# Pricing Power Related Articles

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Changxin Rejects Apple's Price Pressure, Prices Not Lower Than Samsung and SK Hynix, Apple Loses Pricing Power

Apple recently attempted to negotiate lower-priced DRAM procurement deals with China's CXMT (ChangXin Memory Technologies) compared to its agreements with Samsung and SK Hynix but was rejected. CXMT stated its prices would not be lower, and could even be higher, than those of the South Korean suppliers. This refusal is attributed to CXMT's production capacity being largely secured by long-term contracts with major domestic clients like Huawei, Xiaomi, OPPO, Vivo, and Chinese internet giants. Consequently, CXMT feels no pressure to meet Apple's stringent terms. The backdrop is a significant surge in memory prices driven by the AI boom. As Samsung and SK Hynix shift more production capacity towards high-margin High Bandwidth Memory (HBM) for AI servers, the supply of conventional DRAM has tightened, causing prices to skyrocket. This has drastically increased the bill-of-materials cost for devices like iPhones, pressuring Apple's profits. Apple's traditional strategy of leveraging multiple suppliers for price competition has weakened, as memory makers prioritize more profitable AI-related orders. CXMT's confidence stems from achieving technological parity. Its DDR5 and LPDDR5X products have reached mass-production yields above 90%, closely matching Samsung's performance. With technical gaps closed, CXMT no longer competes solely on low prices. Furthermore, Chinese companies are wary of the risks associated with over-reliance on Apple's supply chain, citing cases like OFILM and Wingtech, which suffered severe losses after being removed from or impacted by US sanctions. This event signals a shift in the semiconductor industry's power dynamics. The AI-driven demand has transformed the market from buyer-centric to supplier-centric, where control over scarce, advanced production capacity grants pricing power. For Chinese semiconductor firms, the episode marks a transition from being low-cost alternatives to becoming equal suppliers with their own pricing authority, backed by domestic demand and technological advancement. Apple's loss of leverage with a mainland supplier underscores this changing era.

marsbit23h ago

Changxin Rejects Apple's Price Pressure, Prices Not Lower Than Samsung and SK Hynix, Apple Loses Pricing Power

marsbit23h ago

On L1 Value Capture from Two Solana Proposals

The article, "Discussing L1 Value Capture Through Two Solana Proposals," by Max Resnick, explores how Layer 1 (L1) blockchain tokens derive their fundamental value, drawing parallels to traditional asset pricing theory. Resnick argues that L1 token value, like stock value, stems from claims on future income streams for holders, not merely from network activity or technological promise. This value is captured when fees are either burned (economically akin to a buyback) or distributed to stakers (akin to dividends). Inflationary staking rewards, by contrast, redistribute value among holders rather than creating it. The core challenge is the quality and defensibility of fee-based revenue. High-quality fees come from sustainable, recurring demand for the network's economic utility (e.g., long-term financial activity), not from transient speculation (e.g., meme coins, airdrops). The strength of a blockchain's network effects—liquidity, applications, users—can make its revenue more defensible and grant it greater pricing power than often assumed. The article proposes a foundational valuation framework for L1s, separating revenue (fees captured for token holders), costs, and total token supply. A key accounting principle is that inflationary rewards should not be counted as a cost unless the newly minted tokens are symmetrically counted as a value input; otherwise, it misrepresents profitability. Finally, Resnick discusses the economics of increasing protocol fees to boost revenue. Since revenue equals price times quantity, the net effect depends on demand elasticity. Research on Ethereum suggests transaction demand is somewhat elastic; a fee increase reduces volume. A uniform fee is a blunt instrument, as different transactions (e.g., small transfers vs. large settlements) have vastly different abilities to pay. The article suggests that transaction-value-based fees, potentially implemented via token programs, could be a more efficient way to capture value from high-willingness-to-pay activities. The discussion is framed around ongoing Solana proposals (SIMD-550, SIMD-553) but focuses on the universal principles of L1 value accrual.

marsbitYesterday 07:06

On L1 Value Capture from Two Solana Proposals

marsbitYesterday 07:06

Research Report Analysis: Morgan Stanley Details SanDisk SNDK, The Truth About Cloud Data Center Pricing Power and AI Inference Benefits

Morgan Stanley raised its price target for SanDisk (SNDK) from $1100 to $1750 on June 22, maintaining an Overweight rating. The upgrade is driven by AI inference demand reshaping the NAND market, particularly for KV Cache and context window storage in cloud data centers. These cloud clients exhibit price inelasticity and sign long-term contracts, granting SanDisk significant pricing power. SanDisk's New Business Model (NBM) agreements, covering over one-third of FY27 bit shipments with 3-5 year terms and fixed price/price collar structures, are crucial. They are projected to sustain gross margins around 80% even at floor prices, providing a buffer against cyclical downturns. Morgan Stanley forecasts gross margins to surge from 30.3% in FY25 to 86.7% in FY27e. With NAND supply expected to remain tight into 2026/2027 and cloud/data centers becoming the largest end-market, SanDisk holds supply-side pricing power. The company targets 15-19% bit growth via technology transitions, not capacity expansion. Revenue is projected to grow ~6.6x from FY25 to FY27, with EPS rising from $2.74 to $14.73, driven by high-margin cloud business. Key upside catalysts include faster enterprise SSD adoption and edge AI growth. Downside risks involve slower industry growth, competitor capex increases, market share loss, and competition from Chinese players like YMTC. The investment thesis rests on AI-driven structural demand, NBM's margin protection, and sustained supply tightness. The $1750 target implies ~28x FY27e P/E.

marsbit06/23 12:04

Research Report Analysis: Morgan Stanley Details SanDisk SNDK, The Truth About Cloud Data Center Pricing Power and AI Inference Benefits

marsbit06/23 12:04

A 134% Surge, 75 P/E Ratio: Why Is the Market Paying Up for Murata's 'Zero Growth'?

Murata Manufacturing, the world's largest passive components maker, saw its stock price surge 134% over the past year and hit a record high on May 28th, despite reporting nearly zero growth in operating profit for its latest fiscal year. This has pushed its valuation to a P/E ratio of approximately 75x. The disconnect is driven by a fundamental market re-rating. The catalyst was a late-May meeting where management upgraded the AI investment cycle outlook to "lasting until around 2030" and noted that demand for its components is roughly double its supply capacity, with customers prioritizing securing volume over price. While Murata's revenue grew only 5.0% and operating profit stagnated at ¥281.8 billion for the fiscal year ending March 2026, its guidance for the current fiscal year projects a 34.8% jump in operating profit to ¥380 billion. This sharp growth is underpinned by expectations that its AI/data center-related revenue will nearly double from ¥170 billion to ¥325 billion, becoming a key pillar of its business. Analysts highlight that this growth stems not from broad price hikes but from a shift towards higher-value, cutting-edge MLCCs for AI servers, where Murata holds over 70% market share. The market is now pricing Murata not as a cyclical component maker but as a critical "AI pick-and-shovel" supplier with structural pricing power. However, the high valuation also carries risk if future AI demand or quarterly guidance falls short of the elevated expectations.

marsbit06/01 08:43

A 134% Surge, 75 P/E Ratio: Why Is the Market Paying Up for Murata's 'Zero Growth'?

marsbit06/01 08:43

Wall Street Giants Vie for GPU Futures, Crypto Market Already in Early Skirmish

Wall Street giants CME and ICE are racing to launch GPU futures, marking a pivotal shift as computing power transforms from a critical IT resource into a tradable financial asset. In mid-May, both exchanges announced plans for futures contracts tied to GPU compute pricing indices, aiming to establish a benchmark and provide hedging tools for the volatile, trillion-dollar AI compute market. ICE partnered with data provider Ornn for a broad index covering enterprise and consumer GPUs, while CME teamed with Silicon Data to focus on an H100 leasing index with cash settlement. This push for financialization addresses a key industry pain point: the lack of risk management tools in a market dominated by a few cloud providers, where prices are opaque and highly unstable. Proponents argue futures will help large cloud operators and AI labs lock in costs and manage investment risk. However, challenges remain, including the intangible nature of compute, high market concentration, and the potential for leveraged speculation to exacerbate price swings and resource inequality. Notably, the crypto market has moved faster. Platforms like Architect Financial have already launched perpetual contracts tied to compute indices, leveraging DeFi's agility to create a parallel, global market. As Wall Street awaits regulatory approval, the race to define and control the pricing of "21st-century oil" is accelerating both in traditional and decentralized finance.

marsbit05/22 07:42

Wall Street Giants Vie for GPU Futures, Crypto Market Already in Early Skirmish