Robinhood RVI Fund Drops 16% After Missing $1B IPO Target

TheNewsCryptoPublicado em 2026-03-07Última atualização em 2026-03-07

Resumo

Robinhood's RVI Fund (ticker: RVI) experienced a 16% decline on its first day of trading on the New York Stock Exchange on March 6. The drop followed the fund's failure to meet its $1 billion initial public offering (IPO) target, falling short by over $300 million. The IPO was priced at $25 per share, but the stock opened at $22 and closed around $21. The closed-end fund, which provides retail investors access to stakes in major private companies like Databricks, Ramp, and Revolut, launched during a period of market volatility. Broader U.S. stock averages faced a weekly decline amid concerns over prolonged U.S.-Iran tensions. CEO Vlad Tenev stated the fund aims to open a part of the capital markets traditionally inaccessible to retail investors. The offering was initially planned for February 26 but was delayed by one week.

The RVI stock of Robinhood has slipped by around 16% in the initial period of its trading on March 6. This came after the initiative wasn’t able to meet its $1 billion goal in its IPO raise plan.

Venture Fund I, of the investment company, slipped 16% in its public market launch on the New York Stock Exchange on March 6 after its IPO wasn’t successful in meeting its IPO target.

The fund trading under the symbol “RVI” offers access to significant private companies. The chief executive officer of Robinhood, Vlad Tenev, gave an interview to CNBC’s Squawk Box in which he stated that RVI stock looks to permit access to a part of the capital markets that has significantly been closed to retail investors.

Investors can trade the close-end fund, which is structured similar to an investment firm. Although this went public at a difficult time for the markets. The prominent U.S. stock averages are on the verge of a weekly decline.

This comes amid selling of shares because of fears of the U.S.-Iran conflict possibly lasting longer than anticipated. The RVI stock of Robinhood priced its initial public offering at $25 a share.

Last Month’s Plan

The opening price of stock was $22 a share and hovered around $21 a share at the time of closing. The fund registered on the stock exchange after missing its aim by over $300 million.

Robinhood Markets also reported last month that it has plans to captivate $1 billion from its initial public offering of the closed-end fund. The starting date of the trading was set to be February 26, but the listing was delayed by a week.

The RVI stock of Robinhood also has stakes in prominent private companies. This adds Databricks, Ramp, and Revolut. The crypto exchange sold 12.6 million shares, fewer than the firm had in the beginning sought from its IPO.

Highlighted Crypto News Today:

Binance, CZ Secure Legal Win as Court Rejects Claims Tied to 64 Terror Attacks

TagsIPORobinhoodStock

Perguntas relacionadas

QWhat was the percentage drop in Robinhood RVI Fund's stock on its first day of trading?

AThe Robinhood RVI Fund stock dropped by 16% on its first day of trading.

QWhat was the target amount for the Robinhood RVI Fund's IPO and how much did it actually raise?

AThe target for the IPO was $1 billion, but it missed this goal by over $300 million, raising less than $700 million.

QOn which stock exchange did the Robinhood RVI Fund make its public market debut?

AThe Robinhood RVI Fund made its public market debut on the New York Stock Exchange.

QWhat is the stated purpose of the RVI stock according to Robinhood CEO Vlad Tenev?

AAccording to CEO Vlad Tenev, the RVI stock is designed to provide retail investors with access to a part of the capital markets that has been largely closed off to them, specifically investments in significant private companies.

QWhat was the opening share price and the closing share price for RVI on its first trading day?

AThe opening share price was $22, and it hovered around $21 at the time of closing.

Leituras Relacionadas

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbitHá 4m

Token Inefficient, Economy Tokenless

marsbitHá 4m

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

In 2026, a historic shift occurred in AI as major cloud providers' inference spending surpassed training spending for the first time, signaling a move from "building large models" to "using large models." This shifts the core challenge from computing power to the "memory wall"—the bottleneck of data movement (model weights, activations, KV Cache) between external DRAM and processors, where energy and latency from data transfer far exceed computation itself. Companies like Nvidia face GPU idle time due to bandwidth limits. In contrast, Cerebras Systems adopts a radical "wafer-scale" approach with its Wafer-Scale Engine (WSE). Instead of cutting a silicon wafer into many chips, Cerebras uses almost the entire wafer as one massive chip (WSE-3). This design provides 44GB of on-chip SRAM, delivering memory bandwidth thousands of times higher than traditional HBM (e.g., 21 PB/s vs. Nvidia B200). For LLM inference, weights are streamed layer-by-layer from external MemoryX storage to the chip, avoiding HBM bottlenecks. This results in token generation speeds 1.5–5 times faster than Nvidia's B200 in some models and significant advantages in first-token latency and long-context tasks. Additionally, Cerebras's architecture offers much lower interconnect power consumption (0.15 pJ/bit vs. GPU's ~10 pJ/bit). However, Cerebras faces challenges: SRAM scaling has slowed with advanced nodes, limiting future capacity gains; the chip requires specialized liquid cooling and custom software stacks; and its external I/O bandwidth (150 GB/s) is low compared to NVLink, hindering multi-system scaling for very large models. Competition is intensifying. Major players are pursuing three paths: 1) Developing proprietary inference ASICs (e.g., Google TPU, Microsoft Maia), 2) Leveraging advanced packaging (e.g., TSMC's SoW) to democratize wafer-scale-like integration, potentially eroding Cerebras's process advantage within a few years, and 3) Exploring optical interconnects for ultimate bandwidth. Commercially, Cerebras is transitioning from a hardware vendor to a service provider, facing the immense challenge of building high-power, specialized data centers to meet large contracts (e.g., 250MW/year from 2026–2028). In conclusion, the AI inference era presents a fundamental architectural trade-off. Cerebras opts for extreme physical optimization for low-latency, single-task performance, while Nvidia prioritizes versatility and massive cluster throughput. The path forward remains uncertain, with technology and business models still evolving in the race toward advanced AI.

marsbitHá 10m

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

marsbitHá 10m

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

**Title: Has Bitcoin's Rebound Ended, Entering the Late Bear Market Phase?** **Summary:** Bitcoin's price has declined by 13% this week, signaling a potential return to late-stage bear market conditions. The price fell to around $67k, positioned between the Realized Price and Realized Cap Weighted Average. For the first time since early 2022, the Short-Term Holder cost basis has dropped below this key average, confirming a hallmark of late-cycle bear markets. Profitability metrics have collapsed sharply. The 7-day average of the Realized Profit/Loss ratio plummeted from a local high of 3.16 to 0.29, mirroring the February panic sell-off. Critically, the 90-day average never breached the threshold of 2, indicating the recent rally to $82k was a bear market bounce, not a structural shift. Realized losses surged to $1.35 billion daily, with $770 million coming from Long-Term Holders selling at a loss. This accelerating redistribution of supply from weak to strong hands is a necessary but ongoing process for a market bottom. The rally stalled almost precisely at the aggregate cost basis (~$83k) of US spot Bitcoin ETF investors, turning that level into strong resistance and leaving the average ETF holder underwater again. Spot market flows have turned decisively negative, showing sellers are dominating order books despite the price drop. While a significant futures long liquidation event cleared over $400 million in leverage, providing a potential reset, sustained spot demand is yet to materialize. Options markets continue to price in higher future volatility (Implied Volatility) than recent price action (Realized Volatility) has shown, with a persistent skew towards put options, indicating ongoing demand for downside protection. In conclusion, multiple metrics point to a fragile market structure. Resistance at the ETF cost basis, accelerating realized losses, dominant spot selling, and cautious options pricing all suggest the bear market trend persists. A sustainable recovery likely requires a resurgence of spot demand, ETF holders returning to profit, and a clear reduction in selling pressure.

marsbitHá 10m

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

marsbitHá 10m

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

In today's TechFlow Intelligence Briefing, several major tech stories highlight a growing theme of trust and credibility gaps across AI, crypto, and finance. AI company Anthropic has publicly called for a global pause in AI development, citing risks from Claude's "recursive self-improvement." Ironically, this coincides with reports the company is preparing for a massive IPO targeting a near $1 trillion valuation. This perceived hypocrisy, coupled with widespread user complaints about Claude's declining performance, is sparking debate over whether the safety warning is genuine or a competitive tactic. Meanwhile, in a substantive security move, Anthropic open-sourced a framework for AI-powered vulnerability discovery. In the crypto market, Bitcoin's price drop below $61,000 triggered over $1.16 billion in liquidations, flipping the market into a state where more BTC is held at a loss than at a profit, a historical bearish signal. On the corporate front, SpaceX's highly anticipated IPO is generating immense Wall Street excitement, with Goldman Sachs projecting 100x revenue growth by 2030. However, the S&P 500 has refused to fast-track the company's inclusion post-IPO, potentially limiting immediate institutional demand. Separately, ByteDance's AI app Doubao lost over 6 million monthly active users after introducing a subscription model, highlighting the challenges of AI monetization. Other notable developments include Nvidia certifying HBM4 memory from Samsung, SK Hynix, and Micron; Cloudflare's acquisition of front-end tooling company VoidZero; and its CEO warning that bot traffic now exceeds human traffic online. The underlying narrative connects these events: a trust crisis. From AI firms' contradictory actions and crypto volatility to the clash between SpaceX's hyped narrative and institutional rules, a pattern is emerging where stated intentions and actual practices are increasingly misaligned.

marsbitHá 26m

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

marsbitHá 26m

Dalio Warns: AI Boom Shows Signs of a Bubble, Day of Reckoning Will Be the Time of Burst

Ray Dalio, founder of Bridgewater Associates, warns that the current artificial intelligence investment boom shows classic signs of a bubble, which he expects will eventually burst. In a Bloomberg Television interview, he noted that great technological revolutions often lead to capital inflows that create bubbles, making it difficult for investors and companies to calibrate their spending accurately—either overspending to capture market share or underspending and losing their competitive position. This caution comes amid significant rallies in AI-related assets, particularly chipmakers, driven by soaring demand for data centers and high-bandwidth chips, raising debates about overheating valuations. In contrast, Nvidia CEO Jensen Huang recently asserted that investors embracing the AI wave would see "crazy" returns and dismissed concerns over return on investment for data center spending as outdated. Dalio, however, focuses on the risks in the profit realization phase. He argues that bubbles tend to show signs of破裂 when markets transition from investment to the need for tangible returns, describing the burst as a process of converting paper wealth into cash. While acknowledging AI's intrinsic value, he expressed concern over the future profitability of some AI companies, suggesting the market is repeating a familiar pattern. The 76-year-old billionaire, who fully exited Bridgewater in 2025, has a net worth estimated at $21.5 billion according to the Bloomberg Billionaires Index.

marsbitHá 1h

Dalio Warns: AI Boom Shows Signs of a Bubble, Day of Reckoning Will Be the Time of Burst

marsbitHá 1h

Trading

Spot
Futuros
活动图片

Categorias popularesright-arrow

Etiquetas Popularesright-arrow