gold sell-off is tied to the U.S. dollar getting stronger (a firmer DXY) and rising Treasury yields, which have jumped nearly 10% and are now more attractive.

QWhat does the falling Coinbase Premium Index (CPI) signal for the crypto market?

AThe falling Coinbase Premium Index is hinting at a shift, showing that crypto could eventually follow gold's lead downward as capital moves away from risk assets.

QWhat does the negative perpetual funding rate and bearish bias in directional premium indicate about trader sentiment?

AIt confirms a bearish bias, indicating that even though BTC has bounced off lows, traders are still leaning short and positioning for a potential downside move.

QWhy does the article suggest that a crypto crash may already be 'priced in'?

ABecause of the rising Bitcoin shorts, falling CPI, limited capital inflows, BTC being stuck near resistance, and a shifting macro backdrop with a stronger dollar and rising yields, all of which point to a bearish bias.

Lecturas Relacionadas

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbitHace 5 min(s)

marsbitHace 5 min(s)

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

In 2026, a historic shift occurred in AI as major cloud providers' inference spending surpassed training spending for the first time, signaling a move from "building large models" to "using large models." This shifts the core challenge from computing power to the "memory wall"—the bottleneck of data movement (model weights, activations, KV Cache) between external DRAM and processors, where energy and latency from data transfer far exceed computation itself. Companies like Nvidia face GPU idle time due to bandwidth limits. In contrast, Cerebras Systems adopts a radical "wafer-scale" approach with its Wafer-Scale Engine (WSE). Instead of cutting a silicon wafer into many chips, Cerebras uses almost the entire wafer as one massive chip (WSE-3). This design provides 44GB of on-chip SRAM, delivering memory bandwidth thousands of times higher than traditional HBM (e.g., 21 PB/s vs. Nvidia B200). For LLM inference, weights are streamed layer-by-layer from external MemoryX storage to the chip, avoiding HBM bottlenecks. This results in token generation speeds 1.5–5 times faster than Nvidia's B200 in some models and significant advantages in first-token latency and long-context tasks. Additionally, Cerebras's architecture offers much lower interconnect power consumption (0.15 pJ/bit vs. GPU's ~10 pJ/bit). However, Cerebras faces challenges: SRAM scaling has slowed with advanced nodes, limiting future capacity gains; the chip requires specialized liquid cooling and custom software stacks; and its external I/O bandwidth (150 GB/s) is low compared to NVLink, hindering multi-system scaling for very large models. Competition is intensifying. Major players are pursuing three paths: 1) Developing proprietary inference ASICs (e.g., Google TPU, Microsoft Maia), 2) Leveraging advanced packaging (e.g., TSMC's SoW) to democratize wafer-scale-like integration, potentially eroding Cerebras's process advantage within a few years, and 3) Exploring optical interconnects for ultimate bandwidth. Commercially, Cerebras is transitioning from a hardware vendor to a service provider, facing the immense challenge of building high-power, specialized data centers to meet large contracts (e.g., 250MW/year from 2026–2028). In conclusion, the AI inference era presents a fundamental architectural trade-off. Cerebras opts for extreme physical optimization for low-latency, single-task performance, while Nvidia prioritizes versatility and massive cluster throughput. The path forward remains uncertain, with technology and business models still evolving in the race toward advanced AI.

marsbitHace 11 min(s)

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

marsbitHace 11 min(s)

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

**Title: Has Bitcoin's Rebound Ended, Entering the Late Bear Market Phase?** **Summary:** Bitcoin's price has declined by 13% this week, signaling a potential return to late-stage bear market conditions. The price fell to around $67k, positioned between the Realized Price and Realized Cap Weighted Average. For the first time since early 2022, the Short-Term Holder cost basis has dropped below this key average, confirming a hallmark of late-cycle bear markets. Profitability metrics have collapsed sharply. The 7-day average of the Realized Profit/Loss ratio plummeted from a local high of 3.16 to 0.29, mirroring the February panic sell-off. Critically, the 90-day average never breached the threshold of 2, indicating the recent rally to $82k was a bear market bounce, not a structural shift. Realized losses surged to $1.35 billion daily, with $770 million coming from Long-Term Holders selling at a loss. This accelerating redistribution of supply from weak to strong hands is a necessary but ongoing process for a market bottom. The rally stalled almost precisely at the aggregate cost basis (~$83k) of US spot Bitcoin ETF investors, turning that level into strong resistance and leaving the average ETF holder underwater again. Spot market flows have turned decisively negative, showing sellers are dominating order books despite the price drop. While a significant futures long liquidation event cleared over $400 million in leverage, providing a potential reset, sustained spot demand is yet to materialize. Options markets continue to price in higher future volatility (Implied Volatility) than recent price action (Realized Volatility) has shown, with a persistent skew towards put options, indicating ongoing demand for downside protection. In conclusion, multiple metrics point to a fragile market structure. Resistance at the ETF cost basis, accelerating realized losses, dominant spot selling, and cautious options pricing all suggest the bear market trend persists. A sustainable recovery likely requires a resurgence of spot demand, ETF holders returning to profit, and a clear reduction in selling pressure.

marsbitHace 11 min(s)

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

marsbitHace 11 min(s)

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

In today's TechFlow Intelligence Briefing, several major tech stories highlight a growing theme of trust and credibility gaps across AI, crypto, and finance. AI company Anthropic has publicly called for a global pause in AI development, citing risks from Claude's "recursive self-improvement." Ironically, this coincides with reports the company is preparing for a massive IPO targeting a near $1 trillion valuation. This perceived hypocrisy, coupled with widespread user complaints about Claude's declining performance, is sparking debate over whether the safety warning is genuine or a competitive tactic. Meanwhile, in a substantive security move, Anthropic open-sourced a framework for AI-powered vulnerability discovery. In the crypto market, Bitcoin's price drop below $61,000 triggered over $1.16 billion in liquidations, flipping the market into a state where more BTC is held at a loss than at a profit, a historical bearish signal. On the corporate front, SpaceX's highly anticipated IPO is generating immense Wall Street excitement, with Goldman Sachs projecting 100x revenue growth by 2030. However, the S&P 500 has refused to fast-track the company's inclusion post-IPO, potentially limiting immediate institutional demand. Separately, ByteDance's AI app Doubao lost over 6 million monthly active users after introducing a subscription model, highlighting the challenges of AI monetization. Other notable developments include Nvidia certifying HBM4 memory from Samsung, SK Hynix, and Micron; Cloudflare's acquisition of front-end tooling company VoidZero; and its CEO warning that bot traffic now exceeds human traffic online. The underlying narrative connects these events: a trust crisis. From AI firms' contradictory actions and crypto volatility to the clash between SpaceX's hyped narrative and institutional rules, a pattern is emerging where stated intentions and actual practices are increasingly misaligned.

marsbitHace 26 min(s)

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

marsbitHace 26 min(s)

Dalio Warns: AI Boom Shows Signs of a Bubble, Day of Reckoning Will Be the Time of Burst

Ray Dalio, founder of Bridgewater Associates, warns that the current artificial intelligence investment boom shows classic signs of a bubble, which he expects will eventually burst. In a Bloomberg Television interview, he noted that great technological revolutions often lead to capital inflows that create bubbles, making it difficult for investors and companies to calibrate their spending accurately—either overspending to capture market share or underspending and losing their competitive position. This caution comes amid significant rallies in AI-related assets, particularly chipmakers, driven by soaring demand for data centers and high-bandwidth chips, raising debates about overheating valuations. In contrast, Nvidia CEO Jensen Huang recently asserted that investors embracing the AI wave would see "crazy" returns and dismissed concerns over return on investment for data center spending as outdated. Dalio, however, focuses on the risks in the profit realization phase. He argues that bubbles tend to show signs of破裂 when markets transition from investment to the need for tangible returns, describing the burst as a process of converting paper wealth into cash. While acknowledging AI's intrinsic value, he expressed concern over the future profitability of some AI companies, suggesting the market is repeating a familiar pattern. The 76-year-old billionaire, who fully exited Bridgewater in 2025, has a net worth estimated at $21.5 billion according to the Bloomberg Billionaires Index.

marsbitHace 1 hora(s)

Dalio Warns: AI Boom Shows Signs of a Bubble, Day of Reckoning Will Be the Time of Burst

marsbitHace 1 hora(s)

Trading

Spot

Futuros