Crypto ETPs could see a flood of liquidations by 2027: Analyst

cointelegraphPublicado a 2025-12-18Actualizado a 2025-12-18

Resumen

Bloomberg analyst James Seyffart predicts that while over 100 crypto exchange-traded products (ETPs) could launch in 2026, a significant number will face liquidation by 2027 due to insufficient demand and low assets under management. This follows a trend of ETF closures, with 244 shutting down in the U.S. in 2023 alone. The anticipated surge in approvals is linked to the SEC's new generic listing standards, which streamline the process. Despite the success of major spot Bitcoin and Ether ETFs, which have attracted tens of billions in inflows, more speculative products, including those tracking tokens like Solana, have seen smaller inflows, and some, such as two ARK 21Shares ETFs, have already been liquidated this year.

More than 100 crypto exchange-traded products are likely to hit the market in 2026, but many of them will quickly be shuttered due to a lack of demand, an analyst says.

Bloomberg analyst James Seyffart said on Wednesday that he agreed with a 2026 prediction from crypto asset manager Bitwise that over 100 crypto ETFs would launch, but said many wouldn’t last.

“We’re going to see a lot of liquidations in crypto ETP products. Might happen at [the] tail end of 2026 but likely by the end of 2027,” Seyffart said, adding that over 126 ETP applications are currently awaiting an outcome from the US Securities and Exchange Commission.

“Issuers are throwing A LOT of product at the wall.”

Last year, a total of 622 ETFs closed down, including over 189 in the US, The Daily Upside noted last month. Morningstar reported in January 2024 that the 244 ETFs that closed in the US in 2023 had an average age of 5.4 years.

Source: James Seyffart

Most of these investment products shut down because they failed to attract sufficient inflows, resulting in low assets under management.

Several crypto ETPs have already been liquidated this year, the most noteworthy were the ARK 21Shares Active Bitcoin Ethereum Strategy ETF (ARKY) and ARK 21Shares Active On‐Chain Bitcoin Strategy ETF (ARKC).

SEC’s listing standards to spur mass approvals

Industry analysts expect an explosion in the number of crypto ETPs approved in 2026 under the SEC’s new generic listing standards, which no longer require that each application be assessed on a case-by-case basis.

Even before the SEC’s generic listing standards came into effect in September, asset managers had filed to launch ETFs tied to increasingly speculative tokens, such as Melania Trump‘s memecoin.

ETFs tracking Litecoin (LTC), Solana (SOL), and XRP (XRP) launched with relative success this year, expanding from the Bitcoin (BTC) and Ether (ETH) ETFs that launched in 2024.

Related: Bitcoin institutional buys flip new supply for the first time in 6 weeks

Spot Bitcoin ETFs in the US have accumulated $57.6 billion worth of inflows since launching in January 2024, while spot Ether ETFs have amassed $12.6 billion since July 2024, Farside Investors data shows.

Meanwhile, spot Solana ETFs from Bitwise, VanEck, Fidelity, 21Shares, Franklin Templeton, and Grayscale have seen $725 million since late October.

Magazine: Quantum attacking Bitcoin would be a waste of time: Kevin O’Leary

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When Inference Becomes the Scarce Resource, Who Captures the Value? The core AI bottleneck has shifted from model training to inference (runtime execution). While concerns persisted about an "AI compute gap"—initially a $200B, now a $600B problem—the market is now recognizing that the solution and value lie in the inference layer. Nvidia's financial restructuring around "serving tokens" and Cerebras's successful IPO highlight this shift. Inference is a recurring, usage-based cost, estimated to be 10-50x larger than the one-time training market, especially with the rise of agentic AI. The inference stack spans six layers: silicon (e.g., Nvidia), bare metal (e.g., CoreWeave), GPU rental/aggregation, deployment/optimization, model APIs, and end applications. Most companies operate in one layer. However, Hyperbolic uniquely spans three layers (GPU rental, deployment, and model APIs) without owning any hardware. It aggregates fragmented GPU supply from multiple cloud providers into a standardized pool, offering developers the cheapest available compute through intelligent routing. Its multi-cloud aggregation creates a data moat and a flywheel: more supply leads to better pricing data and liquidity, attracting more developers and providers. In contrast, applications like Venice operate at the top of the stack, reselling privacy-wrapped inference but remaining dependent on and constrained by the underlying compute costs they purchase. As inference demand explodes, value accrues not just to consumer applications but increasingly to the aggregation and routing layer that captures their cost of revenue. The coming potential GPU oversupply reinforces this dynamic. While hardware owners may suffer from depreciation, asset-light aggregators like Hyperbolic benefit from price arbitrage, routing workloads to the cheapest available capacity. The ultimate winner in the inference economy may not be the entity with the most GPUs, but the one that can most efficiently discover, aggregate, and route the world's fragmented compute.

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