# Risk Management Related Articles

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

Breaking the DeFi Cascading Liquidation Curse: Vitalik Proposes a New Solution

Vitalik Buterin has proposed a new DeFi design to eliminate the automatic liquidation mechanism that causes market instability during sharp downturns. The current system, used by protocols like Aave, triggers forced sales when collateral value falls below a threshold, often exacerbating price drops and creating systemic selling pressure. Buterin's alternative model is based on splitting an asset like ETH into two synthetic option-like tokens, P and N, pegged to a price index. Their combined value always equals one ETH. Instead of sudden liquidation, a position's value gradually drifts from its target peg if the market moves. Users must proactively rebalance their holdings to maintain their desired exposure, transferring the management burden from the protocol to the user or automated tools. A key advantage is the reduced reliance on real-time oracles. Pricing decisions are deferred until contract expiry, allowing for more robust, fault-tolerant oracle designs. This removes a clear liquidation threshold that speculators can target for manipulation or MEV extraction. However, significant challenges remain. Frequent rebalancing could incur high slippage and transaction costs, necessitating new liquidity provider models. The design is better suited for hedging instruments than for stablecoins requiring a rigid 1:1 peg. While not an immediate replacement for existing systems, the proposal challenges the foundational assumption that instantaneous forced liquidation is an unavoidable necessity in DeFi, opening the door for fundamentally different risk management architectures.

marsbit06/05 01:47

Breaking the DeFi Cascading Liquidation Curse: Vitalik Proposes a New Solution

marsbit06/05 01:47

a16z: Why Do Prediction Markets Matter?

Prediction markets, which allow users to trade on the outcome of future events, have gained significant traction, especially in the U.S. At their core, these markets function like any other market by aggregating information from all participants and translating it into a price signal—in this case, the perceived probability of a specific event occurring. Unlike polls or surveys that offer static snapshots, prediction markets provide dynamic, quantifiable probability estimates that update in real-time as new information and participants enter. A key advantage is the incentive structure: participants risk their own capital, which encourages serious research and trading based on genuine knowledge. This can surface information that traditional methods might miss. Furthermore, prediction markets can be created for a vast array of specialized questions—from geopolitical events to AI model performance—that aren't covered by traditional financial markets. However, several challenges remain. Infrastructure issues include reliably determining event outcomes and resolving disputes. Market design must ensure participation from well-informed individuals while preventing manipulation, such as insider trading or attempts to sway public perception by artificially moving prices. Addressing these concerns around rules, participation, and contract design is crucial. If these hurdles are overcome, prediction markets could evolve into a powerful, widely-used tool for forecasting and navigating uncertainty.

marsbit06/01 08:33

a16z: Why Do Prediction Markets Matter?

marsbit06/01 08:33

Deconstructing the Investment Methodology of the 'Stock God Serenity' in One Article

"Serenity's Bottleneck Investment Methodology: A Deep Dive" This article dissects the "bottleneck point investment" strategy of the pseudonymous investor Serenity, known for exceptional returns (YTD 4502.45%). The core methodology involves identifying a major technological trend (e.g., AI compute expansion), mapping its supply chain, and investing early in the most irreplaceable, supply-constrained upstream component before the market fully values it. The framework is broken down into a five-factor model: 1. **Deterministic Demand**: Anchored in a large, validated trend. 2. **Constrained Supply**: The component must be difficult to replicate or scale quickly. 3. **Low Market Attention**: Opportunities exist where coverage is sparse. 4. **Value Capture**: The company must have pricing power, high margins, and customer lock-in. 5. **Catalyst**: A near-term event to trigger price discovery (earnings, customer ramp, etc.). The article provides illustrative examples like $AXTI (InP substrates for photonics), $RPI (edge hardware for AI agents), and $AAOI/$LITE (components for cloud ASICs). To apply this method, a six-step process is outlined: identify the macro trend, map the supply chain, pinpoint the true bottleneck, gather evidence (client wins, certifications), assess risks ("anti-thesis table"), and size the position according to research depth. Crucially, the article notes significant limitations: risk of overfitting inferences from sparse data, valuation challenges for pre-revenue companies, liquidity/reflexivity risks due to Serenity's own market influence, and survivor bias amplified by a strong AI bull market. The key takeaway is to emulate the rigorous research process—finding the trend, the bottleneck, the evidence—rather than blindly copying specific stock picks, emphasizing the discipline of "walking through the narrow gate."

marsbit05/30 06:45

Deconstructing the Investment Methodology of the 'Stock God Serenity' in One Article

marsbit05/30 06:45

One Article Deconstructs the Investment Methodology of 'Stock God Serenity'

This article deconstructs the "bottleneck point" investment methodology of the renowned investor known as "Serenity" (aleabitoreddit). Characterized by a YTD return of over 4500%, the strategy involves identifying a major, confirmed trend (e.g., AI data center expansion), mapping its supply chain, and then pinpointing a critical, hard-to-replace upstream bottleneck that the market has yet to fully price in. The core framework is a five-factor model: 1) **Certain Demand** from a clear megatrend; 2) **Constrained Supply** with high barriers to entry and slow replication; 3) **Low Market Attention**, where the company is overlooked; 4) **Value Capture** potential through pricing power and market share; and 5) a near-term **Catalyst** to trigger re-evaluation. Case studies include **$AXTI** (InP substrates for photonics), **$RPI** (edge hardware for AI agents), and companies like **$AAOI** and **$LITE** tied to hyperscaler-specific ASIC demand (e.g., Microsoft Maia, Amazon Trainium). The article provides a six-step guide for applying this approach: 1) Identify a validated macro trend; 2) Map the entire supply chain; 3) Find the true bottleneck; 4) Gather concrete evidence (e.g., filings, customer contracts); 5) Perform rigorous risk assessment ("anti-thesis"); 6) Match position size to depth of research. Key limitations are also noted: the risk of narrative overfitting, difficulty in valuing early-stage companies, Serenity's own market-moving influence creating reflexivity, and potential survivorship bias due to the AI bull market. The essence of the method is not to copy picks but to adopt the research process: find the trend, locate the bottleneck, verify with evidence, assess valuation, await a catalyst, and then invest with discipline. The philosophy is summarized as "walking through the narrow gate"—seeking non-consensus, structurally vital points within booming industries before they become widely recognized.

链捕手05/30 06:36

One Article Deconstructs the Investment Methodology of 'Stock God Serenity'

链捕手05/30 06:36

The Truth About Global Payments, Revealed by Airwallex

The article discusses Airwallex's approach to global payments, highlighting the key challenges and different strategic paths in the industry. It begins by addressing common user questions about platform reliability, cryptocurrency payments, and the necessity of Airwallex's "heavy" infrastructure model. The core argument is that while many payment platforms appear similar on the surface—offering features like global acquiring and multi-currency accounts—their underlying capabilities differ drastically. The piece identifies three primary paths for global payment providers: 1. **Bypassing Traditional Infrastructure (Web3/Crypto):** This path promises efficiency through stablecoins and on-chain settlements but faces significant regulatory hurdles and offers little advantage over established players for mainstream use, often serving only niche or non-compliant markets. 2. **Aggregating/Packaging Existing Infrastructure:** The most common route, where companies layer a better user experience over legacy banking and partner networks. While fast to market, this approach does not solve fundamental issues like dependency on intermediaries, correspondent banking risks, and compliance fragility. 3. **Building Proprietary Global Infrastructure:** The path chosen by Airwallex and similar firms. This involves obtaining local licenses, building direct regulatory relationships, establishing local teams, and controlling the compliance and technology stack. This is the most difficult and capital-intensive route but aims to internalize complexity. Airwallex's strategy of "heavy" investment in its own infrastructure is framed not as inefficiency, but as a long-term bet to provide clients with greater stability, cost savings beyond fees, and certainty. The platform's "heaviness" absorbs risk and operational complexity, aiming to deliver a "lighter" experience for business customers. The article concludes that in global payments, while shortcuts enable faster growth, mastering the most difficult aspects—the underlying infrastructure—is what creates durable value for clients and sustainable competitive advantage.

链捕手05/28 16:02

The Truth About Global Payments, Revealed by Airwallex

链捕手05/28 16:02

Interview with Former Goldman Sachs CEO: Crisis, Leadership, AI, and Advice for Young People

Former Goldman Sachs CEO Lloyd Blankfein discusses crisis leadership, risk management, and AI in an interview with a16z's David Haber. Reflecting on guiding Goldman through the financial crisis, he emphasizes building organizational resilience, making decisions under pressure, and preserving culture during growth. He shares his calm reaction during a White House Correspondents' Dinner shooting, illustrating his crisis mindset. Blankfein explains that effective leadership involves both encouraging calculated risk-taking and implementing safeguards. He highlights the value of "mark-to-market" practices and independent valuation as early warning systems. On technology, he notes finance eagerly adopts tech for competitive edges but must manage risks carefully, especially with AI's opaque, automated trading. He advises AI companies to proactively engage with the public before crises arise. For young professionals, he recommends becoming well-rounded individuals by studying history and humanities, as opportunities often lie at the intersection of disciplines. Your reputation and relationships, built over decades, are crucial long-term assets.

marsbit05/27 07:18

Interview with Former Goldman Sachs CEO: Crisis, Leadership, AI, and Advice for Young People

marsbit05/27 07:18

BTC Faces Triple Resistance at $80,000 Milestone, HYPE Hits New Highs Signaling Potential | Invited Analysis

This weekly analysis maintains a structured framework, focusing on Bitcoin (BTC) and HYPE, dissecting their multi-timeframe price action to identify key support and resistance zones and formulate actionable trading plans. The previous week's short position on BTC yielded a 2.78% gain, reinforcing the "signal-driven, disciplined" approach. For Bitcoin, the core scenario revolves around the battle between the 78,500–79,500 USD resistance zone and the 73,500–75,000 USD support area. The daily chart shows BTC within a rising channel; a failure to hold support at the channel's midline could lead to a test of the lower boundary. The 4-hour chart details an 8-segment corrective structure from the 82,850 USD high. Two short-term strategies are proposed: (A) Selling on a failed rally into the 78.5k-79.5k zone, with a stop above 80,600, or (B) Selling a confirmed breakdown below the 73.5k-75k support, with a stop above 76,500. Medium-term positioning remains neutral. For HYPE, the 4-hour chart indicates a five-wave advance from the May 14th low, now showing potential exhaustion and a top warning signal near 65 USD. The core view is to watch for a potential short-term peak formation. The recommended strategy is to avoid chasing the rally and instead look for a long setup upon a pullback to the 47.5–50 USD support zone, provided clear stabilization and model confirmation signals appear. The report concludes with a detailed review of the prior BTC short trade, executed based on model signals and candlestick patterns, and reiterates strict risk management rules, including immediate stop-loss placement and trailing stops to protect profits. All analysis is presented as a personal trading log, not investment advice.

Odaily星球日报05/26 04:34

BTC Faces Triple Resistance at $80,000 Milestone, HYPE Hits New Highs Signaling Potential | Invited Analysis

Odaily星球日报05/26 04:34

Blockchain Capital Partner: The Structure of On-Chain Two-Tier Capital Is Still in the Early Stages of Value Discovery

Spencer Bogart, a general partner at Blockchain Capital, argues that the on-chain economy possesses unique features like programmability, composability, and global distribution, fostering an open and fast-paced innovation ecosystem. However, these very features create challenges for large, fiduciarily-responsible institutional capital, which requires robust risk assessment frameworks often difficult in a permissionless and adversarial environment. The proposed solution is the emergence of a two-tiered capital structure. The first, permissionless layer remains the crucible for innovation, where protocols are built, tested, and hardened with real capital. The second, "institutional" layer consists of chains (L1s, L2s, etc.) that, while based on similar code, incorporate risk-management features like the ability to pause or freeze transactions in extreme scenarios, making them suitable for large-scale institutional deployment. The synergy between these layers is key. Protocols proven resilient in the open, permissionless environment can then scale to the institutional layer, accessing deeper capital pools. This creates a lifecycle: build and launch permissionlessly, test and prove robustness publicly, then expand to an institutional-grade chain for scaled adoption. This architecture allows the open, experimental side to continue driving innovation with crypto-native capital, while the institutional layer provides the liquidity, stability, and trust required for mainstream adoption. The major challenge identified is the "cold start" problem: aligning where institutional capital prefers to go with where the most proven applications and network effects currently reside. How this dynamic resolves—whether through protocol migration, new protocol builds, or institutional adaptation—will be crucial to watch. Overall, this evolving structure aims to combine the strengths of open innovation and institutional depth within a shared on-chain ecosystem.

链捕手05/22 06:13

Blockchain Capital Partner: The Structure of On-Chain Two-Tier Capital Is Still in the Early Stages of Value Discovery

链捕手05/22 06:13

Who is Selling, Who is Holding, Who is Still Buying? The Divergence of U.S. Old Money's Crypto ETF Holdings

"American Institutional Crypto ETF Holdings Show Divergence in Q1 2026. Amidst a quarter of market pullback, major institutional 13F filings reveal distinct strategies towards crypto ETFs. Key sell-offs/trimming: Harvard Management cut its iShares Bitcoin Trust (IBIT) holdings by ~43% and fully exited its iShares Ethereum Trust (ETHA) position, reallocating some funds toward AI/tech stocks. Goldman Sachs reduced its overall crypto ETF exposure, notably clearing its XRP and Solana ETF holdings while adding to selected crypto-related equities like Circle and Galaxy Digital. Hedge funds Millennium Management and Capula Management also significantly reduced or fully exited major Bitcoin and Ethereum ETF positions. Holders maintaining positions: Brown University kept its IBIT stake unchanged, demonstrating a long-term allocation approach. Dartmouth College maintained its core Bitcoin ETF holding while shifting some Ethereum exposure to a staking ETF and initiating a position in a Bitwise Solana Staking ETF. Strategic buyers increasing exposure: Sovereign wealth fund Mubadala increased its IBIT holdings by ~16%. JPMorgan significantly boosted its IBIT stake by 174%, while Wells Fargo raised its Ethereum ETF allocations. Market maker Jane Street rebalanced, cutting Bitcoin ETF holdings but adding ~$82 million in Ethereum ETF exposure. The filings indicate institutions are actively sorting crypto assets by perceived risk and liquidity, with Bitcoin often treated as a 'core' holding, Ethereum facing mixed treatment, and altcoins like Solana and XRP being the first to be cut or used for tactical 'elastic' allocations by some. It's crucial to note that 13F data is a lagging snapshot (as of March 31) and doesn't reveal entry costs or potential off-balance-sheet hedging strategies."

marsbit05/22 02:59

Who is Selling, Who is Holding, Who is Still Buying? The Divergence of U.S. Old Money's Crypto ETF Holdings

marsbit05/22 02:59

147 Trillion vs 70 Billion: The Rise of On-Chain 'Risk Managers' and the Potential Dawn of a New Era in DeFi Asset Management

"147 Trillion vs 70 Billion: The Rise of On-Chain 'Risk Managers' and the Potential Dawn of a New Era in DeFi Asset Management" Key Points: The role of professional asset managers is emerging in DeFi, ending the era where protocols and governance dictated everything. While early DeFi protocols like Aave and Compound bundled risk management within their code, innovations like Morpho have separated infrastructure from risk judgment. This allows specialized "Risk Managers" to operate independent lending vaults, acting as on-chain asset managers. The market, though early with ~$7B in assets under management (AUM), is rapidly consolidating around top performers like SteakhouseFi (RWA focus), SentoraHQ (AI-driven models), and Gauntlet (crisis management). This modular structure mirrors TradFi's division of labor: distributors (e.g., exchanges) source capital, Risk Managers design strategies and set standards, and underlying protocols handle custody and execution. For traditional asset managers, this familiar structure presents clear entry paths: 1) **Distribution**: Partnering with Risk Managers as a backend service. 2) **Supply**: Bringing real-world assets (RWA) on-chain as collateral. 3) **Operation**: Becoming a Risk Manager themselves (e.g., Bitwise). The core competency required is shifting from coding to traditional risk underwriting and financial expertise—areas where established institutions hold a natural advantage. While the current DeFi market (~$80B) is minuscule compared to global asset management (~$147T), it represents a significant growth runway. The teams that build the trusted standards and rails for risk-managed capital now are poised to define the market's future as institutional capital seeks secure on-ramps.

marsbit05/21 01:24

147 Trillion vs 70 Billion: The Rise of On-Chain 'Risk Managers' and the Potential Dawn of a New Era in DeFi Asset Management

marsbit05/21 01:24

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