Kalshi, Polymarket Tighten Rules to Curb Insider Trading

TheNewsCrypto2026-03-24 tarihinde yayınlandı2026-03-24 tarihinde güncellendi

Özet

Kalshi and Polymarket, two major prediction market platforms, are implementing new rules to combat insider trading and market manipulation amid increasing regulatory scrutiny. Kalshi has introduced new screening tools to prevent individuals, including elected officials and those in sports (athletes, coaches, referees), from trading on events they are involved in. The platform is shifting from a reactive enforcement approach to a more proactive one and has added a feature for users to report suspicious activity directly. Similarly, Polymarket has updated its policies to explicitly prohibit trading on stolen information, illegal tips, and by individuals who can influence an event's outcome. It has also broadened its rules against market abuse like spoofing and wash trading. Both platforms are enhancing surveillance, aligning more closely with traditional financial market standards due to concerns about manipulation in prediction markets.

Prediction market platforms Kalshi and Polymarket have planned to launch new rules to curb insider trading and market manipulation as regulatory pressure from Capitol Hill boosts.

The March 23 blog post includes the statement of Kalshi, which mentions that it has rolled out new screening tools to block potential candidates from trading on their own elections, widening current restrictions that so far apply to elected officials.

The platform is also executing a new policy aiming at sports-aimed markets, leveraging screening lists advanced with integrity overlooking company IC360 to prevent athletes, coaches, referees, and other insiders from trading on events they are involved in.

While activities like these are so far restricted, Kalshi mentioned enforcement has widely been reactive, needing scrutiny after trades were placed. Kalshi also featured a prominent feature embedded directly into its trading interface, permitting users to report suspicious activity more swiftly.

Kalshi’s enforcement and legal counsel, Bobby DeNault, mentioned these rules have been in advancement for months to “proactively address” guidance from the Commodity Futures Trading Commission and a congressional proposal to avoid insider trading.

Polymarket’s Statement

At the same time, Polymarket mentioned on March 23 that it has upgraded its governing document over its decentralised platform as well as its CFTC-regulated U.S. exchange, rolling out clearer rules surrounding insider trading and enforcement.

To be specific, Polymarket highlighted three main categories of restricted conduct: trading on stolen confidential information, trading on illegal tips, and trading by individuals who can directly impact the result of an event.

It also widened limitations on wider forums of market abuse, comprising spoofing, wash trading, and front-running. As per the statement of March 23, Polymarket leverages multi-layered surveillance over its DeFi and U.S. platforms, amalgamating on-chain transparency and third-party monitoring to recognise breaches.

The updates show a wider industry push to line up more closely with traditional financial market standards, as policymakers raised concerns that prediction markets, specifically those associated with politics and sports, could be vulnerable to manipulation.

Highlighted Crypto News Today:

TRON DAO Expands AI Fund to $1B for Agentic Economy

TagsInsider tradingKalshiPolymarket

İlgili Sorular

QWhat are the two prediction market platforms mentioned that are implementing new rules to curb insider trading?

AKalshi and Polymarket.

QWhat new tool has Kalshi rolled out to prevent potential candidates from trading on their own elections?

AKalshi has rolled out new screening tools to block potential candidates from trading on their own elections.

QAccording to the article, what are the three main categories of restricted conduct highlighted by Polymarket?

ATrading on stolen confidential information, trading on illegal tips, and trading by individuals who can directly impact the result of an event.

QWhat is the name of Kalshi's enforcement and legal counsel who commented on the new rules?

ABobby DeNault.

QWhat broader industry trend do the updates from Kalshi and Polymarket represent?

AThe updates show a wider industry push to align more closely with traditional financial market standards.

İlgili Okumalar

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.

marsbit58 dk önce

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

marsbit58 dk önce

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.

marsbit2 saat önce

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

marsbit2 saat önce

İşlemler

Spot
Futures
活动图片