# Investing Related Articles

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This New Generation of US Stock Trading Gods No Longer Read Financial Reports

The new generation of "stock gods" in the 2026 US AI bull market are not analyzing traditional financial reports. Instead of focusing on giants like NVIDIA, figures like the 22-year-old Leopold Aschenbrenner (who reportedly turned $200M into $14B) and influencers like Serenity on platforms like Reddit's WallStreetBets, X, and Substack are gaining fame and returns by targeting obscure, low-cap "micro-cap" stocks. Their strategy, dubbed "supply chain sniping," involves identifying critical, often monopolistic, bottlenecks in the AI hardware supply chain—such as specific materials or components essential for giants like Google and NVIDIA—that are missed by mainstream Wall Street analysts. Serenity's call on AXTI, a $700M company supplying indium phosphide substrates crucial for photonics and optical interconnects, saw the stock soar from ~$12 to nearly $150. Similarly, accounts like KawzInvests and PhotonCap focus on thematic, supply-chain-driven research in areas like AI infrastructure, optics, and cloud services for SMEs, bypassing traditional valuation metrics. This shift represents a cultural move away from Warren Buffett-style value investing based on deep financial statement analysis. The new approach thrives on low liquidity, early narratives, and strong community propagation on social media, similar to meme stocks or crypto. However, this "attention economy" strategy carries risks: it depends on sustained information gaps, the underlying companies' ability to deliver fundamental results, and the potential for crowded, volatile exits as narratives shift. The trend also shows crypto traders applying their narrative-sensing skills to US micro-caps, marking a significant evolution in trading culture.

marsbit05/27 11:55

This New Generation of US Stock Trading Gods No Longer Read Financial Reports

marsbit05/27 11:55

X Stock Market Investment & Trading: A 'Noise-Free' List of 50 Key Accounts

Titled "A 'Noise-Reduction' List of 50 Top US Stock Market Influencers on X," this article curates a selection of accounts for investors seeking quality information beyond follower counts. The list prioritizes accounts that have consistently discussed US stocks, ETFs, earnings, macroeconomics, options, and tech/AI/semiconductor topics over the past 90 days. Selection criteria focused on genuine informational value, stable analytical frameworks over mere news aggregation, and a clear relevance to US equity markets, with tighter filtering for crypto-heavy accounts. The final 50 accounts are categorized into three groups: - **Core US Stocks/Trading (31 accounts)**: Covering market trends, individual stocks, earnings, valuation, options, macroeconomics, and trading strategies. - **Tech/AI/Semiconductors (18 accounts)**: Focused on tech stocks, AI supply chains, semiconductor cycles, data centers, and cloud capital expenditure. - **News Source (1 account)**: Useful as a news radar, not for standalone decision-making. Presented alphabetically by handle, the list includes analysts, traders, and researchers such as @amy6tina (options/CFA), @dylan522p (semiconductors/AI infrastructure), @gerberkawasaki (tech stocks), @jimcramer (market commentary), and @tengyanai (semiconductors/AI trends). The article suggests using the list to: 1) complete one's information sources on US markets and specific sectors, 2) observe narrative linkages between AI, semiconductors, earnings, macro liquidity, and stock prices, and 3) "de-noise" and enhance the quality of one's X feed. It clarifies this is not investment advice or an endorsement, but a snapshot of content relevance and informational value for US equity investors.

marsbit05/27 00:08

X Stock Market Investment & Trading: A 'Noise-Free' List of 50 Key Accounts

marsbit05/27 00:08

Silicon Bull, Carbon Bear: The Wealth Code of 2026 is Only 'Chips' and 'Light'

The article, titled "Silicon Bull, Carbon Bear: In 2026, the Wealth Code Lies Only in 'Chips' and 'Optics'", discusses the extreme market divergence in 2026 driven by the AI investment frenzy. Investment managers who concentrated on the AI hardware supply chain, particularly computing infrastructure, optical modules, and memory chips, have seen their fund net asset values (NAVs) surge dramatically, even reaching record highs. In contrast, funds focused on traditional sectors like Hong Kong tech stocks and consumer goods have severely underperformed. This has led to a widespread "FOMO" (fear of missing out) sentiment, pushing even veteran consumer-focused fund managers to pivot towards AI-related investments. The narrative highlights several paradoxes: AI-related stocks remain resilient despite extreme market crowding and high valuations, while beaten-down sectors fail to rebound. The author dubs this split market "Silicon Bull, Carbon Bear," suggesting a bull market only for those invested in silicon-based tech (AI hardware) and a bear market for carbon-based traditional economy sectors. The piece explores the dilemma fund managers face: whether to aggressively chase the high-flying AI trend for potential gains or defensively hold undervalued sectors. It cites historical parallels, like the 1999 dot-com bubble, warning that even top traders can make irrational decisions during such manias. Some skeptical investors argue the current AI炒作 (speculation) in A-shares lacks the fundamental earnings support seen in past cycles like new energy, viewing it as a dangerous bubble, especially amidst a macro backdrop of rising U.S. bond yields. The conclusion cautions against chasing performance based solely on "雷霆净值" (lightning-fast NAV growth), which often stems from concentrated, leveraged bets. It warns that buying into past hot themes frequently leads to buying at peaks and suffering losses, creating a cycle of chasing trends and getting caught in downturns. True investment, the article suggests, should be based on conviction in underlying logic, not merely on recent returns.

marsbit05/21 07:46

Silicon Bull, Carbon Bear: The Wealth Code of 2026 is Only 'Chips' and 'Light'

marsbit05/21 07:46

When the Bubble Comes, How to Short "Smartly"?

Title: When the Bubble Comes, How to "Smartly" Short? Author: Campbell (Macro Analyst) Summary: Amid the heated debate over whether the current AI-driven market is in a bubble, analysts are divided. While some, like Dan Niles and Paul Tudor Jones, argue that the AI boom has further to run, Michael Burry warns of similarities to the dot-com bubble. The author explores practical strategies for navigating and potentially shorting a bubble without being crushed by its momentum. Key challenges in shorting a bubble include the exponential risk from parabolic price increases and the high cost of options due to extreme volatility. Instead of directly shorting the bubbly asset, the author proposes three approaches: 1. **Find the "Wedge"**: Identify external factors that could pop the bubble, such as rising interest rates. By betting on trends that could undermine the bubble (e.g., inflation or higher rates), investors can hedge without timing the bubble's collapse. 2. **Short the "Victims"**: Target assets adjacent to the bubble that are highly vulnerable to its burst, such as over-leveraged companies or sectors with "negative convexity." These assets may have cheaper options and suffer disproportionately when the bubble stalls. 3. **Wait for Confirmation**: Exercise discipline and wait for clear signals of a breakdown, including deteriorating fundamentals, exhausted buying sentiment, and decisive breaks in trendlines. Only then should investors take substantial short positions. The author shares their recent actions, including shorting SPX and high-yield bonds while buying short-term put spreads, and emphasizes avoiding direct shorts on vertically rising assets. The core takeaway: Hedge, identify wedges, wait for confirmation, and only then commit heavily.

marsbit05/14 08:57

When the Bubble Comes, How to Short "Smartly"?

marsbit05/14 08:57

Leaving OpenAI, How Much Has Their Net Worth Increased?

Former OpenAI employees have collectively accrued near-trillion dollar valuations through ventures and investments, charting AI's future. The article highlights two main paths: founding high-value companies like Anthropic and Perplexity, or applying insider insights as investors. Leopold Aschenbrenner exemplifies the investor path. After being fired from OpenAI, he leveraged firsthand knowledge of AI's massive energy demands to make hugely successful public market bets on nuclear and fuel cell companies, practicing "cross-industry cognitive arbitrage." Other alumni, like the Zero Shot VC fund founders, use their technical foresight for early-stage investing. Their key advantage lies not just in picking winners, but in knowing which technical approaches are likely dead ends—a "veto list" derived from internal OpenAI experience. Angel investing within the network, as seen with Mira Murati and Sam Altman, operates on deep, pre-existing understanding of a founder's capabilities, reducing due diligence to near zero. This creates an ecosystem bound by a shared belief in AGI's imminent arrival, differing from networks like the "PayPal Mafia" which were built on shared past struggles. The shift of these builders to investors signals a profound conviction: their situational awareness of the AI landscape is now so clear that deploying capital based on that judgment is more efficient than building themselves. They are allocating bets on the future they helped shape from the inside.

marsbit05/13 09:06

Leaving OpenAI, How Much Has Their Net Worth Increased?

marsbit05/13 09:06

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