Author: NotDegenAmy, Derek, yiwei Source: Ocular Translation: Shan Oppa, Golden Finance

Background

Today , when people think of intelligence, the first thing that comes to mind may be the LLM model, namely GPT, Claude, Llama, etc.

But in fact, the market itself may be the best form of general intelligence, because it is essentially the synthesis of all behaviors. Artificial intelligence itself is trained on the vast amounts of information produced by the masses. Having said that, AI is passive, it requires goals and instructions (at least until we enter the world of true agents). To better leverage and express market intelligence, we need something that captures the changing minds of the crowd, something forward-looking.

Enter the prediction market. A prediction market is a platform where participants can buy and sell contracts based on their beliefs about the potential outcomes of future events. These events can be political (e.g. election results) and economic (e.g. interest rate changes), or entertainment and sports (e.g. match results).

The concept is not new – early forms of prediction markets are thought to date back to It existed more than 500 years ago and was mainly used to predict outcomes.

Prediction markets like Intrade and Betfair came to prominence in the early 2000s, especially during the U.S. presidential election. However, these are centralized platforms that are often limited by geographic restrictions, regulatory constraints, and the need for trusted intermediaries to manage funds and settle bets. This affects their ability to grow and expand.

For example, Intrade was forced to close in 2013. The U.S. Commodity Exchange and Futures Commission sued Intrade, requesting that Americans be banned from using the website, claiming that it illegally sold futures contracts. , which led to a sharp decline in its user numbers.

In the late 2010s, with the rise of blockchain technology, prediction markets resurfaced stronger than before. This time, the platform leverages blockchain to create decentralized and global platforms that offer several advantages over past centralized versions:

However, prediction markets have never become mainstream. Until this year. There is renewed interest and focus in this new form of market intelligence due to the 2024 U.S. presidential election. In this article, we’ll take a deep dive into the mechanics of web3 prediction markets, covering 1) the use cases and current landscape of prediction markets; 2) the Polymarket case study; and 3) future trends.

1) Use Cases and Current Situation

In addition to providing users with the opportunity to profit from their views/predictions about the future, prediction markets have other use cases, As stated below:

DeFiLlama estimates that the current total value locked (TVL) of the web3 prediction market ) is approximately US$140 million. That's down from a pre-election high of $545 million.

In October 2024, the total monthly revenue from all prediction markets is estimated to be approximately $750,000, or approximately $9 million on an annualized basis.

The main players in this space are Polymarket, Azuro, and Drift (BET). Across the three companies, total wagering volume increased by more than 550% to $3.1 billion in the third quarter of 2024, compared with just $463.3 million in the second quarter of 2024 (see chart below).

(Source: CoinGecko and ocularvc)

In November 2024, there were approximately 290,000 monthly active traders on Polymarket alone, and more than 300,000 new accounts were opened on the platform. According to Polymarket's historical rankings, the most active traders on Polymarket generated $397 million in trading volume, while the most profitable traders earned over $22 million.

2a) Polymarket - Case Study

So how do prediction markets work? This can be divided into three sub-categories, namely its characteristics, charging model and dispute resolution process. Thanks to Polymarket is currently dominant and we will refer to its operating model.

Characteristics

Market - usually related to real-world events . Polymarket has a wide range of markets, from cryptocurrencies and cryptocurrencies to pop culture and weather results, while others may choose to specialize in a specific niche, such as sports betting.

Outcome - can be:

Multi-outcome markets are primarily characterized by binary outcomes . Some markets have multiple outcomes, but for each option (e.g. candidate) it will be a binary trade (see example below). Each side of the transaction has a probability/price, and after the event occurs, a portion of the correct outcome is redeemable for $1, while a portion of the incorrect outcome is worth $0.

Binary, such as whether an event will occur "yes" or "no";

Multiple outcomes, such as predicting which candidate will win a multi-candidate election or which team will win the championship; or

Continuous, which is predicting a range of values results (such as stock price or voting percentage).

Odds - There are two main ways to determine the price/odds in the market:< /p>

One ​​is through an order book system similar to the stock market. Participants submit buy and sell orders; the price is determined by matching these orders.

The second is through a system based on automated market makers (AMM). In this system, every buy and sell is accepted. Prices are automatically determined and adjusted based on algorithmic/mathematical formulas that track trading volume.

Polymarket primarily uses an order book-based system.

When the market was first established, there were initially no stocks and no predetermined prices or odds. Those interested in buying Yes or No stock can place a limit order at the price they are willing to pay.

When both "Yes" and "No" bid $1.00, the order is "matched" and the $1.00 will be converted into 1 share of "Yes" and 1 share of "No", respectively. Buyer owned.

For example, if you place a "Yes" limit order of $0.60, when someone places a $0.40 When a USD "No" order is placed, the order is matched.

The price shown on Polymarket is then the order book for the buy and sell. Midpoint of the spread - unless the spread exceeds $0.10, in which case the price of the last trade is used

As shown in the market below, 37%. The probability/price is 34¢ buy price and 40¢ The midpoint between the bid and ask prices. If the bid-ask spread is greater than 10¢, the probability/price is shown as the last traded price.

Payment - Polymarket runs on the Polygon blockchain and users place orders using USDC. Polymarket also recently partnered with MoonPay to allow users to purchase USDC using fiat currency.

Order - Polymarket Market, limit, and AMM orders are available. However, there is currently no leverage option, and Polymarket allows users to trade the stocks they own before the market-described event actually occurs. left;">Referring to the example above, let’s say we bought Ethereum “yes” shares at 37% odds when the price of Ethereum reached 3,000 USD. If the odds go up after we place the bet, we can decide to sell our shares at a higher price and lock in the profit before the actual event occurs/the deadline comes. Of course, it can also work if the odds go down after we place the bet. Choose to sell stocks at a loss

Fees

The main fees charged by decentralized prediction markets are. Two types:

Transaction fees, that is, the platform charges a small fee each time a transaction is executed.

Deposit/withdrawal fees, which are a small fee charged each time fiat/cryptocurrency enters or leaves the platform.

Polymarket currently no< No trading fees are charged, however, they take a 2% fee from the net proceeds from winning bets, instead Polymarket uses it to reward liquidity providers as their liquidity. as part of the Sexual Incentive Program) and pay Polymarket gas fees. There are also no deposit/withdrawal fees

When asked about the pricing strategy, Polymarket founder Shayne Coplan said in July 2024: "We are focused right now. To expand the market and provide the best user experience. We will focus on monetization later. ”

Dispute

In order to solve market problems after the event is over, platforms usually rely on 1) Oracle; and 2) community voting

In Polymarket's case, they use Universal Market Access (UMA)'s optimistic oracle and data verification mechanism ( DVM) Rely on both strategies. Here is a simplified diagram illustrating the market resolution process:

2b) Risks and Limitations

To date, there are varying views on the effectiveness of Polymarket and prediction markets as a whole as a source of market intelligence.

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Ocular It is believed that the prediction market needs to meet three conditions to serve as a source of intelligence:

First, when the three factors of incentives, capabilities and timing match, the prediction market can function Best effect.

About incentives: The individuals you survey need to have a vested interest in an issue. This could be because it affects their daily lives; their other investments; or it's a trending topic on social media and they want to get involved .The point is, they need to have a sense of involvement/involvement in the issue, whichso that they can participate in the market.

Ability: The public needs to have enough information to form their own opinions. It can’t be a topic that is too niche, or one that requires deep technical knowledge, because in that case the public may not be any wiser and the results will be unconvincing.

About time: While markets can start instantly, you need time to gather public opinion and allow the market to react to new information. Therefore, this is not suitable for time-sensitive decisions.

Second, there needs to be sufficient liquidity. Ultimately, prediction markets work best when they can truly harness the wisdom of the crowd. This means that the market needs to reach a certain size, both in terms of the number of relevant individuals participating and the volume of bets placed, in order to be meaningful and useful.

Third, it should not be used in isolation. Prediction markets are typically driven by publicly available information, such as mentions in the news or social media. Others may have private data sources that may not be fully reflected in the transaction, so it may be helpful to seek them out to get a different perspective.

3) Future trends

We see the trend of prediction market use case expansion:

Prediction market May be applicable to decision-making markets. Users vote on "what the outcome should be," not "what the outcome will be." Prediction markets, while providing valuable insights, are more passive. People vote and wait for the results to be known, often with little impact on the outcome. Decision-making markets, on the other hand, are more proactive and better suited for governance.

Case Study: MetaDAO ($META)

MetaDAO It is a project established in January 2023 and funded by Colosseum and Paradigm. Its core product is Futarchy, which proposes governance proposals for voting and launches 2 conditional trading markets at the same time:

When the market believes that the proposal will make the token When the value exceeds a certain threshold, they can bid up the price of the "passed" token. Instead, they will drive up the price of “failed” coins.

When the voting ends, if the TWAP price of the Pass tokenIf the price is 3% higher than the TWAP price of the Fail token, the proposal will be passed and implemented; otherwise, if the proposal fails, the market will return to its original state.

For example, the proposal could be to hire a new CEO for the company. If the decision market indicates that the value of the company's stock will increase significantly if the CEO is hired, then the proposal will pass and the CEO will be hired.

The overall idea of ​​the future system is as follows:

Futarchy was proposed by economist Robin Hanson in 2000. He proposed Futarchy as a governance model that combines prediction markets with traditional voting systems. In the Futarchy governance model, decisions are based on predictions from decentralized markets. Participants do not vote directly on , but on measurable goals such as economic growth. Prediction markets then predict how the proposal will affect these goals. Market-determined expectations that achieve the best results will be implemented. This approach uses collective intelligence and financial incentives to guide decisions.

Futarchy outperforms Polymarket's binary betting model in the following scenarios:

Decision-making It’s a goal, not just a prediction.

The complex, long-term effects must be considered.

Incentive structures need to be aligned with social or organizational goals.

Currently, MetaDAO collaborates with six projects for decision-making in addition to its own DAO governance. MetaDAO has shown some early signs of success with its decision-making, from preventing whales from buying $META at deep discounts to diverting company resources away from new initiatives that holders see as a distraction.

However, MetaDAO is still in its infancy. MetaDAO's model has several key limitations, and it remains to be seen whether it can be applied on a large scale:

Oracle - not every project has a token, andNot every decision outcome can be precisely measured using metrics. It can also be difficult to judge the impact on metrics for relatively small decisions.

Liquidity - Concentration of users and wallets may skew results. The user experience may also be too technical to be accessible to a wider audience, which may limit the number of voters.

Applicability - Powerful people may not want to hand over decision-making authority to the market. Participants must also be an informed group. How do we ensure users vote based on the long-term interests of the company?

In addition to MetaDAO, the prediction and decision-making market is also constantly developing and innovating:

New Markets – This year, prediction markets have generated a lot of hype and discussion as they coincide with the Olympics and the U.S. presidential election. The challenge for the industry is to maintain interest in prediction markets even after these cyclical events end. Platforms can consider expanding beyond seasonal/one-off events and explore different consumer groups and categories, such as pop culture and social media, to target female and youth participants.

Advanced Oracles - To establish a new market, you may need to build a new oracle to crawl and obtain relevant data to price the new market. Overlay is one such project that is looking to build oracles for unique markets, such as Counter-Strike skins and AI indices.

Efficient arbitrage - Many platforms use an order book-based system (i.e. buy and sell orders placed by users) to price the market. Because user behavior and overall liquidity can vary across markets and platforms, arbitrage opportunities exist both within and between platforms.

The following is an example of the odds for the October 28 US presidential election on Polymarket and Kalshi. Users can buy a Kamala-win contract on Polymarket (33% odds) and a Trump-win contract on Kalshi (62% odds) for a total cost of 95 cents. Given that the two events are mutually exclusive, the user will receive a $1 payout regardless of the outcome, resulting in a 5% arbitrage opportunity.

Ensure there are no duplicate or similarly worded listings on the platform;

Incorporate odds from other platforms into their pricing model; and/ Or

Build a trading bot to take advantage of such opportunities and minimize cross-platform spread

In order to effectively exploit these arbitrage opportunities, platforms may wish to:

Capital Efficiency - Currently, to execute trades on most platforms, users need to have capital on hand, and once the trade is executed, the capital is locked on the platform. To improve capital efficiency, platforms can consider:

Introduce leveraged products so that users can over-bet;

Allow the use of profitable stablecoins/ Tokens for trading;

Tokenize the user's position and allow the token to be traded on other platforms; and/or

Design a lending protocol that allows users to trade based on their own Lending and borrowing positions

Anti-manipulation- To address price manipulation, platforms could consider setting betting limits or limiting the number of accounts an individual can open. In smaller, less liquid markets, the use of cross-examination can also be effective: for example, asking “What do you believe and what do you think others believe?” What" and then compare the results.

Artificial Intelligence Participation- To make the resolution process (especially for simple markets) more efficient, platforms can consider leveraging AI/large language models to obtain and verify the information needed to resolve the market. AI agents can also be trained to research the truth more efficiently and effectively. Participate in future voting.

Conclusion

Ocular is paying close attention to the field of prediction markets and its development.

Today, prediction markets are used to generate revenue, hedge positions, engage the community, and gauge market sentiment. Going forward, it can be used for collective decision-making/governance and many more interesting areas:

Predicting the replicability of scientific papers;

Aggregating private information (within the company);

Predicting the success of drug trials;

Obtain estimates on subjective issues (pre-product launch testing); and

Reinvent news media – empowering reporters and analysts The teacher is involved.

While the industry has inefficiencies/constraints that need to be addressed (such as liquidity inconsistencies, regulatory uncertainty, and oracle issues), we remain The long-term outlook for the industry is optimistic, especially the overlap with artificial intelligence.