“The illusion of free markets is maintained by the asymmetry of information.” – Nassim Nicholas Taleb
Brief overview
Recent events in the crypto market have stirred up the CIS community again. In honor of the quick flip from eth-fuder to eth-maxi and the uncertainty around the Eclipse airdrop – we’re becoming hostages to an information imbalance, especially newcomers.
The goal of this article is to try to look at the situation not from the point of view of a losing player or a lucky winner, but as a cold, calculating machine analyzing large volumes of information.
The PVP market
Professor Andrew Lo, in his research, suggests viewing financial markets not as physical systems governed by mathematical laws, but as complex ecosystems with different species that compete, evolve, innovate, and adapt. This is a direct analogy to a PvP environment, where participants literally fight for survival.
The efficient market hypothesis is not false, it’s just incomplete. In extreme conditions, people start making decisions emotionally rather than rationally, which can quickly become counterproductive for wealth accumulation. Here the PvP element emerges: when rationality disappears, a direct battle of instincts begins.
We can see something similar not only in markets but, for example, in politics, when heaps of distorted – hidden from homo sapiens – information are given out, and turmoil starts within a country among ordinary people.
If we transfer this problem to the crypto market, factors include the teams’ Jewish dances, volumes, the political and economic backdrop, and the diversity of participants. All this creates many variables for answering the main question: “How to make money?” Because there will always be someone who knows more than you.
America vs CIS
To understand the whole picture, let’s define the difference between two key archangels. There are many deep reasons, but we’ll touch on the main ones.
The market of collective expertise is highly developed in the United States. Open exchange of ideas promotes innovation, the growth of passive investing, and the development of complex fintech products, reducing demand for gray and illegal ways to make money.
Parental financial support. Research shows that American parents are more likely to invest both time (support, education) and money in their children’s development, especially if they believe in the possibility of the “American Dream” and economic mobility for their child. Parents tend to pay for development, education, trial business projects, and their children’s first investments.
Regular behavioral anomalies: Even with all its maturity, American investors are prone to herding, especially during crises. All this stems from trust, which is amplified by information noise. In the U.S., 73% of the population uses social networks, one of the highest penetration rates in the world. There you have a vicious circle created by state freemasons. As everywhere, there are pros and cons.
The CIS has cardinal differences. From early childhood, the goal is to become “the richest,” to have everything and everyone, and the faster – the better. A large niche is chosen where that very money flows. Oh, glory to the internet! But there’s a big problem. The entry threshold. For the average American, $10,000 is normal; for the CIS – a jackpot. Inequality gives rise to drive and that very hunger, which from childhood changes the approach to markets. Hence, an already complex market starts turning into a high-intensity PvP battle. Multi-accounting, cross-platform arbitrage, aggressive speculation, creating pseudo-financial schemes, toxic trading.
Rise of scam and criminal earnings: The CIS and Russia remain global leaders in cybercrime. In 2021, 74% of all ransomware revenue went to groups affiliated with Russia and the CIS – that’s more than $400 million. BBC and Chainalysis experts highlight Russian-language forums, multi-accounting, and laundering through crypto exchanges in Moscow City as key nodes of the crypto gray market.
The observations are confirmed by the largest international studies. American markets are an arena with a developed expert infrastructure, protection institutions, and collective knowledge, whereas the CIS market more often resembles hard PvP “every man for himself,” with a tilt toward shadow strategies amid a deficit of transparency and resources. This split shapes completely different approaches to making money, interacting, and ethics in financial markets.
You still need to earn, but engaging in black schemes with a guaranteed outcome is off the table. When discussing the ethics of multi-accounting or finding technical vulnerabilities in markets with uneven reward distribution, it’s important to take a comprehensive view and consider the following:
Large, multimillion-funded projects often use reward models that objectively don’t match the volume and value of users’ work (for example, minimal rewards for complex testing, uneven airdrop algorithms, opaque participation conditions).
When market participants face repeated underpricing of their contribution, it becomes natural to look for compensatory strategies that sometimes fall outside classical boundaries.
Users implement multi-accounting not to destroy ecosystems, but to compensate for the imbalance between effort and the final reward. This indicates flexible thinking and a search for optimal ways to survive in a highly competitive and non-transparent market – especially in countries with limited economic opportunities.
Globally, it’s customary that the strongest participant sets the rules of the game (in this case – the project or team). If a project initially builds its economy on underpayment or “invisible slavery” of participants, then the unethical aspect shifts much more toward the organizers than toward users who seek to “pull up” their share through technical ingenuity and multi-strategies.
Implementing strict anti-multi-accounting measures and fair bug bounty programs increases the market’s democracy and safety for everyone, and proactive discovery of “loopholes” reveals a product’s real maturity and encourages teams to treat their communities fairly.
In many markets, it is precisely the “hunger” for fair incentives that forms classes of top specialists.
As long as the market keeps obvious provocations toward unfair play (undervalued labor, unequal conditions, unfair resource distribution), any sanctions against multi-accounting or technical initiative are merely reactions by the sides to systemic imbalance and a symptom of a deeper problem – not a pure manifestation of “criminality” on one side and “holiness” on the other.
The uninformed and the informed
“It’s not what you know, it’s who you know.”
After the loud scandal around bets on the color of Zelensky’s suit at his meeting with Trump, we realized – insider trading on prediction markets has become a systemic problem. Someone clearly knew the result in advance, and this wasn’t an isolated case.
There is a free resource that tracks suspicious wallets on Polymarket. But their methodology seemed superficial to us – they focused on the size of bets and the timing of entries. Real insiders are smarter. They disguise themselves with small amounts, use multiple wallets, and avoid obvious patterns.
We decided to dig deeper.
Methodology: three key metrics
After analyzing hundreds of suspicious transactions, we identified three critical metrics that reveal insider activity:
- Initial concentration
The percentage of purchases by wallets that traded only in one or two similar markets. The logic is simple: if a wallet was created specifically for a particular event, the owner is likely to have insider information about that question.
Regular traders diversify activity. Insiders concentrate on what they know for sure. - Volume concentration
The percentage of purchases by wallets with minimal total trading volume over their entire existence. Most insiders are not professional traders – they are people with access to non-public information who decided to profit from it.
Their wallets show minimal trading history but anomalously precise entries in specific positions. - Market concentration
The percentage of purchases by wallets that made more than 50% of their total trading volume in a single market. This pattern is especially telling – normal traders spread risk, insiders go “all-in” where they’re confident in the outcome.
Results: from the obvious to the hidden
Applying these metrics to Polymarket’s top markets, we got a list of the 25 most suspicious events. The result exceeded expectations.
Confirmed insiders
Among our findings were all the markets the X community had already labeled as insider-driven:
- GPT-5 markets with different launch dates – multiple wallets bet on the same release windows
- U.S. military action against Iran – activity began days before official statements
- Israeli military action against Iran – confirmed insider trading
- Thai strikes on Cambodia – X’s suspicions proved justified
- Zelensky’s suit – our starting point
Hidden insiders
But most interestingly, we found markets that perfectly fit insider knowledge but had not previously attracted attention:
- Pump Fun announces a public round that sells out in the first hour? – Someone knew the exact parameters of the round and the announcement time. The concentration of suspicious wallets reached 70%.
- Will MicroStrategy buy Bitcoin between May 20 and 26? – Corporate insiders had access to board decisions. The trading pattern is classic.
- Berachain airdrop in Q1 2025? – Information about token distribution dates is usually known to a narrow circle of developers and investors.
Event dynamics
On August 12, when we first noticed suspicious activity, the probability of insider trading was about 70%. By August 15, this figure jumped to 90%.
This dynamic is typical of markets with asymmetric information. First, the most informed participants enter, then their inner circle, and only afterward does the information become public.
Scale of the problem
Of the 25 markets analyzed, roughly 20 show patterns characteristic of insider trading. That’s 80% accuracy – an insanely high figure for algorithmic detection.
Of course, not all cases are necessarily classic insider trading. Some may result from skilled traders with superior information networks or analytical capabilities. But the statistical patterns are too obvious to explain by chance.
What this means for prediction markets
Our research shows a systemic problem with Polymarket and similar platforms. Prediction markets are positioned as tools for aggregating collective opinion, but in reality, they often become venues for monetizing insider information.
This is not only unfair to ordinary participants – it also distorts the very essence of prediction markets: obtaining an objective assessment of event probabilities.
Technical implementation
The algorithm works in real time, analyzing each transaction through the lens of our three metrics. We plan to make the tool publicly available – let the community track suspicious activity on its own.
Transparency is the only way to cleanse prediction markets of manipulation.
Next steps
This is just the beginning of the research. We continue monitoring activity, improving the algorithm, and preparing to publish a detailed technical report with open-source code.
Prediction markets can become a powerful forecasting tool, but only if they are fair. Our task is to make them so.
Story by @denymbas x @q_anyway
While the crypto community was busy farming popular memecoins, we noticed that the value of points in the Eclipse project dropped sharply. Over two weeks, their price fell 4x. The reason was the introduction of a new system of boosts that most farmers ignored.
Most market participants made three key mistakes:
- Ignored changes in mechanics: They paid $40–50 for 100k points, even though with the new boosts the same result could be achieved for $10–12.
- Underestimated the boost system: They didn’t understand how multipliers worked and got 100k points instead of a possible 400k.
- Didn’t use automation: Manual work didn’t allow them to scale the strategy and make full use of the opportunities.
Our strategy: Automation
We automated the entire process of obtaining points, which allowed us to act quickly and efficiently. Our strategy included:
- Automatic funding via Eclipse Relay for fast and cheap delivery of assets.
- ADS: working with Discord/Twitter accounts, replacing tokens from accounts + extraction.
- Running activity through the tap app with software.
- Activating all boosts: We configured the system to get up to a 9x multiplier, turning 100k base points into 900k final points.
One full cycle that others performed manually took us a few minutes. While others were clicking for hours.
Result: Top positions with minimal investment
By investing only $1,000, we were guaranteed a top-20 wallet position in the project. Under old conditions, this would have required $3,000–4,000. High positions gave us:
- Priority token allocations at TGE (Token Generation Event).
- Hidden bonuses for top participants.
- Early access to new products.
We used several account tiers with different strategies: some conservative for stable farming with a 6x boost, others aggressive to maximize results with a 9x boost and to get into the top 10. This allowed us to manage risks.
Conclusions:
Our success was based on several key factors:
- Information advantage: We tracked all projects, including secondary ones.
- Technical preparation: Automation allowed us to scale the strategy.
- Contrarian approach: We acted when most of the market wasn’t paying attention to Eclipse.
Eclipse became an example of how information asymmetry, rapid action, and automation lead to maximum results with minimal risk. Our ROI was 8–12x compared to the standard approach to farming.
Such opportunities arise regularly. The main thing is to constantly monitor the market, automate processes, and not be afraid to go against the crowd.
The flip side: who lost
While some were earning on information asymmetry and technological advantage, thousands of other participants were taking losses by choosing the wrong strategies.
On Polymarket:
- Retail traders lost money by betting against insiders in obviously “fixed” markets
- Many tried to copy large bets but entered too late, when prices were already distorted
- Algorithmic bots without insider information bled capital trying to trade against informed participants
- Burned money in hopes of an airdrop
In Eclipse farming:
- Farmers who ignored updates overpaid 4–5x for the same points
- Those who worked manually spent hundreds of hours on what automation solved in minutes
- Participants who didn’t understand the boost system received 9x fewer points for the same costs
- Many tried to slip by on lower tiers and didn’t earn – at all
Systemic losses:
- By our estimates, ordinary participants lost more than $2 million on insider markets on Polymarket over the period analyzed.
- In Eclipse, the average farmer missed 60–80% of potential income due to inefficient strategies or even went into the red.
- Many projects with similar mechanics went unnoticed by the community, leading to missed profits in the millions of dollars.
These statistics underscore the importance of information advantage and technical preparation in the crypto space. The market harshly punishes ignorance and the unwillingness to adapt to changes.
All these stories lead to one key question: