Gold Plunged Over 4%, Silver Crashed 11%, Did the US Stock Market Plunge Trigger Algorithmic Selling in Precious Metals?

marsbitPublicado a 2026-02-13Actualizado a 2026-02-13

Resumen

Gold and silver prices plummeted sharply on Thursday, with gold dropping over 4% and silver plunging nearly 11%, amid a broader sell-off in metals triggered by a significant decline in U.S. equities. The Nasdaq fell more than 2%, prompting some traders to liquidate commodity positions—including gold, silver, copper, platinum, and palladium—to cover losses in equities and seek liquidity. A strong dollar and risk-off sentiment contributed to the decline. The sharp and sudden downturn was largely attributed to algorithmic and momentum-driven trading. After a period of sustained gains, metals faced heavy selling pressure as key technical levels were breached, leading to automated sell orders. Some analysts characterized the move as a "vacuum-style drop," typical of systematic trading strategies during periods of market stress. Despite the sell-off, many analysts remain bullish on gold’s longer-term prospects, citing ongoing geopolitical risks, questions around Federal Reserve policy, and a broader shift away from traditional assets. Major banks, including J.P. Morgan and Deutsche Bank, maintain positive year-end targets. Market participants are now closely watching upcoming U.S. economic data, particularly the CPI release, for clues on the Fed’s interest rate path, as lower rates generally support non-yielding assets like precious metals.

On Thursday, US stocks fell sharply, with the Nasdaq dropping over 2%. Some traders sold precious metals to cover losses in the stock market, leading to significant declines in gold, silver, copper, platinum, and palladium. The US Dollar Index saw a slight increase.

Amid renewed concerns over whether massive AI investments can truly be implemented on a large scale, US tech stocks declined. Metal prices suddenly dropped amid suspected algorithmic trading sell-offs, with some investors forced to exit commodity positions, including metals, for liquidity, while some funds shifted to US Treasuries for safety.

Spot gold once fell by 4.1%, while silver plummeted by 11%. Copper prices on the London Metal Exchange (LME) dropped by 2.9%. Metal prices later pared some of their losses:

At the close of New York trading on Thursday, spot gold fell 3.26% to $4,918.36 per ounce. Before 00:00 Beijing time, it maintained a slight decline, largely holding above $5,050, before experiencing a sharp plunge, hitting a daily low of $4,878.66. COMEX gold futures fell 3.06% to $4,942.50 per ounce.

At the close of New York trading on Thursday (February 12), spot silver fell 10.89% to $75.0942 per ounce. Before 00:00 Beijing time, it held steady above $82 with a slight decline, before a sharp drop below $76, hitting a daily low of $74.4456 near the close of US stocks. COMEX silver futures fell 10.56% to $75.050 per ounce.

Other important metals: COMEX copper futures fell 3.65% to $5.7740 per pound, spot platinum fell 6.19%, and spot palladium fell 5.89%.

What Do Analysts Say?

Regarding Thursday's gold and silver movements, industry insiders said: "This all happened too fast, it felt like a risk-off move. During periods of extreme market stress, even safe-haven assets like gold are sold by investors in urgent need of liquidity."

Part of the selling in gold and silver on Thursday also stemmed from profit-taking, as the previous rapid rally was partly driven by speculative buying.

Some industry insiders pointed out that for gold and silver, trading is still largely driven by sentiment and momentum. On days like this, they struggle.

Since 2024, gold and silver have surged strongly, with momentum-driven buying pushing metal prices to repeated new records. However, this trend halted abruptly on January 29, when gold recorded its largest single-day drop in over a decade, and silver saw its biggest decline on record. Since then, both metals have traded in a narrow range with increased volatility, lacking new catalysts.

Some analysts believe that Thursday's sudden drop in gold prices does not signal an imminent sustained downtrend. However, it does increase the likelihood of continued volatility in the short term. The market has cleared a significant chunk of lower liquidity, and the next move will depend on how prices perform near key technical levels.

Media analysis noted that despite a slight rebound, overall, metal prices were hit hard in a sudden vacuum-like decline, more akin to systematic strategy selling—such as momentum-driven de-risking operations common among CTA (Commodity Trading Advisor) groups when key levels are breached.

Despite recent sharp declines, many analysts still expect gold to resume its upward trend, believing the factors that drove the earlier rally remain—including geopolitical tensions, doubts about the Fed's independence, and a broader shift from traditional assets like currencies and sovereign bonds to alternative assets. J.P. Morgan Private Bank expects gold to reach $6,000 to $6,300 per ounce by year-end, while Deutsche Bank and Goldman Sachs maintain bullish views.

The world's largest silver ETF, iShares Silver Trust, saw significant trading in May/June $125 strike call options, while investors sold contracts previously bought at high levels, which may have further intensified selling pressure on silver.

Traders are now focusing on US economic data, including the key CPI data to be released on Friday, for clues on the Fed's interest rate path. Lower borrowing costs typically benefit non-yielding precious metals.

Criptos en tendencia

Preguntas relacionadas

QWhat was the main reason for the sharp decline in precious metals like gold and silver according to the article?

AThe decline was primarily triggered by algorithmic trading sell-offs, as investors sold precious metals to cover losses in the stock market and obtain liquidity during a risk-off event.

QHow much did spot silver drop at its lowest point during the trading session?

ASpot silver plummeted by 10.89%, reaching a low of 74.4456 dollars per ounce.

QWhat broader market movement coincided with the sell-off in precious metals?

AThe sell-off coincided with a significant drop in U.S. tech stocks, with the Nasdaq falling over 2%, amid renewed worries about the large-scale implementation of AI investments.

QDespite the recent drop, what is the outlook for gold from major banks like J.P. Morgan according to the analysts in the article?

AAnalysts from J.P. Morgan Private Bank expect gold to reach $6,000 to $6,300 per ounce by the end of the year, maintaining a bullish outlook.

QWhat upcoming economic data are traders focusing on for clues about the Federal Reserve's policy?

ATraders are focusing on the upcoming U.S. CPI data to find clues about the Federal Reserve's future interest rate path.

Lecturas Relacionadas

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.

marsbitHace 42 min(s)

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

marsbitHace 42 min(s)

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.

marsbitHace 46 min(s)

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

marsbitHace 46 min(s)

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.

marsbitHace 46 min(s)

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

marsbitHace 46 min(s)

Trading

Spot

Artículos destacados

Cómo comprar 4

¡Bienvenido a HTX.com! Hemos hecho que comprar 4 (4) sea simple y conveniente. Sigue nuestra guía paso a paso para iniciar tu viaje de criptos.Paso 1: crea tu cuenta HTXUtiliza tu correo electrónico o número de teléfono para registrarte y obtener una cuenta gratuita en HTX. Experimenta un proceso de registro sin complicaciones y desbloquea todas las funciones.Obtener mi cuentaPaso 2: ve a Comprar cripto y elige tu método de pagoTarjeta de crédito/débito: usa tu Visa o Mastercard para comprar 4 (4) al instante.Saldo: utiliza fondos del saldo de tu cuenta HTX para tradear sin problemas.Terceros: hemos agregado métodos de pago populares como Google Pay y Apple Pay para mejorar la comodidad.P2P: tradear directamente con otros usuarios en HTX.Over-the-Counter (OTC): ofrecemos servicios personalizados y tipos de cambio competitivos para los traders.Paso 3: guarda tu 4 (4)Después de comprar tu 4 (4), guárdalo en tu cuenta HTX. Alternativamente, puedes enviarlo a otro lugar mediante transferencia blockchain o utilizarlo para tradear otras criptomonedas.Paso 4: tradear 4 (4)Tradear fácilmente con 4 (4) en HTX's mercado spot. Simplemente accede a tu cuenta, selecciona tu par de trading, ejecuta tus trades y monitorea en tiempo real. Ofrecemos una experiencia fácil de usar tanto para principiantes como para traders experimentados.

853 Vistas totalesPublicado en 2025.10.20Actualizado en 2026.06.02

Cómo comprar 4

Discusiones

Bienvenido a la comunidad de HTX. Aquí puedes mantenerte informado sobre los últimos desarrollos de la plataforma y acceder a análisis profesionales del mercado. A continuación se presentan las opiniones de los usuarios sobre el precio de 4 (4).

活动图片