# Пов'язані статті щодо Investing

Центр новин HTX надає останні статті та поглиблений аналіз на тему "Investing", що охоплює ринкові тренди, оновлення проєктів, технологічні розробки та регуляторну політику в криптоіндустрії.

Are Rising U.S. Stocks Getting More Dangerous? Goldman Sachs: Downside Protection Mechanisms Have Almost Failed

The US stock market rally is showing signs of becoming increasingly precarious as key downside protection mechanisms fail, according to Goldman Sachs. Derivatives strategist Brian Garrett notes that the S&P 500 options volatility skew has plunged to an 18-month low, indicating the market now prices an 8% probability for both a 10% drop and a 10% rise—a sign of "skew failure." Concurrently, Goldman's Panic Index hit a two-year low, reflecting minimal demand for tail-risk hedging. This complacency emerges amid a relentless market surge, with the S&P 500 setting new records frequently in 2024. Garrett highlights three major concerns: extreme concentration in the top ten stocks (40% of index weight), heavy reliance on AI-themed performance, and a price pattern eerily similar to the 1998-1999 period. Despite pervasive media pessimism, this fear is absent in options pricing. Downside hedge costs are historically low. Goldman suggests tactical trades: buying RSP outperformance options versus the SPX for a broadening rally, purchasing VIX calls for protection, and going long on Bitcoin ETF volatility. Hedge funds have been net buyers for two weeks, with sector rotation into financials and out of industrials. Notably, the global single-stock leveraged/ inverse ETF AUM has doubled to over $60 billion in two months, underscoring growing speculative activity.

marsbitВчора 09:45

Are Rising U.S. Stocks Getting More Dangerous? Goldman Sachs: Downside Protection Mechanisms Have Almost Failed

marsbitВчора 09:45

Will the US AI Bull Market Crash?

Will the U.S. AI bull market collapse? SoftBank has invested $34.6 billion in OpenAI, with Masayoshi Son selling stakes in Nvidia, Deutsche Telekom, Alibaba, and T-Mobile to fund it. He plans to invest another $30 billion this year, raising his stake to 13%, even taking on debt. This frenzy is driven by OpenAI's valuation surging to $852 billion in February, generating over $45 billion in paper gains for SoftBank. Similarly, Anthropic is reportedly negotiating funding at a $900 billion valuation, up from $61.5 billion a year ago. The article draws a parallel to the dot-com bubble, comparing OpenAI and Anthropic to Yahoo. Back then, Yahoo's portal model seemed unassailable, but it was disrupted by more targeted services. Today, the core assumption is that all AI applications must rely on foundational models like OpenAI and Anthropic, making them permanent "toll booths" of the AI era. However, as AI becomes a ubiquitous utility, this "model-as-gateway" advantage may erode. Financially, to justify trillion-dollar valuations with high P/E ratios (30-40x), these companies would need annual net profits of $25-30 billion, implying revenues of $50-80 billion. Current metrics like Annual Recurring Revenue (ARR)—$25 billion for OpenAI and $30 billion for Anthropic—are based on monthly subscription extrapolations and include promotional, less-sticky API usage. Aggressive price cuts on tokens to capture market share further squeeze margins. A critical risk is that the entire AI industry's profitability depends on downstream applications generating substantial revenue. Currently, besides some coding and content assistance, no "killer app" has emerged to create massive new markets. If enterprises pause AI spending due to performance plateaus, economic downturns, or poor ROI, the foundation for these valuations could crumble. Two potential outcomes are outlined: 1) A Yahoo-style crash where valuations collapse, companies downsize, and AI becomes a low-margin utility business. 2) A successful reinvention where companies find sustainable monetization, perhaps by replacing SaaS or achieving AGI. However, the market's impatience could trigger a downturn before such a breakthrough. The article concludes that while AI will undoubtedly transform society as a fundamental infrastructure, the current speculative frenzy mirrors past bubbles. A correction wouldn't mean the end of AI but could remove financial hype, leading to more grounded integration into industries. The rapid rise warrants caution, as a collapse in trillion-dollar valuations could cause significant economic damage, surpassing the fallout from the dot-com bust.

marsbit05/29 09:11

Will the US AI Bull Market Crash?

marsbit05/29 09:11

Interview with Macro Master Raoul Pal: The Economic Singularity Is Approaching, Don't Get Off the Train Easily in the Next Four Years

Macro investor Raoul Pal discusses the approaching "Economic Singularity," driven by the unprecedented capital race in AI between the US and China. He argues this competition, focused on turning energy into intelligence, will not stop until the system can no longer handle the speed of technological growth. Pal remains bullish on crypto, viewing it as having superior risk-adjusted returns long-term. He believes crypto's total addressable market is now "infinite" due to the future proliferation of AI agents operating on-chain. Pal sees the recent Bitcoin pullback to $60k as a normal, painful correction within a bull market, not a bear trend. He advocates a "buy and hold" strategy over trading, as long-term holders historically outperform. His buys during dips include SUI and Zcash. He states Layer 1 smart contract platforms (like ETH, SOL, SUI) will capture most crypto value as they are the foundational infrastructure for the future digital economy and AI agent activity. While DeFi faces security challenges, he sees this pushing for better products and notes DeFi is ideally suited for AI agents. He is also launching an NFT fund, betting on a revival of the sector as crypto wealth grows. Pal concludes that with massive trends like fiat debasement, financial migration to blockchain, and exploding global liquidity, investors should accumulate crypto assets and hold for the next four years, not sell. He assigns a 70% probability to this highly bullish outcome, citing regulatory progress, institutional adoption of stablecoins, and crypto's current undervaluation relative to assets like the Nasdaq.

marsbit05/29 07:50

Interview with Macro Master Raoul Pal: The Economic Singularity Is Approaching, Don't Get Off the Train Easily in the Next Four Years

marsbit05/29 07:50

Deconstructing Mysterious Researcher Serenity's Chokepoint Algorithm and the Global Revaluation of Equity Assets

Unmasking Serenity's "Chokepoint Theory": A Framework for AI-Era Investment This article deconstructs the investment methodology of the pseudonymous online researcher Serenity (formerly AleaBito on Reddit), who claims extraordinary returns by identifying critical bottlenecks in AI and robotics supply chains. Rejecting Wall Street's typical top-down analysis, Serenity employs a bottom-up, reverse-engineering approach. Starting with an end product like an Nvidia GPU cluster, he meticulously maps the global supply chain down to its most essential, irreplaceable physical components—the "choke points." These are low-profile, often monopolized sub-sectors where a disruption could paralyze entire downstream industries, analogous to a strategic strait controlling global oil flow. His primary focus is the physical evolution of AI data centers, specifically the shift from copper interconnects to silicon photonics and Co-Packaged Optics (CPO). He identifies five critical, monopolized technical barriers within CPO: high-precision fiber alignment components (e.g., FOCI), external light sources and high-power lasers (e.g., SIVE), molecular beam epitaxy equipment (ALRIB/Riber), ultra-high-purity red phosphorus raw materials, and Silicon-on-Insulator (SOI) wafers (Soitec). Serenity extends this framework to humanoid robotics, arguing that while the AI "brain" resides in the US, the physical "body" hardware (actuators, gears, motors) is dominated by Asian manufacturers. He highlights a looming "demand tsunami" for specific rare earth elements essential for robot motors, presenting a severe future supply chain and geopolitical challenge. The article cites several of his investment targets (RPI, SIVE, Soitec, VLN, NBIS) where identifying such choke points, coupled with correcting market mispricings (e.g., ticker code confusion for VLN), allegedly led to significant re-ratings. Ultimately, the article posits that Serenity's core value is not in providing stock picks, but in demonstrating a paradigm: using deep technical analysis to find the silent, indispensable "physical switches" within complex systems, thereby exploiting institutional research blind spots. However, it warns of major risks, including illiquidity in micro-cap stocks, potential "pump-and-dump" accusations, and the foundational gamble that his identified technological paths (like CPO) are the correct and inevitable ones.

marsbit05/28 07:26

Deconstructing Mysterious Researcher Serenity's Chokepoint Algorithm and the Global Revaluation of Equity Assets

marsbit05/28 07:26

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