Crypto Prediction Markets Continue To Be Under Siege — Are Traders Now Fair Game For Prosecutors?

bitcoinistPublicado a 2026-04-09Actualizado a 2026-04-09

Resumen

U.S. federal regulators, including the CFTC and DOJ, are seeking a court order to prevent Arizona from enforcing its gambling laws against crypto prediction-market platform Kalshi. They argue that contracts tied to sports, elections, and real-world events qualify as financial derivatives ("swaps") under federal law, not state-regulated gambling. This legal action is part of a broader conflict between federal and state authorities over jurisdiction on prediction markets. Arizona and other states contend these platforms constitute illegal gambling and have initiated criminal charges. Similar legal pressures are affecting Kalshi’s rival, Polymarket, which faces lawsuits and investigations in multiple states. The outcome could either legitimize and boost U.S. prediction markets or fragment them into riskier offshore operations.

U.S. regulators are urging a court to stop Arizona from enforcing its gambling laws against crypto prediction‐market platform Kalshi.

Another Battle Over Crypto Prediction Markets

In a filing from yesterday, the Commodity Futures Trading Commission (CFTC) and the Justice Department (DOJ) commended a federal court to stop Arizona from using its gambling laws against crypto prediction‐market platform Kalshi.

The agencies are asking for a temporary restraining order and preliminary injunction to halt Arizona’s criminal case and gambling‐law enforcement.

Related Reading: Bitcoin Creator Exposed? New Investigation Points At The Real Identity Of Satoshi Nakamoto

CFTC argues that these contracts tied to sports, elections and other real‐world events qualify as swaps (financial derivatives) under U.S. law, rather than falling under state gambling statutes. The federal regulators based their arguments on the fact that since the contracts are settled on future events with economic impact, they are governed by the Commodity Exchange Act and fall under federal law rather than state authority.

Such interpretation curbs how far individual states can go in blocking or constraining these platforms, which regulators say would otherwise splinter the market into a patchwork of state‐by‐state rules.

The Arizona Lawsuit Explained

Arizona charged Kalshi with illegal gambling over sports and election markets. Arizona, along with an expanding list of other states, argue that contracts tied to sports results operate like ordinary bets and must be treated as gambling, subject to licensing rules, age limits, and consumer safeguards.

According to the court filing, Arizona first sent a cease‐and‐desist order to KalshiEx LLC and Kalshi Trading LLC in May 2025, alleging they were taking unlawful bets in breach of state law. The state then brought criminal charges against both entities for “betting and wagering” under several Arizona statutes, with an arraignment set for April 13.

On Monday, a Third Circuit (one of the 13 U.S. federal courts of appeals) ruling stated that sports event contracts on designated contract markets (DCMs) are “swaps” preempting state gambling laws. However, one judge disagreed, blasting Kalshi’s stance as a “performative sleight” designed to hide the fact that its offerings are, in substance, sports betting.

Crypto Prediction Markets Under A Coordinated State Pushback

This move follows a broader CFTC and DOJ litigation against Arizona, Connecticut, and Illinois over prediction‐market jurisdiction. Bitcoinist reported on it last week. This past month, a bipartisan Senate bill targeting sports‐style bets on platforms like Polymarket and Kalshi was introduced by Senators Adam Schiff (D-CA) and John Curtis (R-UT).

Also on March, democratic representative Seth Moulton of Massachusetts (MA-06) formally banned all his staff from participating in prediction markets. That same day, Congressman Adrian Smith (R-NE-03) and Congresswoman Nikki Budzinski (D-IL-13) from Nebraska introduced the PREDICT Act, banning members of Congress from trading on political and policy outcome markets.

Related Reading: SEC Admits Flaws In Crypto Enforment, What Went Wrong?

Kalshi’s main rival, Polymarket, is also under mounting legal fire, with a New York class action filed in February alleging it runs an unlicensed sports‐betting operation. Regulators in Nevada have launched a civil case against its parent company, and authorities in Ohio, Utah, and Iowa have likewise begun probing the platform.

Not too long ago, Argentinian authorities ordered a full national ban of Polymarket after it “predicted” inflation data back in February. On top of that, the platform faced terrible backlash recently after bettors sent death threats to Times of Israel military reporter Emanuel Fabian, following his report of an Iranian ballistic missile on March 10.

Both Kalshi and Polymarket updated their rules at the end of March to preemptively block politicians, candidates and sports insiders from trading on related markets

If the federal preemption is upheld, it will de‐risks U.S. prediction venues, potentially boosting liquidity and making them more attractive as macro and sports‐beta tools for crypto‐savvy traders. However, if states carve out sports and politics as gambling, markets may fragment offshore or into on‐chain, harder‐to‐police venues, raising operational and legal risk premia for anyone treating these contracts as serious hedging instruments.

Yesterday, Bitcoin bounced back and reclaimed $72k. At the moment of writing, BTC trades for around $71k on the daily chart. Source: BTCUSD on Tradingview.

Cover image from Perplexity. BTCUSD chart from Tradingview.

Preguntas relacionadas

QWhat is the main argument of the U.S. regulators (CFTC and DOJ) against Arizona's enforcement of its gambling laws on Kalshi?

AThe CFTC and DOJ argue that the contracts offered by Kalshi, which are tied to sports, elections, and other real-world events, qualify as financial derivatives (swaps) under U.S. federal law, specifically the Commodity Exchange Act. They contend that these contracts, because they are settled on future events with economic impact, fall under federal jurisdiction and preempt state gambling statutes.

QWhat specific legal measures are the federal agencies requesting from the court regarding Arizona's case against Kalshi?

AThe Commodity Futures Trading Commission (CFTC) and the Justice Department (DOJ) are asking the court for a temporary restraining order and a preliminary injunction to halt Arizona's criminal case and its enforcement of gambling laws against Kalshi.

QAccording to the article, what was the recent ruling by the Third Circuit court regarding sports event contracts on designated contract markets (DCMs)?

AA recent Third Circuit ruling stated that sports event contracts on designated contract markets (DCMs) are considered 'swaps,' which preempts state gambling laws. However, one judge dissented, calling Kalshi's stance a 'performative sleight' designed to disguise what is essentially sports betting.

QBesides Kalshi, which other major prediction market platform is facing significant legal challenges, and what are some examples?

AKalshi's main rival, Polymarket, is also under significant legal pressure. A New York class action lawsuit was filed in February alleging it runs an unlicensed sports-betting operation. Regulators in Nevada have launched a civil case against its parent company, and authorities in Ohio, Utah, and Iowa are probing the platform. It was also completely banned in Argentina.

QWhat are the two potential future scenarios for U.S. prediction markets outlined at the end of the article, depending on the legal outcome?

AIf federal preemption is upheld, it would de-risk U.S. prediction venues, potentially boosting their liquidity and attractiveness as trading tools. Conversely, if states successfully classify these markets as gambling, the markets may fragment and move offshore or into on-chain venues that are harder to police, thereby raising operational and legal risks for traders.

Lecturas Relacionadas

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbitHace 1 hora(s)

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbitHace 1 hora(s)

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.

marsbitHace 1 hora(s)

Token Inefficient, Economy Tokenless

marsbitHace 1 hora(s)

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.

marsbitHace 1 hora(s)

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

marsbitHace 1 hora(s)

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.

marsbitHace 1 hora(s)

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

marsbitHace 1 hora(s)

Trading

Spot
Futuros
活动图片