Foreword: Predicting Market Emergence: Mechanisms Shape Probabilities
Throughout the history of financial markets, prices have always been the carriers of information. However, traditional financial markets can only reflect the present value of assets, but they cannot accurately quantify the probability of "future events" occurring.
In recent years, the booming gambling culture and various elections and wars have fueled the rise of prediction markets. Market estimates suggest that the online prediction market will exceed $150 billion within three years. Prediction markets allow users to earn high returns by betting on predictions. Coupled with the widespread adoption of cryptocurrencies and the integration of DeFi, which eliminates the need for traditional financial intermediaries and makes participation easier for global users, this trend of 100x betting in prediction markets stems from an era of increasing wealth inequality and a strong desire for asymmetric returns.
The success of prediction markets is not based on a pure probability game of events, but rather on transforming the uncertainty of future events into tradable assets. These assets operate in the form of information platforms where users can buy and sell "shares" representing the probabilities of events. This mechanism not only provides entertainment and speculative opportunities, but more importantly, it balances prices through consensus-building through buying and selling, extracting signals that are closest to the truth.
This article will use Polymarket as an example to illustrate how prediction markets use "mechanisms" to forge "price setting". It will analyze Polymarket's binary and multi-market models, explain the arbitrage opportunities and positive balance in the market, and reveal in detail how Polymarket uses its underlying pricing model to construct a decentralized "truth machine".
Polymarket Background
Polymarket is a non-custodial, decentralized prediction market platform founded in 2020 by Shayne Coplan and headquartered in Harmanton, New York. Built on the Polygon blockchain, Polymarket allows users to enjoy a low-cost and fast betting experience. Unlike traditional betting platforms, Polymarket does not act as a house; instead, it provides a peer-to-peer platform for users to place bets on topics such as politics, economics, sports, and cryptocurrencies.
Funding and Team Strength
Polymarket boasts a strong core team. Founder and CEO Shayne Coplan has extensive entrepreneurial experience, having participated in multiple tech startups; Chief Marketing Officer Matthew Modabber is responsible for brand promotion and user growth; and Head of Business Data Niraek Jain-Sharma focuses on data analytics and market insights. Polymarket's team emphasizes cross-disciplinary expertise, combining blockchain engineering, financial modeling, and marketing strategies to ensure the platform's stable future development.
Polymarket has secured backing from top-tier institutions. In 2024, the platform completed an $80 million Series A funding round led by Blockchain Capital; Founder Funds led a $195 million investment; and in 2025, Intercontinental Exchange made a $2 billion strategic investment, pushing Polymarket's valuation to $15 billion. This demonstrates the recognition of the market's prospects by traditional financial institutions. To date, Polymarket's total funding has reached $2.279 billion.
Current market data performance
According to the latest data from DefiLlama, Polymarket's monthly trading volume has reached $3.7 billion, making it the absolute leader in decentralized prediction markets. The platform covers a wide range of fields, including politics, cryptocurrencies, and sports, and emphasizes transparency and high liquidity. Its market share is gradually increasing.
Polymarket DefiLlama data
For more background information on Polymarket, please refer to this article.
The pricing foundation of Polymarkets: the constraints of "mathematics" and "money"
The pricing mechanism of prediction markets such as Polymarket is based on two fundamental constraints: the law of summation in mathematics and the principle of conservation of financial value. These two factors together ensure that the sum of event probabilities and the sum of prices achieve accurate pricing through the Gnosis Conditional Token Framework.
Mathematical constraint: Total probability 100%
In Polymarket, all possible outcomes of all probabilistic events are mutually exclusive and complete. For example, in the event "Will the candidate be elected?", there are only two outcomes: elected or not elected.
Let the probability of being elected be A, then the probability of not being elected is not A. According to the basic principles of probability theory:
P(Yes) + P(No) = P(A) + P(非A) = 1 （100%）
*P = Probability
This mathematical constraint is an inviolable hard law: if the market shows a 65% chance of being elected, then the chance of not being elected is 35%. If applied to a multi-faceted market with multiple outcomes, such as an election with multiple candidates, the sum of each person's chance of being elected will also be 100%.
Monetary constraint: $1 redemption guarantee
Polymarket uses Gnosis CTF as its underlying technical architecture. Under this framework, each prediction market issues two complementary condition tokens, Yes and No, as shown in the diagram below, with 0¢~100¢ representing a probability of 0~100%.
The Boundary Between 0 and 1: Probabilistic Mining
In the prediction market, where a $1 redemption guarantee is provided, Polymarket employs a "binary option"-style token structure to express the outcome of an event occurring (1) or not occurring (0).
When a user deposits $1 into the smart contract, the system performs a split to mint a complete set of resulting tokens:
$1 -> 1 Yes Token + 1 No Token
This minting process is risk-free and value-conserving because, regardless of the outcome after the event is settled, one of the Yes or No tokens will inevitably have a price of zero (0¢), while the other will have a value of $1 (100¢).
Merging
If a user holds both Yes and No tokens, they can merge them at any time, which is a common hedging technique.
1 Yes Token + 1 No Token -> $1
It is this mechanism of splitting and merging that establishes an unshakeable financial boundary for market prices. This is the $1 redemption guarantee, which simply means that the sum of the values of the Yes and No tokens with mutually exclusive results is 1.
V(Yes) + V(No) ≈ $1
*V = Value (Market Value)
Expectation value anchoring: price equals probability
Having established the monetary and mathematical constraint of $1, we need to understand why price is directly equivalent to probability. Expected Value (EV) becomes the key element in converting probability into price. Therefore, we say that Polymarket prices not only reflect market sentiment but also quantify the expected value of future events.
Suppose an investor is watching a binary market to see if "(Avatar) will gross more than $123 million this weekend." The film will be released from December 17th to 19th. Polymarket will use the box office data from the opening weekend of December 19th to 21st for its calculations.
Users can observe the daily box office data predictions on The Number website. If the box office is evenly distributed over the three days of the weekend, users can estimate the probability of the third day exceeding $123 million. The following assumes that the box office exceeds $123 million as A.
P(A) represents the true probability that the investor believes the box office will meet the target.
V(A) is the market price at which the box office target is met.
The expected return from purchasing >123M Yes tokens is:
EV(A) = P(A) x $1 + P(1-A) x $0 = $V(A)
In equilibrium, rational traders are willing to pay a price equal to their expected return and continue trading until the market price equals the expected value equals the probability of the event. Therefore, if the market collectively estimates the probability of box office success at 10%, the market price will be 10¢, as shown in the diagram below.
Discovering and Promoting Intrinsic Value
As we have learned above, the intrinsic value of tokens purchased on Polymarket will approach the probability of the event occurring infinitely. This anchoring mechanism ensures that the price equals the probability through the following dynamic process:
1. Price is lower than probability (V < P)
If the true probability is 70%, but the market price is only 60¢, the expected return is (0.7 – 0.6) x $1 ≈ $0.1, which is a 16.7% return. Traders will buy in large quantities and push the price up to 70¢.
2. Price is higher than probability (V > P)
If the true probability is 50%, but the market price is 60¢, the expected loss is (0.5 – 0.6) x $1 ≈ -$0.1, with a 20% loss rate. The trader would sell or short the price to 50¢.
Polymarket, through its numerous participants and capital, analyzes and engages in buying and selling games based on its informational advantage, driving V(A) to converge infinitely to the market's collective consensus probability P(A).
(Avatar) Box Office for the Three Days This Weekend
Dual Markets & Multi-Markets
The same principle applies to multi-market scenarios with multiple outcomes. If there are three outcomes, A, B, and C, the sum of their probabilities will also be 1.
EV(A) = P(A) x $1 + P(B) x $0 + P(C) x $0 = $V(A)
The Gnosis CTF framework ensures that the total value of all tokens is pegged to $1, such as $V(A) = 0.5, $V(B) = 0.2, and $V(C) = 0.3. Furthermore, professional traders utilize automated bots to execute buy and sell arbitrage by detecting biases, ensuring that Polymarket prices reflect more accurate probabilities.
Arbitrage Mechanism: Dutch Book Constraints
As mentioned in the article above, Polymarket prices are subject to a law that the sum of the prices of two mutually exclusive outcomes must approach $1, V(Yes) + V(No) ≈ $1. After the event settlement, a complete Yes + No combination will inevitably equal $1.
Since we know that this combination is guaranteed to be worth $1 after settlement, the current price should be close to $1. If this price deviates or the equation is broken, a "Dutch Book Arbitrage" opportunity will arise, and arbitrageurs will immediately intervene and force the price back down.
Mathematical proof
Suppose there is a temporary liquidity gap in the market, with V(Yes) = 60¢ and V(No) = 36¢. At this time, V(Yes) + V(No) = 96¢.
Cost = $0.6 + $0.36 = $0.96
Under Polymarket's $1 guaranteed redemption mechanism, regardless of the outcome, holding this portfolio will ultimately result in a $1 settlement and redemption.
Arbitrage yield
The net profit from the above arbitrage is calculated as $1 – $0.96 = $0.04, a single return of up to 4%. Such an amazing return has attracted the attention of many arbitrage users and institutions. Whenever a similar liquidity gap occurs in Polymarket, they will get involved in arbitrage.
Assuming that the combination V(Yes) + V(No) > $1 also applies to arbitrage, arbitrageurs would deposit USD to mint Yes + No token combinations and sell them, immediately profiting from the premium. This two-way arbitrage pressure forces the Polymarket to form a strong equilibrium, ensuring the market's continued stability at $1.
Risk premium: Price risk fee adjustment
Although the expected value theory anchors prices to probability, careful observers will surely notice that Polymarket's prices deviate slightly from, and are lower than, the predictions of polling organizations such as Five Thirty-Eight.
This situation does not represent market failure, but rather the risk premium inherent in on-chain prediction markets. When investing, traders not only bear the probability risk of the event itself, but also a series of platform structural risks, such as oracle pricing errors, smart contract attacks, platform regulatory crackdowns, etc. In order to bear these unhedged factors, they demand a "discounted price" as compensation, which is called the risk premium in prediction markets.
In practical pricing models, we can introduce a correction parameter λ using the following formula:
$V(A) = $Q(A) – / λ
$V(A): Asset market price.
$Q(A): The price corresponding to the true probability of information.
λ: Compound risk premium cost
The λ composite risk premium consists of the following variables:
Smart contract risk: the probability of the code being hacked.
Oracle risk: The probability of disputes or errors occurring during oracle settlement.
Decoupling risk: The risk that USDC-settled stablecoins will lose their 1:1 peg.
Regulatory risks: Liquidity premium due to platform funds being locked or front-end being shut down.
Therefore, when the actual probability of an event in a poll is 55%, but the price on Polymarket is 52¢, it means that traders are pricing the risk premium of λ at 3% after considering the compound risk. This premium usually shrinks as uncertainty decreases as the settlement date approaches. If you believe that the market has overestimated the risk, this 3% premium is your potential for excess returns.
Polymarket Pricing Structure: CLOB's Victory
Polymarket consistently offers the best prices and stable liquidity slippage thanks to its Central Limit Order Book (CLOB) architecture and well-designed market maker incentive mechanism, which combines on-chain settlement with off-chain matching to optimize efficiency.
Advantages of CLOB architecture
Early prediction markets, such as Augur 2, like most trading platforms, mostly used the Automated Market Maker (AMM) mechanism. However, Polymarket innovatively adopted the CLOB hybrid model, which improves upon the following advantages.
1. Capital efficiency
The traditional AMM model spreads funds across the entire equity curve, resulting in high slippage of about 2 to 30 basis points. In contrast, CLOB allows market makers to concentrate liquidity near the current price, thereby increasing trading depth. CLOB has an average slippage of about 2 to 3 basis points, and for large traders, CLOB can reduce transaction costs by 90%.
2. Unified order book
Polymarket's backend employs a unique architecture: when a user places a "Buy Yes 60¢" limit order, the system automatically displays a "Sell No 40¢" on the other side of the order book. This mirrored mapping represents shared liquidity; regardless of whether a trader is bullish or bearish, they share a unified order book, preventing price deviations caused by AMM curve pricing.
3. Hybrid Architecture Design
Polymarket order matching is completed off-chain, which can improve speed and reduce gas fees. Final settlement is executed on the Polygon chain to ensure transparency and immutability. The platform will bear the gas fees, allowing users to enjoy zero-fee transactions.
Market maker incentive mechanism
Polymarket incentivizes professional market makers to provide liquidity through a secondary rating reward system. The reward index is R ∝ (spread quality)², meaning that the reward R has a quadratic relationship with the quality of the bid-ask spread provided by the market maker. The smaller the spread, the more exponentially the reward grows. Market makers who can consistently place orders at the best bid-ask prices can obtain the highest returns, and the reward pool comes from the platform's profit fees.
Polymarket's incentive mechanism ensures that market makers continuously compete to provide the best quotes, keeping market spreads at 0.1-0.3% in the long term. Polymarket does not charge any transaction fees; all revenue comes from USDC interest income from platform holdings, the time value of unsettled markets, and potential data API licensing fees.
The Polymarket model significantly lowers the barrier to entry for users, attracting a large number of traders and market makers, thus creating a positive cycle.
Conclusion: Decentralized truth machines combined with arbitrage-driven efficiency
Polymarket's success lies not only in its betting nature as a prediction market, but also in its essence as a decentralized truth-discovering machine. Through ingenious mechanism design, Polymarket aggregates globally dispersed information and judgments into quantifiable probabilities, providing a collective prediction that is closest to the truth for an uncertain future.
Polymarket ensures the conservation of the sum of probabilities through the dual constraints of mathematics and money in the Gnosis CTF framework. It establishes a link between price and probability by anchoring to expected value and maximizes capital efficiency with its CLOB order book structure. Arbitrageurs act as "scavengers" in the prediction market, their pursuit of arbitrage unintentionally correcting price deviations. The dynamic adjustment of the risk premium reflects traders' rational assessment of systemic risk. These combined advantages make Polymarket the most liquid and price-efficient online prediction market today.
As the prediction market grows to over $100 billion, prediction platforms like Polymarket will continue to evolve, providing a source of truth based on "stakeholder interests" in this information overload era rife with misinformation and bias, allowing money to vote for truth and the market to price the future.
Predicting market value: "Utilizing human greed to serve the discovery of truth."
The future applications of prediction markets will extend far beyond politics and sports, reaching fields such as corporate decision-making and scientific research. As probabilities are increasingly priced accurately, uncertainty becomes a manageable asset. Polymarket, through "mechanism-driven probability," is writing a new chapter in decentralized prediction.
This report is for informational purposes only and does not constitute investment advice or a basis for decision-making. The data, analysis, and opinions cited are based on the author's research and publicly available sources and may be subject to uncertainty or change. Readers should make their own investment decisions based on their individual circumstances and risk tolerance. For further guidance, it is recommended to seek professional advice.
