Crypto ETP Boom Set To Go Into Overdrive In 2026, Bitwise Says

bitcoinistPubblicato 2025-12-17Pubblicato ultima volta 2025-12-17

Introduzione

More than 100 new crypto exchange-traded products (ETPs) are expected to launch in 2026 due to a recent US regulatory change, according to Bitwise researcher Ryan Rasmussen. The SEC's new generic listing standards eliminate the need for lengthy individual approvals, streamlining the process. This shift allows issuers to file a wider variety of products, including spot crypto, index funds, and equity-linked ETPs. While this will significantly expand investor choice, analysts caution that success will depend on real demand, liquidity, and clear use cases. The market will likely see a wave of new listings, but assets are expected to concentrate in a few large funds, mirroring the broader ETF market.

More than 100 new crypto exchange-traded products could hit the market in 2026 after a recent rule change by the US securities regulator, a researcher at Bitwise said. According to Ryan Rasmussen, that drop in red tape will let firms file many more ETPs without the long, individual approval process that slowed launches in the past.

Regulatory Shift Lowers Bar

The SEC issued generic listing standards in October that remove the need for separate 19(b) approvals for qualifying crypto ETPs. That step cuts out a process some issuers had to wait through — a delay that could stretch to a 240-day clock under earlier practice.

Reports have disclosed that the number of crypto ETPs already sits above 300, based on data from Fineqia International, which shows the market is no longer limited to just a few funds.

Institutional Appetite

Market watchers say new listings make it easier for issuers. But easier access is not the same thing as strong buying. Bitfinex analysts warned in August that altcoins are unlikely to enjoy a major rally until ETFs that track assets beyond the largest coins are available and attract real money. Liquidity, investor interest, and clear use cases still matter a lot. An ETF wrapper does not fix those basic needs by itself.

Total crypto market cap currently at $2.91 trillion. Chart: TradingView

Issuers Race To Expand Menus

Rasmussen said issuers can now plan a variety of products — spot crypto, index funds, equity-linked ETPs, smart beta strategies and momentum plays.

He compared the change to moving from a tiny menu to a much larger one, saying investors will have more choices about where to put money. He also noted it has been about 15 years since the Winklevoss twins first filed for a Bitcoin ETF, and yet only a handful of crypto ETPs are widely held today.

Many New Products, Few Big Winners

Expect a wave of filings. But expect concentration too. In the wider ETF market, most assets gather in a few large funds while many other listings see thin trading.

That pattern is likely to repeat in crypto: dozens of niche products may be launched, while a smaller group gathers most assets under management. Issuers get to plant flags quickly. Investors will sort the winners from the rest over time.

Market Reaction Hinges On Demand

On Sept. 17, Bloomberg ETF analyst James Seyffart said the rule change could trigger a “wave of spot crypto ETP launches.”

Letture associate

a16z: AI's 'Amnesia', Can Continuous Learning Cure It?

The article "a16z: AI's 'Amnesia' – Can Continual Learning Cure It?" explores the limitations of current large language models (LLMs), which, like the protagonist in the film *Memento*, are trapped in a perpetual present—unable to form new memories after training. While methods like in-context learning (ICL), retrieval-augmented generation (RAG), and external scaffolding (e.g., chat history, prompts) provide temporary solutions, they fail to enable true internalization of new knowledge. The authors argue that compression—the core of learning during training—is halted at deployment, preventing models from generalizing, discovering novel solutions (e.g., mathematical proofs), or handling adversarial scenarios. The piece introduces *continual learning* as a critical research direction to address this, categorizing approaches into three paths: 1. **Context**: Scaling external memory via longer context windows, multi-agent systems, and smarter retrieval. 2. **Modules**: Using pluggable adapters or external memory layers for specialization without full retraining. 3. **Weights**: Enabling parameter updates through sparse training, test-time training, meta-learning, distillation, and reinforcement learning from feedback. Challenges include catastrophic forgetting, safety risks, and auditability, but overcoming these could unlock models that learn iteratively from experience. The conclusion emphasizes that while context-based methods are effective, true breakthroughs require models to compress new information into weights post-deployment, moving from mere retrieval to genuine learning.

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Can a Hair Dryer Earn $34,000? Deciphering the Reflexivity Paradox in Prediction Markets

An individual manipulated a weather sensor at Paris Charles de Gaulle Airport with a portable heat source, causing a Polymarket weather market to settle at 22°C and earning $34,000. This incident highlights a fundamental issue in prediction markets: when a market aims to reflect reality, it also incentivizes participants to influence that reality. Prediction markets operate on two layers: platform rules (what outcome counts as a win) and data sources (what actually happened). While most focus on rules, the real vulnerability lies in the data source. If reality is recorded through a specific source, influencing that source directly affects market settlement. The article categorizes markets by their vulnerability: 1. **Single-point physical data sources** (e.g., weather stations): Easily manipulated through physical interference. 2. **Insider information markets** (e.g., MrBeast video details): Insiders like team members use non-public information to trade. Kalshi fined a剪辑师 $20,000 for insider trading. 3. **Actor-manipulated markets** (e.g., Andrew Tate’s tweet counts): The subject of the market can control the outcome. Evidence suggests Tate’sociated accounts coordinated to profit. 4. **Individual-action markets** (e.g., WNBA disruptions): A single person can execute an event to profit from their pre-placed bets. Kalshi and Polymarket handle these issues differently. Kalshi enforces strict KYC, publicly penalizes insider trading, and reports to regulators. Polymarket, with its anonymous wallet-based system, has historically been more permissive, arguing that insider information improves market accuracy. However, it cooperated with authorities in the "Van Dyke case," where a user traded on classified government information. The core paradox is reflexivity: prediction markets are designed to discover truth, but their financial incentives can distort reality. The more valuable a prediction becomes, the more likely participants are to influence the event itself. The market ceases to be a mirror of reality and instead shapes it.

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