# Strategy Related Articles

HTX News Center provides the latest articles and in-depth analysis on "Strategy", covering market trends, project updates, tech developments, and regulatory policies in the crypto industry.

Breaking: OpenAI Loses Key Figure, Father of Sora Departs, Turmoil Continues on the Eve of IPO

OpenAI is undergoing significant internal turmoil ahead of its planned IPO, marked by high-profile executive departures and strategic shifts. Key figures including Sora project lead Bill Peebles and Chief Product Officer Kevin Weil have announced their exits. The company is consolidating projects, discontinuing standalone products like the research tool Prism and integrating it into Codex, while also halting the video project Sora. Simultaneously, CEO Sam Altman faces renewed allegations of conflicts of interest. Reports reveal he attempted to have OpenAI invest in his personal ventures, such as nuclear fusion company Helion and space firm Stoke Space, raising internal concerns about transparency and governance. These moves come as OpenAI, valued at around $850 billion, shifts from rapid expansion to focusing resources on core priorities like enterprise products and AGI development, under pressure from competitors and the upcoming IPO.

marsbit04/18 05:28

Breaking: OpenAI Loses Key Figure, Father of Sora Departs, Turmoil Continues on the Eve of IPO

marsbit04/18 05:28

Analyst Exposes Bitcoin Market Maker Buy Strategy, Shows What Happens When Accumulation Ends

A crypto analyst, Merlijn The Trader, has presented a market structure model suggesting Bitcoin is following an institutional trading cycle. The model outlines four key phases: a "Distribution" phase where large holders sold BTC near highs, a sharp "Flush" that dropped prices 38% to eliminate weak traders, the current "Accumulation" phase where institutions are buying in a tight range between $60k-$77k, and a future "Re-accumulation" period. The analyst projects that once accumulation ends, Bitcoin could break out to new all-time highs, with a potential target above $142,000 by early 2027. Holding above the $70,000 resistance level is critical for this bullish scenario to remain valid.

bitcoinist04/18 03:01

Analyst Exposes Bitcoin Market Maker Buy Strategy, Shows What Happens When Accumulation Ends

bitcoinist04/18 03:01

Fortune Investigation: Copying Strategy's Homework Fails, Fund Suffers Huge Losses and Liquidation, Fiancée Dies Mysteriously in Africa

In a dramatic turn of events, Joe McCann, founder of the crypto fund Asymmetric, faces both financial collapse and personal tragedy. After raising funds from prominent investors like Marc Andreessen, Asymmetric's liquidity fund nearly doubled in value during the 2024 crypto market surge. However, by July 2025, the fund suffered massive losses of nearly 80%, leading to investor redemptions and eventual liquidation. McCann attempted to pivot the fund’s strategy to emulate Michael Saylor’s "digital asset treasury" model but failed. Amid this financial turmoil, McCann’s personal life unraveled. His fiancée, influencer Ashly Robinson, died under suspicious circumstances during a vacation in Tanzania in April 2025. Initially ruled a suicide, her death is under investigation, with McCann’s passport seized by local authorities. Robinson’s family has called the events "suspicious." McCann, who had built a flashy personal brand around crypto success and cultural influence, now faces a crisis extending far beyond financial losses, encapsulating the high-risk, "asymmetric" nature of both his investments and his life.

marsbit04/18 00:09

Fortune Investigation: Copying Strategy's Homework Fails, Fund Suffers Huge Losses and Liquidation, Fiancée Dies Mysteriously in Africa

marsbit04/18 00:09

Bitcoin Trading Strategy Breakdown: Celebrity Predictions and Classic Models All Fail, Only These Four Indicators Remain

Analysis of Bitcoin Trading Strategies: Why Celebrity Forecasts and Classic Models Fail, Leaving Only These Four Reliable Indicators This analysis examines the failure of common Bitcoin prediction methods and identifies four reliable indicators for constructing a trading strategy. The author reviewed all major BTC prediction approaches from 2017-2025, categorizing them into three groups: celebrity price targets (consistently over-optimistic), analytical models like Stock-to-Flow (broken post-2022), and on-chain signals. The key finding is that more data often creates confusion, not clarity. The strategy discards unreliable elements: celebrity predictions (incentivized to be extreme), pure models (invalidated by post-ETF market changes), and the Fear & Greed Index used alone (too many false signals). Four reliable indicators were selected: 1. **MVRV Z-Score:** Accurately identifies cycle bottoms when entering its green zone (e.g., 2018, 2020, 2022). Note: Its ability to call tops is now ineffective post-2024. 2. **SOPR (28-day MA):** Consistently signals bottoms when below 1.0, indicating holders are selling at a loss. 3. **ETF Net Flow:** A crucial post-2024 metric showing institutional momentum (e.g., sustained inflows = buying). 4. **Macro Liquidity (Fed policy & M2):** Sets the overall directional bias (e.g., bullish during easing cycles). The core strategy involves waiting for a multi-signal共振 (resonance). For example, a bottom signal requires MVRV in the green zone + SOPR < 1.0. A top signal requires overheated on-chain data + sustained ETF outflows. Macro policy sets the overall direction. The Fear & Greed Index is only used as a weighted confirmatory signal, never alone. Action is only taken when three or more indicators align. The author automated this into a monitoring system that sends Telegram alerts only when signals trigger. As of the article's date (April 15, 2026), the system showed a strong bottom signal: extreme fear (F&G=12), MVRV in the buy zone, and SOPR < 1.0. The only contrary signal was weak ETF flows. Historically, such triple on-chain共振 has preceded 100%+ returns. The conclusion emphasizes building a personal framework over relying on external predictions, allowing for iterative improvement and customization based on individual risk tolerance.

marsbit04/17 08:08

Bitcoin Trading Strategy Breakdown: Celebrity Predictions and Classic Models All Fail, Only These Four Indicators Remain

marsbit04/17 08:08

Can You Make a Steady Profit by Blindly Following Polymarket's Pre-Game Win Probability to Bet on NBA Games?

The article investigates whether blindly betting on NBA teams with higher pre-game win probabilities on Polymarket guarantees profits. Backtesting data from the 2025-26 regular season (1,096 games) shows that a strategy of consistently betting $100 on the team with the higher pre-game probability resulted in a net loss of $2,054 (ROI: -1.87%), indicating that the market is efficient and prices are accurately set. Further analysis reveals that returns varied significantly by team. Certain teams, such as the Trail Blazers (POR, 19% ROI), 76ers (PHI, 14%), Spurs (SAS, 12%), Lakers (LAL, 11%), and Hornets (CHA, 9%), consistently outperformed market expectations when favored. In contrast, top-performing teams like the Celtics, Knicks, and Nugks had ROIs close to zero or negative, showing their probabilities were efficiently priced. The weakest teams showed extreme ROI variations but had insufficient sample sizes for reliable conclusions. The key takeaway is that blindly following pre-game probabilities is not a profitable strategy overall, but targeting specific teams may yield better results.

marsbit04/17 07:02

Can You Make a Steady Profit by Blindly Following Polymarket's Pre-Game Win Probability to Bet on NBA Games?

marsbit04/17 07:02

Can You Make a Steady Profit by Blindly Following Polymarket's Pre-Game Win Probability to Bet on NBA Games?

**Can You Consistently Profit by Blindly Following Pre-Game Win Probabilities on Polymarket for NBA Games?** A backtest of the entire NBA 2025-26 regular season (1,096 games) was conducted to test the strategy of always betting $100 on the team with the higher pre-game win probability on Polymarket. The results show that this strategy is not profitable. The total amount wagered was $109,600, with a return of $107,545.20, resulting in a net loss of $2,054 and a Return on Investment (ROI) of -1.87%. This indicates that the market is highly efficient, and pre-game probabilities are accurately priced, leaving no simple arbitrage opportunity. In fact, blindly following the market would have been slightly less profitable than betting against it. However, a deeper analysis by team revealed significant differences. Certain teams consistently outperformed market expectations when they were favored to win: * Portland Trail Blazers (POR): 19% ROI * Philadelphia 76ers (PHI): 14% ROI * San Antonio Spurs (SAS): 12% ROI * Los Angeles Lakers (LAL): 11% ROI * Charlotte Hornets (CHA): 9% ROI In contrast, the market was highly efficient for the top-performing teams, offering minimal returns (e.g., Boston Celtics ROI: 4%, Denver Nuggets ROI: -5%). Results for the weakest teams were too inconsistent due to small sample sizes. The key finding is that team-specific factors, rather than the probability percentage itself, drive potential value, making a one-size-fits-all strategy ineffective.

Odaily星球日报04/17 06:58

Can You Make a Steady Profit by Blindly Following Polymarket's Pre-Game Win Probability to Bet on NBA Games?

Odaily星球日报04/17 06:58

An Internal Memo Exposes OpenAI's Most Real Anxieties and Ambitions

An internal memo from OpenAI's Chief Revenue Officer, Denise Dresser, reveals the company's strategic priorities and competitive anxieties as the enterprise AI market matures. The document outlines a shift from competing solely on model capability to winning on integration, platform strategy, and becoming "hardest to replace." Key priorities for Q2 include: the model layer, the agent platform, expanding market reach via Amazon, selling the full tech stack, and controlling deployment. The goal is to evolve from a point solution to an enterprise AI "operating system" by deeply embedding into customer workflows, creating switching costs, and securing multi-year, nine-figure deals. The memo contains a direct and unusually sharp critique of rival Anthropic, accusing it of building a narrative on "fear" and "restriction," suffering from compute shortages leading to user experience issues, and overstating its annualized revenue by $8 billion due to accounting methods. This public criticism is seen as a calculated move for investor narratives, internal mobilization, and external signaling. For the Chinese AI market, the memo highlights a gap in competition stages. While domestic players still focus on benchmarks and price wars, the next phase will be won on deployment, platform integration, and ecosystem. It also underscores the critical importance of data sovereignty and trust, suggesting that compliant, auditable, on-premise solutions could be a major differentiator in regulated industries. A notable warning for Chinese companies is OpenAI's claim that its biggest constraint is "capacity," not demand. This contrasts sharply with the domestic market's challenge of finding enterprise customers willing to make large, long-term paid commitments, pointing to a fundamental gap in commercial adoption readiness.

marsbit04/14 10:21

An Internal Memo Exposes OpenAI's Most Real Anxieties and Ambitions

marsbit04/14 10:21

A Four-Page Internal Letter: What Card Is OpenAI Playing?

OpenAI's internal memo, revealed by The Information, outlines a strategic narrative against Anthropic across three key areas: revenue accounting, enterprise competition, and compute capacity. First, OpenAI CRO Denise Dresser challenged Anthropic’s reported $30B annualized revenue, claiming the actual net figure—using OpenAI’s accounting method—is $22B. The discrepancy stems from differing GAAP interpretations: Anthropic books gross revenue (including cloud partner shares), while OpenAI records net revenue after partner deductions. Second, enterprise adoption data from Ramp shows Anthropic rapidly closing the gap with OpenAI, narrowing from an 11% to a 4.6% difference within months. Anthropic already leads in high-value sectors like tech, finance, and professional services. Dresser acknowledged Anthropic’s edge in coding capabilities but warned against being a "single-product company" in a platform war. Third, while current compute capacity is comparable (OpenAI ~1.9 GW vs. Anthropic ~1.4 GW), OpenAI’s long-term plans aim for 30 GW by 2030—four times Anthropic’s projected 7-8 GW by 2027. Anthropic’s growth depends on sustaining enterprise revenue to cover rising cloud costs, estimated to reach $6.4B by 2027. The memo also highlighted OpenAI’s strategic shift: reducing reliance on Microsoft (which “limited customer reach”) and partnering with Amazon, which invests in both OpenAI and Anthropic. This places Amazon’s Bedrock platform as a battleground where both models compete for the same enterprise clients.

marsbit04/14 08:44

A Four-Page Internal Letter: What Card Is OpenAI Playing?

marsbit04/14 08:44

The True Target of Hong Kong's 'Open Scheme' Was Never Stablecoins

Hong Kong's recent issuance of the first stablecoin licenses to HSBC and Standard Chartered—while excluding strategic players like Bank of China Hong Kong—has sparked market disappointment. However, this move may be a deliberate “managed failure” designed not to promote a commercial stablecoin industry, but to advance the government’s broader financial infrastructure goals. The licensed banks, with limited commercial incentive, are effectively subsidizing the development of user education, technical infrastructure, and regulatory frameworks. Their participation ensures that Hong Kong can build the ecosystem needed for its central bank digital currency (e-HKD) without direct public investment. Key narratives around stablecoin use cases—cross-border payments, RWA tokenization, and retail consumption—are structurally flawed and unsustainable in Hong Kong’s context. Instead, the licensing framework serves as a tool to channel private sector resources into developing a state-controlled digital clearing system. The ultimate aim is to reclaim monetary clearing sovereignty amid global shifts toward CBDCs and digital monetary competition. While surface-level Web3 excitement fades, Hong Kong is positioning itself to compete as a next-generation financial hub with a modernized, sovereign financial infrastructure.

marsbit04/14 07:14

The True Target of Hong Kong's 'Open Scheme' Was Never Stablecoins

marsbit04/14 07:14

Dragonfly: Venture Capital Can Only Be Stable and Sustainable by Listening to LPs, Backing Reliable People, and Adapting to the Market

The article "Dragonfly: VCs Must Listen to LPs, Back Strong Founders, and Follow the Market to Sustain Success" by Rob Hadick argues that venture capital, especially in crypto, is fundamentally market-driven. VCs serve their limited partners (LPs), whose priorities extend beyond absolute returns to include risk-adjusted performance, reputation, regulatory exposure, and access to key networks. The current market contraction and concentration of capital into fewer funds are signs of a healthy, functioning market, not a failure. To survive, VCs must align their strategies with LP demands. This often means investing in trending sectors like stablecoins and prediction markets, even if not first. While contrarian bets are possible, they are a privilege earned by first demonstrating consistent, stable returns. The industry rewards sustainability, not reckless heroism. Similarly, the notion that founders lack original ideas is misguided. Great companies are often not the first in a space but the best execution of a model. Success is driven by market forces: VCs are rewarded for correct judgment and delivering what LPs want, and founders are rewarded for building valuable, profitable businesses that attract investment. Ultimately, ideological posturing is irrelevant; market dynamics dictate everything.

marsbit04/14 02:13

Dragonfly: Venture Capital Can Only Be Stable and Sustainable by Listening to LPs, Backing Reliable People, and Adapting to the Market

marsbit04/14 02:13

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