Polymarket Just Dropped Its Toughest Insider‑Trading Rules Yet – But Can They Really Calm DC?

bitcoinistPublicado a 2026-03-24Actualizado a 2026-03-24

Resumen

Polymarket, the world's largest prediction market, has introduced stricter rules against insider trading and market manipulation. These updates explicitly ban trading on confidential information, illegal tips, and participation by individuals who can influence event outcomes, such as government officials or athletes. The move comes amid increased regulatory scrutiny, including a new bipartisan Senate bill targeting prediction markets. Competitor Kalshi also announced similar guardrails. Both platforms are strengthening compliance to address ethical concerns and regulatory pressures, which may lead to tighter KYC procedures and reduced tolerance for trading on non-public information.

Polymarket, the world’s largest prediction market, is rolling out new safeguards against insider trading and manipulation.

Polymarket’s Most Recent Bet

The pressure generated from the growing scrutiny that prediction markets have come under as of late seems to have done the trick. Polymarket updated its rules on Monday and shortly after, Kalshi, its main competitor, announced new guardrails that preemptively block politicians, candidates and sports insiders from trading on related markets, Bloomberg claims.

Neal Kumar, Polymarket’s chief legal officer, said in a statement that the goal of this update to the rulebook is clarifying the expectations they have for the users. “Markets thrive on clarity”, he claims:

“These rule enhancements make our expectations abundantly clear for every participant across both platforms and highlight the compliance infrastructure we have already built. As Polymarket continues to scale, we will build on our foundation with clear communication to Polymarket’s users to ensure our markets do what they do best — surface truth.”

The timing is not casual. Also on Monday, Senators Adam Schiff (D-CA) and John Curtis (R-UT) introduced a bipartisan Senate bill targeting sports‐style bets on platforms like Polymarket and Kalshi, after a string of “suspiciously well‐timed” trades. The Senate concerns go beyond the law, citing the surge of gambling culture promoted by online betting can easily lead to addiction.

What Actually Changed At Polymarket And Kalshi

Polymarket updated its Terms of Use and U.S. Rulebook with enhanced “market integrity” rules across both its DeFi platform and CFTC‐regulated U.S. exchange. The new language explicitly bans trading on stolen or confidential information when using it would violate a duty of trust or confidence (classic insider‐trading standard). It also prohibits trading on illegal tips, where a user knows or should know the person sharing the information is themselves barred from trading on it. Additionally, users who can influence the outcome of a bet, such as government officials, corporate executives, or athletes tied to the event, are barred from trading on related contracts.

The rulebook also spells out broader manipulation bans, including spoofing, wash trading, fictitious transactions, front‐running, self‐dealing and other disruptive practices. The dedicated “Market Integrity” provide tools to report suspicious activity across both platforms, highlighting a multi‐layer surveillance and enforcement framework that combines automated monitoring with human review to flag and investigate questionable trades.

Similarly, on its side, Kalshi announced expanded “guardrails” against insider trading and market manipulation, framed as a response to CFTC guidance and the latest congressional proposals. The exchange is rolling out technological screens that aim to preemptively block politicians, political candidates and campaign insiders from trading on their own races. Similar screens will bar athletes and other “relevant people”, like team staff, league insiders and other connected personnel, from trading in sports markets they are involved with.

What This Means For Traders

Prediction markets have exploded into a multi‐billion‐dollar venue for trading politics and sports, but that scale brought CFTC scrutiny, state‐level pushback and now congressional bills aimed squarely at their growth engines. Some of the critiques show valid ethic concerns. Let’s not forget that 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.

Polymarket and Kalshi are now racing to build compliance as a moat: whoever convinces regulators first may become the default institutional on‐ramp, while weaker venues risk being regulated into the ground. Traders can expect tighter KYC/surveillance and less tolerance for “edge” based on non‐public info.

BTC’s price hangs in $71k on the daily chart. Source: BTCUSDT on Tradingview

Cover image from Perplexity, BTCUSDT chart from Tradingview

Preguntas relacionadas

QWhat are the main reasons behind Polymarket's recent update to its insider-trading rules?

APolymarket updated its rules due to growing regulatory scrutiny from the CFTC, state-level pushback, and new congressional bills targeting prediction markets, alongside a series of suspiciously well-timed trades that raised concerns about market integrity.

QWhat specific activities are now explicitly banned under Polymarket's enhanced 'market integrity' rules?

APolymarket now explicitly bans trading on stolen or confidential information that violates a duty of trust, trading on illegal tips, and trading by users who can influence the outcome of a bet. It also prohibits broader manipulation practices like spoofing, wash trading, fictitious transactions, front-running, and self-dealing.

QHow did Polymarket's main competitor, Kalshi, respond to the regulatory pressure?

AKalshi announced expanded 'guardrails' against insider trading and market manipulation, including technological screens to preemptively block politicians, candidates, and sports insiders from trading on markets related to their own events, in response to CFTC guidance and congressional proposals.

QWhat broader concerns did U.S. Senators express about prediction markets beyond insider trading?

AU.S. Senators expressed concerns that the surge of gambling culture promoted by online betting platforms can easily lead to addiction, which is why they introduced a bipartisan bill targeting sports-style bets on these platforms.

QWhat are the potential long-term implications for prediction market platforms like Polymarket and Kalshi according to the article?

AThe platforms are racing to build compliance infrastructure as a competitive moat. The one that convinces regulators first may become the default institutional on-ramp, while weaker venues risk being regulated out of existence. Traders can expect tighter KYC/surveillance and less tolerance for trading on non-public information.

Lecturas Relacionadas

Interview with CoreWeave Co-founders: AI Demand Seems to 'Intensify' Every Day

An Interview with CoreWeave Executives: AI Demand Seems to 'Intensify' Every Day In an interview, CoreWeave executives highlight a structural shift in AI infrastructure demand. While GPU availability remains crucial, the primary bottlenecks are evolving to include powered data center shells, skilled labor (like electricians), and complex supply chain execution. They note that AI demand, particularly for agentic AI and reasoning models, continues to intensify daily, accelerating since Q1 2024. This demand is driving a need for more balanced infrastructure. CoreWeave is redesigning data centers to allocate more space for storage and CPUs alongside GPUs, with significant interest in Nvidia's upcoming Vera CPUs. The company, serving top AI labs and hyperscalers, emphasizes its client-driven model, building precisely to customer specifications. CoreWeave attributes its competitive edge to proven execution, performance, and a mature platform for AI deployment. Pricing is structured to pass component cost increases (e.g., for HBM memory) to customers, protecting margins. Looking ahead, they anticipate Vera Rubin platform deployments to begin meaningfully in late 2025, with a major ramp throughout 2027, mirroring the Blackwell (GB) series rollout pattern. The competition is shifting from merely acquiring chips to holistic engineering and delivery capability.

marsbitHace 4 min(s)

Interview with CoreWeave Co-founders: AI Demand Seems to 'Intensify' Every Day

marsbitHace 4 min(s)

Manus Buyback Plan Emerges: Chinese Investors Plan to Repurchase Equity with $2 Billion, Path to Hong Kong IPO Becomes Clearer

According to a report by The Information, early Chinese investors of Manus, including Tencent, Sequoia Capital China, and ZhenFund, are planning to repurchase the company from Meta for $2 billion—the same price Meta paid in its acquisition last December. This move is a direct response to the Chinese government's prohibition of the foreign acquisition in April. As part of the repurchase plan, Manus is considering establishing a Sino-foreign joint venture within China. This structure is seen as a way to ensure regulatory compliance for its Chinese investors and to pave the way for a future IPO in Hong Kong. Notably, U.S. investor Benchmark will not participate in the buyback, which will concentrate ownership even more among Chinese capital. Since its acquisition by Meta, Manus's business has grown rapidly, with its annualized revenue run rate reportedly increasing four-to-fivefold to $400-$500 million in roughly six months. This strong growth underpins the investors' willingness to repurchase at the original price. Financially, the forced unwinding of the deal may benefit the early investors, allowing them to regain equity at a cost far below the company's current implied valuation, with the added prospect of an independent future listing. However, specific terms of the repurchase, including funding proportions and the joint venture's equity structure, are still under negotiation. This "repurchase-joint venture-Hong Kong IPO" approach could serve as a reference model for other Chinese AI startups navigating cross-border M&A regulations.

marsbitHace 14 min(s)

Manus Buyback Plan Emerges: Chinese Investors Plan to Repurchase Equity with $2 Billion, Path to Hong Kong IPO Becomes Clearer

marsbitHace 14 min(s)

STRC Loses Peg by 11%, Can Strategy's Perpetual Motion Machine Keep Running?

The article discusses the significant and concerning depegging of MicroStrategy's (MSTR) preferred stock, STRC. Designed to trade near its $100 target par value, STRC has recently fallen sharply, reaching a low of $83.26 and closing at $88.59, representing an over 11% discount. STRC is a core component of MicroStrategy's financial strategy. As a perpetual preferred stock, it allows the company to raise capital through an "at-the-market" (ATM) issuance program without diluting common shareholders (MSTR). This capital is primarily used to purchase Bitcoin, creating a "capital flywheel": issuing STRC → raising cash → buying BTC → increasing net assets → supporting STRC's value. The flywheel's operation depends on STRC maintaining its $100 price. To enforce this, MicroStrategy employs a dynamic dividend mechanism, recently raising the rate to 11.5% and increasing payout frequency. However, this has failed to halt the depegging, indicating market concerns extend beyond yield. Analysts cite two main reasons. First, technical factors like forced liquidations from leveraged arbitrage trades may have exacerbated the sell-off. Second, and more fundamentally, is waning confidence in MicroStrategy's financial resilience. A JPMorgan report highlighted the company's limited cash relative to its ~$1.7 billion annual dividend obligation, raising liquidity concerns. While MicroStrategy counters that its massive Bitcoin holdings provide decades of coverage, this argument relies on the potential need to sell BTC—a departure from its long-standing "never sell" narrative. The company's recent sale of a small amount of Bitcoin for "testing," despite being framed as minor, has intensified these fears. The persistent depegging threatens to cripple MicroStrategy's primary funding channel. If STRC remains discounted, the company's ability to fund further Bitcoin purchases weakens. Should cash reserves dwindle while financing is constrained, the market may increasingly price in the risk of MicroStrategy becoming a forced seller of Bitcoin to meet obligations. This shift from a major marginal buyer to a potential seller could pose significant downside risk to the broader Bitcoin market.

链捕手Hace 22 min(s)

STRC Loses Peg by 11%, Can Strategy's Perpetual Motion Machine Keep Running?

链捕手Hace 22 min(s)

Altcoins Face Deepest Spot Sell Pressure Since 2020, CryptoQuant Data Shows

Altcoins are enduring one of their most severe periods of spot-market selling pressure since 2020, according to CryptoQuant data, with a cumulative buy/sell volume gap of roughly $209 billion. This reflects weak retail demand, a rotation into safer assets like Bitcoin, Ethereum, and stablecoin yield products, and broad investor caution. While such extreme selling can set the stage for a contrarian opportunity by showing one-sided positioning, the data does not yet signal an immediate reversal or altcoin season. The market remains in a defensive state, lacking the sustained spot accumulation and broad sector improvement needed for a confirmed bullish turn.

bitcoinistHace 49 min(s)

Altcoins Face Deepest Spot Sell Pressure Since 2020, CryptoQuant Data Shows

bitcoinistHace 49 min(s)

Behind the AI Scorecards Lies a Chinese 'Question Setter'

Behind the AI scorecards that dominate industry discussions—benchmarks like MMLU-Pro, MMMU, and MMMU-Pro—stands a Chinese-Canadian researcher: Wenhu Chen. As an assistant professor at the University of Waterloo and founder of the TIGER Lab, Chen has become a key "exam-setter" for evaluating large language and multimodal models. Chen first gained broader recognition with MMLU-Pro, a more challenging and stable update to the popular MMLU benchmark. As top models like OpenAI’s o3 began achieving near-perfect scores on the original MMLU, it became difficult to distinguish their true capabilities. MMLU-Pro introduced more complex reasoning questions, expanded answer choices, and filtered out ambiguous or simple items, effectively reintroducing differentiation among state-of-the-art models. His work on MMMU addressed the evaluation of multimodal models, requiring them to integrate visual information (like charts, diagrams, or tables) with textual knowledge across diverse academic subjects. Even the strongest models initially scored only around 56-59%, highlighting significant room for improvement in genuine multimodal reasoning. MMMU-Pro further refined this by preventing models from bypassing visual cues. Chen’s research focus has long been on complex information understanding and reasoning. His background—including a PhD at UC Santa Barbara, research at Google/DeepMind on Gemini, and now a role in Meta’s superintelligence lab—provides deep insight into model development and their potential weaknesses. His TIGER Lab also builds models (e.g., for video understanding and generation), ensuring his evaluation benchmarks are grounded in practical challenges. While AI headlines often spotlight company leaders and product launches, Chen’s work exemplifies the critical, behind-the-scenes contributions of researchers crafting the rigorous standards that define and drive progress in AI capabilities.

marsbitHace 1 hora(s)

Behind the AI Scorecards Lies a Chinese 'Question Setter'

marsbitHace 1 hora(s)

Trading

Spot

Futuros