Predicting the weather, the place most prone to insider trading in the world

Title: Predicting the Weather, the Easiest Place in the World for Insider Trading

Author: Liu Kaiwen

Source:

Repost: Mars Finance

Around 9 PM on April 15, 2026, a weather sensor at Paris Charles de Gaulle Airport suddenly jumped from 16°C to 22°C. Twenty-four minutes later, the temperature quietly dropped back to its original level.

Meanwhile, during the same period, all nearby weather stations showed no change in readings. The French meteorological agency conducted physical inspections and data analysis on the sensor afterward, and after ruling out equipment failure, they found “evidence of human illegal interference”: someone had secretly heated the sensor.

As of the publication of this article, the French meteorological agency has officially filed a criminal complaint with the Roissy Airport gendarmerie. If convicted, the involved party could face France’s maximum penalty for tampering with automated data processing systems of public institutions: 7 years in prison and a fine of 300k euros.

A seemingly trivial incident, but behind it points to a prediction market platform called Polymarket.

Prediction Market Principles

Polymarket is a blockchain-based binary options prediction market platform. Here, users can bet on any event with a clear outcome, from “Will Trump win the election?” to “Will the highest temperature in Paris today exceed 22°C?”

Each market’s answer is either “Yes” or “No,” and the real-time fluctuating prices precisely represent the probability of the event occurring, reflecting the collective judgment of participants. Correct guesses profit proportionally, while incorrect guesses lose the principal.

For markets like the highest temperature in a region, Polymarket uses official data from specific weather stations as the settlement basis to avoid ambiguity. In the Paris daily high-temperature market, the settlement source is the automatic weather station at Météo France located at Charles de Gaulle Airport (LFPG station).

The rules themselves are sound—until someone discovered that this sensor was placed just outside the runway perimeter fence, near a public road, with almost no fencing or cameras around, making it accessible to anyone.

Half an hour’s work turned a 178-fold profit, with only a $35 hairdryer as the investment

Around 9 PM local time in Paris on April 15, Polymarket’s “The probability that the highest temperature in Paris on April 15 is 18°C” had already exceeded 99%. At this point, temperatures were dropping at night, and the market seemed to have entered “garbage time.”

But at this moment, an account with ID xX25Xx bet heavily on “No” with less than $120—due to the odds mechanism, this bet’s potential payout exceeded $20k.

Even so, traders didn’t take this bet seriously at the time. On this platform, it’s common for gamblers to “bet small to win big,” and taking the opposite side of these gamblers, earning their principal, is one of the most stable profit strategies.

And after the subsequent temperature reading was announced, the sensor jumped from 16°C to 22°C. The probability of “highest temperature being 18°C” instantly dropped to zero. The original $120 bet by xX25Xx multiplied approximately 178 times, but professional traders and quantitative bots, who have been consistently profitable in such markets, suffered significant losses this time.

Meteorologist Paul Marquis later pointed out: “Without changes in wind direction or relative humidity, and no other stations recording anything unusual, the most reasonable explanation is physical interference using a heating device near the sensor probe.”

The motive for tampering with the temperature data is now basically clear: knowing the principles of weather sensors, xX25Xx first bet at extremely high odds that the day’s highest temperature would exceed 18°C, then used a heating device to artificially modify the sensor’s readings and profited from it.

xX25Xx has since changed their account ID, seemingly trying to avoid public scrutiny; meanwhile, Polymarket’s blockchain-based mechanism makes all their transaction records publicly accessible.

The ultimate “oracle” of public opinion polls

Polymarket isn’t just betting on the weather. Here, you can bet on whether Israel and Hamas will cease fire, whether the Federal Reserve will cut interest rates next time, or what profession AI will replace next. Its markets cover politics, economics, technology, sports, natural disasters—almost any event with a clear outcome can be traded.

What truly brought prediction markets into the spotlight was the 2024 U.S. presidential election. Most polls showed Trump and Harris neck and neck, but the prediction market’s probability of Trump winning had been consistently above 90%. The final result proved that this “collective judgment” driven by real money pointed to the correct answer earlier than most professional polls.

After this event, prediction markets have increasingly been regarded as a unique information tool—not gambling, but “a poll with real money voting.” Participants stake real funds, motivating them to gather genuine information rather than just randomly guessing what feels right. Theoretically, this mechanism makes market prices closer to true probabilities.

But this logic has a hidden risk: the greater the influence, the stronger the motivation for attack. When prediction markets become a “oracle” cited by global media, and their prices start influencing public perception of real events, the vulnerability of each data source becomes a potential exploit.

Weather markets are precisely among the most fragile. And the ways to exploit vulnerabilities go far beyond heating sensors.

The unnoticed airport temperature recorder now charges for access

Besides physical tampering, information asymmetry itself is another widely discussed “advantage” in weather markets.

This month, Polymarket launched daily high-temperature markets for several Chinese cities, including Shanghai Pudong Airport, Shenzhen Bao’an Airport, and Beijing, with settlement relying on METAR data from airports.

According to trading community discussions, a type of “weather prophet” has emerged—different from professional traders and quantitative bots—who can always lock in the betting direction related to temperature changes before the weather data is publicly updated.

Unlike building predictive models based on open-source weather data, these traders seem to have a clear time advantage. There are even rumors circulating that some have shared profit screenshots and trading strategies publicly, and are running paid groups.

In a weather market where “insiders” seem least likely to exist, delays in meteorological reports and differences in data update rhythms are causing widespread doubts about the reliability of weather markets in some Chinese cities.

When weather data becomes an asset that can be priced and traded, those who understand this data suddenly become the most valuable players. Those with access to METAR data channels and who are one step ahead of the market find themselves in an unexpectedly advantageous position.

Heating a sensor for half an hour, shaking the trust foundation of a trillion-dollar business system

So far, this might seem like a financial game happening within the prediction market circle. Bets are only a few tens of thousands of dollars, and the gains or losses circulate within that small circle.

But the METAR data from airport weather stations is never just the settlement basis for Polymarket.

Every operational decision of airlines is based on meteorological data. According to FAA data, over half of flight delays are weather-related, and extreme weather is the single largest factor in 42% of cancellations. Weather-related flight disruptions cause over $60 billion in annual losses to the aviation industry. Behind this figure are countless scheduling decisions relying on accurate data.

Pricing of agricultural insurance also depends on meteorological data. The global agricultural insurance market is about $46 billion, with many products using “parametric insurance” mechanisms—automatic payouts triggered when temperature, rainfall, or other weather indicators meet preset conditions, without manual inspection. The premise of this mechanism is the authenticity of meteorological data. If data is tampered with, trigger conditions become distorted.

On a higher level, reinsurance relies on long-term meteorological data to build actuarial models for pricing extreme weather events. A single station’s data quality issues might have limited impact on a single event; but if such human interference with a single data source can be cheaply replicated, the credibility of climate data begins to shake from the ground up.

This is only the known, traceable commercial dependence. Energy companies use meteorological data to forecast peak electricity demand; logistics firms plan routes and warehouses based on it; construction schedules depend on weather forecasts; and commodity futures prices are also influenced by real-time assessments of agricultural regions’ weather conditions.

In this system, weather station sensors are the most fundamental input. Someone heated a sensor to make a few extra thousand dollars in prediction markets—this small act touches a data chain extending from airport runways to the global financial markets.

France’s investigation into this case is still ongoing. After replacing the settlement source for the Paris market involved, no settled markets have been refunded. The accounts that profited earlier still hold their funds.

The potential risks behind this incident may be greater than we imagine. The objectivity of temperature data makes abnormal behavior relatively easy to detect, but in the prediction market landscape, many markets rely on a single data source for settlement—some events are far more complex than weather, and much harder to verify independently.

Prediction markets were once called the “ultimate oracle” for revealing truth. When their data sources themselves become targets of attack, the meaning of that title becomes much more complicated.