# Insider Trading İlgili Makaleler

HTX Haber Merkezi, kripto endüstrisindeki piyasa trendleri, proje güncellemeleri, teknoloji gelişmeleri ve düzenleyici politikaları kapsayan "Insider Trading" hakkında en son makaleleri ve derinlemesine analizleri sunmaktadır.

Kalshi Sues Minnesota Over New Law Blocking Prediction Markets

Prediction market platform Kalshi has sued the state of Minnesota over a new law that would restrict most prediction market activity and impose criminal penalties on related contracts. Kalshi argues that its event contracts are federally regulated financial products under the Commodity Futures Trading Commission's exclusive oversight, not gambling subject to state law. Minnesota lawmakers, however, view such contracts as a form of gambling operating outside consumer protection rules and have enacted criminal penalties for operating or promoting them. The lawsuit follows increased regulatory scrutiny, including a federal investigation announced in May into Kalshi and Polymarket regarding the detection of insider trading, prompted by suspicious trades linked to US military and geopolitical events.

bitcoinist05/28 23:23

Kalshi Sues Minnesota Over New Law Blocking Prediction Markets

bitcoinist05/28 23:23

Google Engineer Arrested For Using Company’s Own Search Data To Win $1.2 Million On Polymarket

A Google information security engineer, Michele Spagnuolo, has been arrested and charged with commodities fraud, wire fraud, and money laundering. Prosecutors allege he used confidential internal Google search data to place bets on the crypto-based prediction market Polymarket, winning approximately $1.2 million by knowing outcomes before the public. Using an internal tool showing real-time search trends, he reportedly placed successful wagers on contracts tied to Google's "Year in Search" rankings for 2025. This is the second federal criminal case involving Polymarket insider trading in just over a month, following an April arrest of a U.S. Army sergeant accused of using classified military information. The cases highlight increasing legal scrutiny of prediction markets, with blockchain transparency aiding prosecutors. Google placed Spagnuolo on leave and is cooperating with authorities.

bitcoinist05/28 14:31

Google Engineer Arrested For Using Company’s Own Search Data To Win $1.2 Million On Polymarket

bitcoinist05/28 14:31

TechFlow Intelligence Bureau: Spot Gold Falls Below $4,400, Cryptocurrency Market Plunges Across the Board

The market experienced volatility with spot gold dropping below $4400/oz, while the crypto market saw broad declines. In AI developments, VLLM and other mainstream LLM tools were found to have critical vulnerabilities, risking millions of AI agents. Gemini Omni Flash faced criticism for excessive content filtering, while Ali's Qwen3.6-35B showed significant coding improvement with higher-bit quantization. Nvidia introduced LocateAnything, a visual language model with faster object localization. In crypto, a Google employee was charged for insider trading using search data on Polymarket, where suspicious accounts with near-perfect win rates were also discovered. A Trump-linked crypto company neared bankruptcy after losing $1.5B. Hardware and chip stocks, particularly Korean AI memory makers, drove market gains. Meta's stock rose on news of paid subscriptions for Facebook and Instagram, while Micron delivered massive returns for some investors. Broader trends included DuckDuckGo's traffic surging as users reacted against Google's push for AI search, and Microsoft data suggesting AI tools can be more expensive than human labor. The day's theme highlighted the redefinition of insider information boundaries in the age of AI data advantages and a growing scrutiny of AI's real-world costs and user acceptance.

marsbit05/28 11:02

TechFlow Intelligence Bureau: Spot Gold Falls Below $4,400, Cryptocurrency Market Plunges Across the Board

marsbit05/28 11:02

Looking at the Answers Before Submitting the Test? Google Engineer Entangled in Polymarket Insider Trading Case

A Google security engineer, Michele Spagnuolo, has been arrested and charged with commodities fraud, wire fraud, and money laundering. He is accused of using internal Google tools to access non-public data on search trends for 2025's most-searched personalities and then trading on that information via an associated account ("AlphaRaccoon") on the prediction market platform Polymarket, netting over $1.2 million in profits. A key example involved trading on the rising search popularity of singer D4vd hours after viewing the internal data. Prosecutors traced the funds from the Polymarket account through cryptocurrency swaps and privacy tools, with some proceeds eventually reaching an Italian payment account opened with Spagnuolo's identification. Google stated it is cooperating with authorities and has suspended the employee, noting the misuse of confidential information is a serious policy violation. The case highlights deeper regulatory challenges for Polymarket, which faces scrutiny over user identification and the integrity of trades based on non-public information. Polymarket has stated it is cooperating with U.S. investigators and emphasized the traceability of blockchain transactions.

Odaily星球日报05/28 02:26

Looking at the Answers Before Submitting the Test? Google Engineer Entangled in Polymarket Insider Trading Case

Odaily星球日报05/28 02:26

New Information Laundering in Prediction Markets: How Secrets Blend into Investment Signals

"The New Information Laundering in Prediction Markets: How Secrets Infiltrate Investment Signals In late February 2026, nine linked anonymous wallets on Polymarket placed over 80 bets on specific details of a US-Iran war, winning over $2.4 million with a 98% win rate. This exemplifies 'information laundering'—a destructive flaw inherent to prediction markets. These markets function by aggregating trader supply and demand on an order book to set prices, which represent collective probability estimates. This makes them valuable real-time sentiment indicators for institutions. However, the system cannot distinguish between public information and stolen secrets. Confidential information enters one end, and 'clean' market prices—bearing no trace of their illicit origin—emerge from the other. For example, an insider knowing of an imminent strike can buy contracts at low odds, pushing the price up and disguising the secret as a savvy market signal, then profit massively when the event occurs. Analysts can sometimes uncover these schemes due to the blockchain's transparency, as seen with Bubblemaps. Paradoxically, this same transparency can inadvertently broadcast secrets to adversarial observers, providing them with low-cost intelligence. Current laws, like insider trading regulations focused on corporate information, fail to address this issue, especially concerning events like military actions with no 'issuer.' Jurisdictional challenges are amplified as platforms operate offshore, easily bypassing national bans with VPNs. Recent US congressional investigations and proposed bills aim to ban war betting and trading on non-public information by officials. The core issue is that information laundering is not a bug but a feature: a market that perfectly converts knowledge into price will inherently reward those with the best information, including those who obtained it illicitly. As prediction markets grow, potentially reaching hundreds of billions in volume, society must confront whether it can tolerate a machine that profitably transforms its most guarded secrets into public, tradable numbers."

链捕手05/25 08:56

New Information Laundering in Prediction Markets: How Secrets Blend into Investment Signals

链捕手05/25 08:56

Netting $2.4 Million: These 9 Insider Addresses Knew the US-Iran War Best

On May 18th, Bubblemaps investigators disclosed the discovery of nine highly correlated anonymous accounts on Polymarket that netted over $2.4 million from prediction markets tied to US military actions, with a 98% win rate. The accounts focused almost exclusively on the 2026 US-Iran conflict, placing bets with uncanny precision days before key events like the "Operation Epic Fury" strike on February 28th, which eliminated Iran's Supreme Leader. Bubblemaps' analysis linked four core accounts—each profiting around $400k—and five others through synchronized timing, transaction patterns, and fund flows. The money moved through shared wallet networks, suggesting professional obfuscation. This case is six times larger than the earlier prosecution of US Army Sergeant Gannon Van Dyke for insider trading on Polymarket. While platforms like Polymarket have established AI monitoring and explicit rules against trading on stolen or confidential information, the incident has spurred controversial "insider copy-trading" services that help users follow high-success accounts, raising new regulatory questions.

marsbit05/25 02:06

Netting $2.4 Million: These 9 Insider Addresses Knew the US-Iran War Best

marsbit05/25 02:06

Jane Street Sued: Suspected of Using Telegram Insider Information to Exit and Short Before Terra Collapse, Profiting $134 Million

Wall Street trading giant Jane Street Group is facing a lawsuit alleging it used insider information from a private Telegram channel with a former Terraform Labs intern to avoid losses and profit from the collapse of the Terra ecosystem in May 2022. According to newly unsealed court documents, Jane Street allegedly sold nearly $192 million worth of the UST stable币 before its depeg, and then established short positions, netting approximately $134 million in profits. The suit, filed by Terraform's bankruptcy estate, claims the firm gained a critical "information advantage" through these private communications, allowing it to execute large sales, including an $85 million UST transaction on Curve Finance minutes after Terraform quietly withdrew liquidity. Jane Street has denied the allegations as "baseless" and moved to dismiss the case. A 2023 court ruling that classified UST and Luna as securities bolsters the legal basis of this suit.

marsbit05/22 04:53

Jane Street Sued: Suspected of Using Telegram Insider Information to Exit and Short Before Terra Collapse, Profiting $134 Million

marsbit05/22 04:53

'Stock God' Trump's 3,642 Trades Disclosed: The 'Perfect Closed Loop' of Policy and Portfolio

Summary: Donald Trump's First Quarter stock trades, totaling 3,642 transactions, have been disclosed. While the White House maintains the trades were managed by an advisor and complied with disclosure laws, they reveal a portfolio heavily aligned with his policy agenda. The trades show a rotation away from major tech stocks like Microsoft, Amazon, and Meta, and into semiconductor and AI hardware companies such as NVIDIA, AMD, Broadcom, Dell, and Intel. Notably, Trump's account purchased Dell stock before he publicly praised the company, after which its stock rose. The Dell family also pledged funds to a Trump-affiliated policy project. A critical case is Intel. The Trump administration converted $8.9 billion in CHIPS Act subsidies into a 9.9% equity stake, making the U.S. government Intel's largest shareholder. Months later, Trump's personal account also bought Intel stock. This intertwines national industrial policy with potential personal financial interest. Unlike typical insider trading concerns, this situation creates a "closed loop": policy decisions (e.g., subsidies, tariffs, crypto regulation) can boost the value of his holdings, and those holdings may, in turn, influence future policy directions. This blending of presidential power and personal portfolio, while legally disclosed, raises profound questions about conflicts of interest that current rules do not address.

marsbit05/18 10:26

'Stock God' Trump's 3,642 Trades Disclosed: The 'Perfect Closed Loop' of Policy and Portfolio

marsbit05/18 10:26

World Cup Approaches, Prediction Markets Face a Major Test

The 2026 FIFA World Cup represents a major public test for sports prediction markets like Polymarket and Kalshi, which have grown significantly by offering tradable markets on event outcomes. This global event, hosted by the US, Canada, and Mexico, concentrates risks related to sports integrity, cross-border operations, and gambling ecosystems. A key concern is the potential for insider trading on non-public information (e.g., injuries, lineups), which could be exploited in granular prediction markets. FIFA's choice of its official prediction market partner, ADI Predictstreet, has raised significant doubts. The platform, relatively unknown, has faced scrutiny over the integrity of its executives—including past insider trading allegations and associations with a major EU corruption scandal—its rapid licensing in Gibraltar, and the fact its product was not yet live at the time of the announcement. This partnership begins with a "trust deficit." FIFA itself carries historical corruption baggage, and its deepening ties with betting and data industries fuel concerns about maintaining sporting integrity. While FIFA has established monitoring systems, their effectiveness against potential insider trading across decentralized global prediction markets remains unproven. Major US-based prediction platforms have updated rules to prohibit trading based on confidential information. However, the World Cup's complex ecosystem of federations, teams, and officials makes enforcement far more challenging than in domestic leagues. The event will not determine the fate of prediction markets but will critically test whether they can be integrated as a regulated event-trading infrastructure or remain a high-risk gambling-adjacent activity within global sports.

marsbit05/15 05:11

World Cup Approaches, Prediction Markets Face a Major Test

marsbit05/15 05:11

Prediction Markets Cannot Exist Without Insider Trading, But Insider Trading Is Killing Them

Prediction markets face a fundamental contradiction: they rely on insider trading to generate accurate prices, yet this same activity erodes public trust and threatens their survival. Recent scandals, such as a U.S. special forces member making $400,000 on Polymarket using classified information about a raid, highlight the severity of the issue. While platforms like Polymarket and Kalshi market themselves as venues where "everyone is an expert" and encourage informed trading, they also enforce policies against illegal insider trading. The core dilemma is that these markets depend on informed insiders for price efficiency but require uninformed retail participants to provide liquidity. If insider trading is too rampant, retail traders leave, perceiving the market as unfair. If restrictions are too strict, valuable information flow dries up, reducing the market’s predictive utility. The challenge is finding a balance that maintains both accuracy and perceived fairness—a task complicated by regulatory pressures and recurring scandals.

marsbit04/27 02:35

Prediction Markets Cannot Exist Without Insider Trading, But Insider Trading Is Killing Them

marsbit04/27 02:35

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