# Hedging Articoli collegati

Il Centro Notizie HTX fornisce gli articoli più recenti e le analisi più approfondite su "Hedging", coprendo tendenze di mercato, aggiornamenti sui progetti, sviluppi tecnologici e politiche normative nel settore crypto.

Bitcoin Options Traders Hedge For More Downside As Deribit Warns Of Market Weakness

Bitcoin options traders are adopting a defensive stance amid market weakness, according to a Deribit Insights analysis. Key indicators show active hedging against further downside, including net put buying and call selling in BTC options, alongside a negative volatility risk premium and bearish short-dated skew. The report warns that a failure of Bitcoin's current support near $60,000 could lead to a test of $50,000. Ethereum has also seen elevated risk, with realized volatility spiking and a critical support level at $1,520. A break below could target $1,200. While not guaranteeing further declines, the options market data reflects heightened near-term caution and risk management by traders as they monitor these key support levels.

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Bitcoin Options Traders Hedge For More Downside As Deribit Warns Of Market Weakness

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BIT Weekly Market Outlook: Highs Halved, Panic Doubled. The $60,000 Line is the Sole Lifeline

BIT Market Weekly: Halving from the Peak, Doubling Panic. $60K is the Sole Lifeline. The crypto market faces intense pressure from multiple fronts. MicroStrategy's symbolic sale of 32 BTC, its first since December 2022, shattered its "only accumulate" mantra, triggering panic and significant whale selling (~25,000 BTC). This pushed Bitcoin below MicroStrategy's average cost basis, causing unrealized losses. Bearish momentum intensified as spot Bitcoin ETFs saw a record 13-day net outflow streak, with $4.4 billion exiting, led by BlackRock's IBIT. Concurrently, macro risks mounted: sticky inflation dampened rate cut hopes, Mt.Gox wallet movements stoked sell-off fears, and renewed Middle East tensions added uncertainty. Derivatives data reveals a market at a critical juncture. Short-term options show extreme panic (negative Skew), but forward-term Skew has turned positive, signaling institutional expectations for a recovery in 3-6 months. Most notably, institutional activity shifted from defensive hedging to opportunistic bottom-fishing. They are selling puts and buying calls around the $60,000 level, effectively using options to establish controlled long positions. The $60,000 level is now the core battleground, hosting the largest concentration of put options open interest. It represents a binary outcome for the market. Holding above it could provide a base for stabilization, while a break below risks a swift decline toward the next major support at $55,000. Given the high uncertainty ahead of key CPI data and the FOMC meeting, the primary recommendation is risk management via Collar strategies to cap downside. For accumulation, structured products like DCPs or Bullish Seagulls can be deployed in batches near $60,000, mimicking institutional "selling puts to accumulate" logic. While volatility selling appears attractive as Implied Volatility shows topping signals, it's advised only with defined-risk spreads until $60,000 support is confirmed. Current levels are unsuitable for large-scale profit-taking; holding core positions with hedges is preferred.

marsbit2 giorni fa 07:26

BIT Weekly Market Outlook: Highs Halved, Panic Doubled. The $60,000 Line is the Sole Lifeline

marsbit2 giorni fa 07:26

From Madison Square Garden to Kalshi: Prediction Markets Break into the NBA Finals

From Madison Square Garden to Kalshi: Prediction Markets Break into the NBA Finals Prediction markets are playing a significant role in the 2026 NBA Finals, particularly around the New York Knicks' unexpected 2-0 series lead. Platforms like Kalshi and Polymarket have seen massive trading volumes, exceeding hundreds of millions of dollars on championship and related markets. Their influence extends beyond online trading. Kalshi's official partnership with Madison Square Garden has given it prominent physical branding at the arena. Furthermore, local businesses like The Jeffrey bar are using prediction market contracts to hedge the risk of game-result-based promotions, turning potential losses into manageable costs—a concept similar to the famous "Mattress Mack" strategy from traditional sports betting. These markets differentiate themselves by offering a wider, more entertainment-focused range of "event contracts" beyond typical game outcomes, such as predicting celebrity attendance. They also have broader accessibility across the U.S. compared to age- and location-restricted traditional sportsbooks. However, their rapid integration into sports raises regulatory and ethical questions. The NBA is cautiously engaging, discussing integrity frameworks with regulators like the CFTC. While the league permits minor investments like Giannis Antetokounmpo's stake in Kalshi, it advocates for strict rules to prevent insider trading. Many fans express concern on platforms like Reddit, fearing that the close ties between prediction markets, the league, and players could compromise the game's integrity. The NBA Finals has thus become a high-stakes testing ground, showcasing prediction markets' commercial potential while challenging traditional boundaries between financial trading, entertainment, and gambling.

marsbit06/06 23:30

From Madison Square Garden to Kalshi: Prediction Markets Break into the NBA Finals

marsbit06/06 23:30

For Hedging, Buy Gold and Oil; For Explosive Growth, Buy AI; Bitcoin, the 'Outdated' Asset, Enters a Bear Market

Bitcoin’s price has recently fallen sharply, hitting a two-month low near $66,000, with Ethereum also dropping to a three-month low. While surface explanations point to ETF outflows, geopolitical tensions, and corporate selling, a deeper issue is emerging: Bitcoin is losing a crucial asset competition. For years, Bitcoin thrived in a low-rate environment where investors sought alternatives amid inflation fears and dissatisfaction with traditional options. Now, the market landscape has shifted, leaving Bitcoin stuck in an "awkward middle ground," facing challenges on three fronts: 1. **As an inflation hedge, gold is winning.** Investors worried about persistent inflation are turning to tangible assets like gold, energy stocks, and commodity producers, which offer more direct pricing power and physical backing. 2. **For growth exposure, AI is winning.** Those seeking high growth now favor AI-related companies with actual revenues and profits, an area where Bitcoin's lack of cash flow puts it at a disadvantage. 3. **Within crypto, infrastructure and stablecoins are winning.** Even investors wanting crypto exposure have alternatives like exchanges, stablecoin issuers, and tokenization firms, whose performance is directly tied to real-world adoption and offers clearer operational leverage. The recent market reaction to inflation warnings highlights this shift. Instead of boosting Bitcoin as "digital gold," such news now drives flows toward traditional inflation-sensitive assets. Therefore, recent events like ETF outflows and corporate selling are seen not as causes, but as symptoms of this new reality. Capital has more compelling options, and investors are becoming more selective. The emerging bear case for Bitcoin is no longer about it being a fraud or failed technology, but rather that **scarcity alone is no longer enough**. It is no longer seen as the best hedge, the best growth asset, or the only crypto play.

marsbit06/03 02:19

For Hedging, Buy Gold and Oil; For Explosive Growth, Buy AI; Bitcoin, the 'Outdated' Asset, Enters a Bear Market

marsbit06/03 02:19

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.

marsbit06/01 09:45

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

marsbit06/01 09:45

Investment Philosophy of Gavin Baker, an Early Nvidia Investor: Long AI Infrastructure Bottlenecks, Short Overall Market Risk

Gavin Baker, an early investor in Nvidia and founder of Atreides Management, outlines his investment philosophy: going long on AI infrastructure bottlenecks while hedging against broader market risk. He argues AI is not a bubble but a supercycle driven by constraints in power, wafers (semiconductors), and compute efficiency (tokens per watt). True alpha, he believes, lies not in application-layer companies like OpenAI but in "picks and shovels" providers—companies solving physical bottlenecks in GPU connectivity (e.g., Astera Labs), memory (Micron), inference chips (Cerebras, Positron), advanced manufacturing (TSMC, ASML), and energy supply. His portfolio reflects this barbell strategy: concentrated bets on key infrastructure players alongside a significant put position on the QQQ ETF to hedge overall market downside. Baker contends this cycle differs from the dot-com bubble because demand is fueled by the strong balance sheets of hyperscalers (Google, Meta, Amazon, Microsoft), not debt, and physical supply constraints (e.g., chip manufacturing capacity) prevent runaway overinvestment. He highlights the growing importance of inference (vs. pre-training), vertical/small language models, sovereign infrastructure deployment speed, and the convergence of energy and space (e.g., orbital compute). His long-term view is that performance-per-watt and token cost reduction will dictate winners as AI scaling hits fundamental physical limits.

marsbit05/30 03:23

Investment Philosophy of Gavin Baker, an Early Nvidia Investor: Long AI Infrastructure Bottlenecks, Short Overall Market Risk

marsbit05/30 03:23

I Tested with $10,000: Zero Wear, 8% APY, and Earn Points (Full Tutorial + Screenshots Included)

**Title:** My $10,000 Real-World Test: Zero Wear-and-Tear, ~8% APY, Plus Earning Points (Full Guide + Screenshots Included) **Summary:** This article details a personal experiment with $10,000 on the StandX platform to verify its advertised ~8% APY for its stablecoin, DUSD, while earning trading points. The author created two accounts, each depositing $5,000 worth of DUSD, and used StandX's unique "Block Trade" feature to open perfectly offsetting long and short BTC positions (2x leverage each). This neutralized directional market risk. **Key Results (Over 8 Days):** * **Total Profit:** $16.91 (~7.8% annualized). * **Zero Net Directional P&L:** BTC price movements canceled out. * **Zero Wear-and-Tear:** No losses from fees, slippage, or gas from frequent trading. * **Points Earned:** 380+ trading points. **Source of the ~8.46% APY:** The yield is composed of three layers, all paid in DUSD (real USD value, not governance tokens): 1. **DUSD Base (~1.27%):** Derived from funding rates (similar to Ethena's USDe). 2. **SIP-2 Position Boost (~2.27%):** A protocol revenue-sharing mechanism. Users providing liquidity (via open positions) earn a share of platform trading fees. Leverage acts as a multiplier on this yield. 3. **SIP-3 Universal Fee Share (~4.92%):** A portion of all platform trading fees is distributed to *every* DUSD holder, regardless of whether they trade. **Sustainability Claim:** The author argues this yield is more sustainable than pure funding-rate models (e.g., Ethena) because over 7% of it comes from transaction fees (SIP-2 + SIP-3), which are less dependent on market cycles. **Step-by-Step Strategy:** A concise 3-step guide is provided for replicating the zero-risk strategy using two wallets and StandX's Block Trade to create matched long/short positions. **Risk Disclosures:** The article notes standard DeFi risks: smart contract vulnerability and yield fluctuation (Base yield varies with funding rates; SIP-2/3 yields depend on platform trading volume). **Author's Note:** The author discloses their role in Growth at StandX. The piece is presented as personal testing and analysis, not investment advice.

链捕手05/22 09:41

I Tested with $10,000: Zero Wear, 8% APY, and Earn Points (Full Tutorial + Screenshots Included)

链捕手05/22 09:41

Base Native Leveraged Prediction Market OmenX Officially Launches on Mainnet

Base-native leveraged prediction market platform OmenX has officially launched on mainnet. It currently supports up to 5x leverage, with plans to increase to 10x based on platform liquidity and market conditions. Unlike traditional prediction markets where users fully collateralize YES/NO positions and wait for settlement, OmenX aims to create a trading platform-like experience. Users can open leveraged positions on event outcomes, and actively trade, adjust, or hedge these positions before the event concludes for greater capital efficiency. Alongside the mainnet launch, OmenX introduced a "Hedge-to-Earn" campaign targeting existing users of other prediction markets (initially Polymarket). This initiative allows users to claim incentives or hedging benefits on OmenX based on their existing positions, aiming to introduce them to leveraged trading and active risk management. OmenX positions itself as a derivatives trading platform for prediction market assets. The team believes that as platforms like Polymarket mainstream prediction markets, event outcomes are becoming a new tradable asset class. The next phase of demand will focus on leverage, liquidity, and advanced trading tools. Post-launch, OmenX plans to expand supported market types, optimize liquidity, and develop APIs and additional trading tools. The team is also in discussions with investors and partners to secure resources for further development.

链捕手05/19 13:35

Base Native Leveraged Prediction Market OmenX Officially Launches on Mainnet

链捕手05/19 13:35

When Computing Power Becomes Commoditized, How Long Until a GPU Futures Market Emerges?

"When Will GPU Futures Arrive? A Framework for Assessing Compute as a Commodity" The article explores the potential for a robust futures market for compute power (GPUs), arguing that such a market is not yet mature but may emerge. It analyzes the landscape using a five-part framework developed for new commodity futures markets. The analysis scores the current state: * **Fragmented Supply (Red)**: Supply is highly concentrated among hyperscale cloud providers (AWS, Azure, GCP, Oracle), limiting the need for price discovery. * **Price Volatility (Green)**: GPU pricing is already highly volatile due to uncertain supply and surging demand. * **Physical Settlement Infrastructure (Green)**: Early infrastructure exists via OTC brokers and price indices (e.g., Ornn, Silicon Data) standardizing contracts. * **Standardized Unit (Red)**: A lack of standardized, tradable units hinders markets; a GPU instance hour varies by region, configuration, and contract terms. * **Lack of Alternatives (Yellow)**: Large players hedge internally via vertical integration, while smaller players bear spot market risk. Overall, the market shows promise (volatility, early infrastructure) but lacks the fragmented supply and standardization needed for large-scale futures trading. Most activity remains OTC. Key open questions and hypotheses: 1. Supply is expected to fragment moderately in 1-2 years, driven by new cloud providers, cheap power locations, and demand from non-frontier labs and AI startups using open-source models. 2. Standardization is most likely to emerge around inference workloads (forecast to be >65% of AI compute demand by 2029), which have simpler, more homogeneous hardware needs than training. Widespread adoption of open-source model weights could accelerate this by democratizing inference and creating demand for optimized, standardized infrastructure. 3. The primary traded unit will likely be the **"chip instance hour"** (akin to electricity, traded regionally), not the physical chip or the downstream AI output (tokens).

marsbit05/18 09:09

When Computing Power Becomes Commoditized, How Long Until a GPU Futures Market Emerges?

marsbit05/18 09:09

When Computing Power Becomes Commoditized, How Long Until a GPU Futures Market?

When Compute is Commoditized: How Far Away is a GPU Futures Market? The article explores the potential emergence of a futures market for computing power ("compute"), akin to markets for commodities like oil or electricity. It uses a five-dimension framework to assess the market's maturity for sustaining robust futures trading. **Current Market Assessment (Scorecard):** * **Supply Fragmentation:** 🔴 **Red.** Supply is highly concentrated, dominated by a few hyperscale cloud providers. * **Price Volatility:** 🟢 **Green.** GPU pricing is already highly volatile. * **Physical Settlement Infrastructure:** 🟢 **Green.** Early infrastructure exists at the OTC/broker level. * **Standardization:** 🔴 **Red.** Compute lacks a standardized, tradable unit (e.g., an H100 hour is not uniform). * **Lack of Substitutes:** 🟡 **Yellow.** Vertically integrated players can hedge internally, while others are forced to be long. **Conclusion:** The overall scorecard suggests a robust futures market is premature. The market has volatility and early settlement infrastructure but lacks the necessary supply fragmentation and standardization for large-scale price discovery. Most activity remains OTC. **Key Unanswered Questions & Hypotheses:** The article posits that the market could evolve in the next 1-2 years: 1. **Supply:** May become *moderately more fragmented* due to new cloud providers, cheaper power locations, and demand from long-tail users (e.g., startups running open-source model inference). 2. **Standardization:** Could emerge from the growing **inference** workload (expected to be >65% of AI compute demand by 2029), which has more homogeneous hardware requirements than custom training workloads. Widespread adoption of **open-source model weights** is seen as a key catalyst for democratizing inference and driving infrastructure standardization. 3. **Traded Unit:** The most viable layer for trading is likely the **"chip-instance-hour"** (powered, usable compute time), traded similarly to electricity in regional contracts with spot/futures overlays. Trading at the upstream "chip" layer is unlikely due to supply concentration, while the downstream "token" layer faces challenges due to lack of uniformity across AI models.

链捕手05/18 09:04

When Computing Power Becomes Commoditized, How Long Until a GPU Futures Market?

链捕手05/18 09:04

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