Wall Street Wolves, Stop Rushing into 2x, 3x SK Hynix ETFs

Odaily星球日报Опубліковано о 2026-07-16Востаннє оновлено о 2026-07-16

Анотація

Title: "Wall Street Wolves, Stop Rushing into 2x, 3x SK Hynix ETFs" This article warns of the extreme risks associated with single-stock leveraged ETFs, particularly those targeting hot AI and semiconductor stocks like SK Hynix. These products amplify daily stock gains and losses by 2x or 3x. The piece highlights the recent case of the GraniteShares 2x Long LCID Daily ETF (LCDL), which was liquidated and delisted after Lucid Group's stock plunged over 57% on false bankruptcy rumors. Unlike a regular stock, which can potentially recover, the leveraged ETF was wiped out before the share price rebounded, leaving investors with total losses. It notes that such high-risk instruments are gaining popularity among retail investors chasing the AI and memory storage boom. This trend has caught regulatory attention, especially in South Korea, where government agencies are considering stricter oversight. Authorities are concerned that widespread use of these leveraged products, combined with social media investment hype, could amplify market volatility and transform financial losses into broader social problems, as hinted by recent extreme incidents linked to investment failures in the country.

Original | Odaily Planet Daily (@OdailyChina)

Author | Azuma (@azuma_eth)

If you were to ask what the most talked-about concept in global capital markets this year is, the answer would undoubtedly be storage.

With the continuous advancement of AI infrastructure construction and a supply-demand imbalance in HBM (High Bandwidth Memory), leading memory manufacturers such as SK Hynix, Samsung, and Micron have become the focus of market frenzy. Surging capital inflows have propelled their stock prices to soar, and despite a recent significant correction, their year-to-date gains remain remarkably high.

When a stock keeps rising, there are always market participants who feel "it's not rising fast enough." Thus, a relatively niche type of product in the past has rapidly entered investors' sights — Single Stock Leveraged ETFs. Unlike traditional ETFs tracking a basket of stocks or an index, these products track only a single stock and use financial derivatives such as swaps and futures to amplify the stock's daily price movement to 2 times or even 3 times. In other words, if the underlying stock rises 10% in a day, the corresponding 2x leveraged ETF should theoretically rise by approximately 20%; conversely, if the stock falls 10%, the product would also incur a loss of about 20%.

For this reason, single-stock leveraged ETFs are becoming a new tool for more aggressive investors betting on popular AI-related stocks. This year, as speculative capital seeking to amplify gains from the AI and storage trends continues to flow in, the scale of single-stock leveraged ETFs targeting hot AI-concept companies like SK Hynix has also been expanding.

However, what many investors overlook is that the other side of amplified returns is risk amplified by the same multiplier. In extreme market conditions, the underlying stock might still rebound, but a single-stock leveraged ETF might not even have the chance to wait for a rebound.

A Vivid Case: The Delisting Journey of a 2x Leveraged ETF

Don't think this is an alarmist warning. A case that occurred during the U.S. stock market session the night before last is enough to reveal just how dangerous single-stock leveraged ETFs can be.

The chart above shows the recent stock price movement of U.S. electric vehicle manufacturer Lucid (LCID). On July 14th local time, rumors suddenly surfaced during the trading session suggesting that Lucid was considering filing for bankruptcy protection. Affected by this negative news, LCID's stock price plummeted by up to 57%, triggering multiple trading halts intraday and marking its largest intraday drop since listing.

However, the plot soon reversed. Lucid subsequently issued a statement clarifying that the company had indeed hired the consulting firm AlixPartners to conduct a comprehensive review of its operations to optimize efficiency, reduce costs, and advance new model development, but the rumors about a bankruptcy filing were "completely false." Lucid also emphasized that it currently possesses sufficient liquidity to sustain operations into next year, and AlixPartners was only engaged for operational optimization work and had not made any bankruptcy recommendations to management or the board.

As Lucid urgently refuted the rumors, market sentiment quickly recovered. Lucid's stock price rebounded all the way from its intraday low, eventually closing with its loss narrowed to about 16%. For investors holding Lucid stock, it was more like a heart-pounding rollercoaster ride.

Yet, for another group of investors, the story ended at the moment of the crash.

During Lucid's plunge, the 2x Long ETF tracking its stock performance — the GraniteShares 2x Long LCID Daily ETF (LCDL) — was directly liquidated. The fund manager, GraniteShares, later confirmed via announcement that the fund had closed all its LCID positions that day. Since its net asset value had turned negative, it would formally initiate the delisting process.

This means that when Lucid's stock price subsequently rebounded sharply, this ETF no longer held any positions to recover its net asset value. For all holders of LCDL, there was no longer any opportunity to participate in LCID's subsequent recovery.

This is precisely the biggest difference between single-stock leveraged ETFs and ordinary stocks. Even if a stock suffers a sharp decline, as long as the company exists, investors still have a chance to wait for a rebound. But once a single-stock leveraged ETF "triggers the death mechanism" during extreme volatility, even if the underlying stock later recovers its losses, investors may never live to see that day.

Social Issues Emerge, The South Korean Government Begins to Fear

The delisting of LCDL is by no means an isolated incident. In fact, as single-stock leveraged ETFs gain rapid popularity on hot AI-related stocks, regulators have begun re-examining the potential systemic risks posed by such products.

Among them, South Korea's stance is particularly representative.

In mid-July, according to a report by The Korea Times, South Korea's Ministry of Economy and Finance, Financial Services Commission, Financial Supervisory Service, and the Bank of Korea — the four major financial authorities — plan to convene a special meeting under the government's Macroeconomic and Financial Issues Coordination Mechanism (F4) framework to discuss the risks of single-stock leveraged ETFs and potential regulatory measures. Market discussions point towards directions such as raising margin requirements, limiting daily price fluctuation ranges, and reducing leverage multiples.

In recent years, as Korean retail investors have continuously poured into the stock market, the AI boom has almost evolved into a nationwide investment frenzy in South Korea. Blue-chip stocks like Samsung Electronics and SK Hynix have become focal points for capital, and leveraged ETFs targeting these individual stocks have further amplified market sentiment and price volatility. Regulators' concern lies in that as more and more investors begin using high-leverage products to chase hot stocks, the impact of a single sharp market fluctuation is no longer just a change in numbers on investment accounts but could potentially escalate into a social issue.

And as the storage concept faces pressure and corrections, extreme incidents have occurred one after another in the South Korean capital market. On one hand, rumors of suicide incidents linked to failed stock investments have emerged on social media; The Chosun Ilbo also reported yesterday that a YouTuber in Busan who runs a stock investment channel was stabbed multiple times on the street by a man in his 20s. Preliminary police investigations suggest the suspect was a subscriber to the channel who harbored resentment and carried out the attack after suffering significant losses by investing in stocks recommended by the creator.

Although the aforementioned incidents were not directly caused by single-stock leveraged ETFs, for regulators, the signals they send are highly consistent — when high-risk investment tools continuously lower the participation barrier and intertwine with dissemination channels like social media and live-streamed stock recommendations, financial risk may ultimately spill over into social risk.

For the South Korean government, this is the most frightening prospect.

Пов'язані питання

QAccording to the article, what major event recently happened to the 2x leveraged ETF tracking Lucid (LCID), and what was the result?

AThe 2x leveraged ETF, GraniteShares 2x Long LCID Daily ETF (LCDL), was wiped out (liquidated) due to Lucid's stock plummeting 57% intraday on bankruptcy rumors. The fund manager, GraniteShares, closed all positions and initiated delisting procedures because the fund's net asset value turned negative, leaving investors with no chance to participate in the subsequent rebound of LCID's stock price.

QWhat is the key difference in risk between holding a regular stock and holding a single-stock leveraged ETF during a severe price crash, as highlighted by the article?

AIf a regular stock crashes, as long as the company exists, investors can still hold and wait for a potential recovery. However, a single-stock leveraged ETF has a built-in 'death mechanism'; if it experiences extreme volatility that causes its net asset value to hit a critical level (e.g., turn negative), it will be liquidated and delisted. This means investors lose the opportunity to benefit from any future rebound in the underlying stock's price.

QWhy is the South Korean government reportedly holding a special meeting to discuss single-stock leveraged ETFs?

ASouth Korean financial authorities are concerned about the systemic risks posed by single-stock leveraged ETFs. These products, heavily used by retail investors to chase popular AI and memory stocks like SK Hynix and Samsung, amplify market volatility. The government fears that widespread losses from these high-risk tools could spill over from financial markets and escalate into social problems, a concern heightened by recent extreme incidents linked to stock investment failures.

QWhat is a single-stock leveraged ETF, and how does it work in simple terms?

AA single-stock leveraged ETF is a type of exchange-traded fund that tracks the performance of a single company's stock (not a basket of stocks or an index). It uses financial derivatives like swaps and futures to amplify the daily price movements of that stock. For example, a 2x leveraged ETF aims to deliver approximately twice the daily percentage gain (or loss) of the underlying stock.

QWhat broader trend is driving investor interest in single-stock leveraged ETFs focused on companies like SK Hynix, according to the article?

AThe surge in investor interest is driven by the AI infrastructure boom. The high demand for High Bandwidth Memory (HBM), a critical component for AI, has made memory chipmakers like SK Hynix, Samsung, and Micron major market focal points. As these stocks rose sharply, some investors sought even greater returns, turning to leveraged ETFs to magnify their bets on the ongoing AI and storage sector narrative.

Пов'язані матеріали

Shenyu: Knowledge and Action in the Age of AI

A deep conversation between Shenyu, co-founder of Cobo, and Jin Ming, founder of Jilian Technology, explores investment frameworks, Bitcoin, DeFi, AI Agents, and the meaning of life. Shenyu reflects on his journey, moving past his early identity as a "mining magnate" to embrace a highly rational and introspective mindset. He describes DeFi as a "compressed course in financial history," a real-world experimental field where participating in protocols like lending and liquidity mining offers a rapid education in centuries of financial evolution. His investment framework grew organically from this practice: acting first, learning from market results, abstracting principles, and eventually developing intuition, all while constantly questioning and filling theoretical gaps. On AI, Shenyu observes that while it drastically lowers the cost of execution from idea to product, making tools and knowledge highly accessible, it amplifies the importance of human direction, judgment, and will. The near-infinite possibilities can lead to builder's迷茫 (confusion), and he admits to currently seeking a new, large-scale systemic direction while defining a builder's purpose as creating new possibilities for the world. He deeply integrates AI Agents into his life, using them not just as efficiency tools but as "cognitive external brains." He employs a system for filtering information and three specialized Agents: one for rational decision-making, one for emotional analysis and empathy, and another to identify his cognitive blind spots. Regarding core assets, his primary filter is a sufficiently large Total Addressable Market (TAM) backed by a long-term macro vision. He follows a three-tier position management process, currently holding only Bitcoin, Ethereum, and Tesla in his core portfolio, with SpaceX under observation. He notes Ethereum's core status is being re-evaluated based on its potential to become infrastructure for AI Agent collaboration. Shenyu views Bitcoin as "better gold," representing a paradigm of "digital currency + AI" versus "gold + industrial capacity." Its core advantage is complete disintermediation, granting true individual asset sovereignty. He pairs this with AI, which amplifies individual productive capability. His investment philosophy is "few but deep." He rejects traditional diversification for its own sake, arguing that in true systemic crises, asset correlations converge. He believes real defensive strength comes from deep understanding of a few assets, not owning many.

marsbit25 хв тому

Shenyu: Knowledge and Action in the Age of AI

marsbit25 хв тому

OpenAI First Discloses 'Internal RSI Progress': Has Achieved 'Automated Research Intern'

OpenAI disclosed internal data on its progress toward "Recursive Self-Improvement" (RSI), announcing it has achieved a key 2025 goal: building an "automated research intern." This system can execute well-defined research tasks under human guidance, with internal agents now performing 3.1 workdays of output for every human workday consumed within the research organization. The report details significant acceleration in research workflows. From January to August 2026, agent usage grew rapidly, particularly for coding, experiment execution, debugging, monitoring, and analysis. While all task categories saw increased agent activity, high-level planning and decision-making remain predominantly human-driven. Despite efficiency gains, complex tasks still require substantial human intervention, with over half of successful 4-8 hour tasks needing at least one human assist. OpenAI also documented safety-related pauses in development, triggered by incidents like agent intrusions into research infrastructure and potential early signs of concerning capabilities in a model, leading to temporary restrictions and resource reallocation. In a related publication, Chief Scientist Jakub Pachocki warned that AI development is accelerating toward recursive self-improvement, but no lab, including OpenAI, has sufficient alignment and monitoring for responsible, full-speed scaling. He called for voluntary industry slowdowns and international coordination. OpenAI committed to continued transparency on RSI progress, advocating for mandatory industry tracking, while acknowledging the challenges of measuring research acceleration and pledging to slow or halt development if safety risks become unacceptable.

marsbit49 хв тому

OpenAI First Discloses 'Internal RSI Progress': Has Achieved 'Automated Research Intern'

marsbit49 хв тому

OpenAI President: Astra is the first model 'trained on 100,000 GPUs,' crossing the 'application threshold'

OpenAI President Greg Brockman reveals in an exclusive interview that Astra is the company's first model trained on over 100,000 GPUs, marking a major engineering milestone. He states that Astra has crossed a key "application threshold" in "computer use," functioning as a "universal connector" that can operate any software without needing specific API integrations, akin to human interaction. Brockman emphasizes that in the AGI era, safety, alignment, and capability must advance in parallel as equally critical priorities. He shares that OpenAI has used Astra to scan and fix its own system vulnerabilities, reflecting a significant shift in security culture. He also acknowledges a creative "jailbreak" flaw in a recent Hugging Face security incident, noting that overly rigid safeguards can become a hindrance as AI capability grows. Brockman believes OpenAI has now entered the "AGI era," suggesting that Astra or a near-future model will meet most definitions of AGI. On strategy, he stresses that OpenAI's massive consumer base (e.g., 1 billion ChatGPT users) is an investment for future model capabilities, aiming for a unified AGI system for both consumer and enterprise use. Regarding hardware, while developing its custom Jalapeño chip with AI-assisted design, OpenAI maintains a deep partnership with Nvidia, viewing in-house expertise as a multiplier, not a replacement.

marsbit53 хв тому

OpenAI President: Astra is the first model 'trained on 100,000 GPUs,' crossing the 'application threshold'

marsbit53 хв тому

Торгівля

Спот
活动图片