“How to DeFi: Advanced”: An article to understand the decentralized prediction market

The prediction market is an interesting area that allows users to hedge more specific risks and can also act as a poll

Note: This article is from Chapter 10 of Part III of “How to DeFi: Advanced”. Authors include Lucius Fang, Benjamin Hor, Erina Azmi and Khor Win Win.

“How to DeFi: Advanced” is an advanced version of the classic DeFi book “How to DeFi” published by CoinGecko. This book can be purchased through the official website or Amazon, and can also be redeemed by accumulating CoinGecko points, requiring 800 points.

In order to better spread DeFi-related knowledge, Babbitt will continue to translate the entire book. The following is the entire compilation of “Chapter 10: Decentralization Index”.

The prediction market is a market created for participants to place bets on the outcome of future events. A good example of the traditional prediction market is the sports betting platform.

The decentralized prediction market uses blockchain technology to create a prediction market of almost anything. For example, a prediction market can be created based on when the price of Bitcoin exceeds $100,000 or who is the next president of the United States.

Proponents of decentralized prediction markets believe that centralized platforms put users at a disadvantage. (Because) standard practices often have high transaction fees, delayed withdrawals and frozen accounts. In addition, most traditional betting platforms today are focused on sports betting, limiting the types of prediction markets that the public can use.

The decentralized prediction market protocol is designed to allow users to create their own markets, thereby empowering them.

How does the forecast agreement work?

Unlike traditional prediction markets, prediction protocols are decentralized and must rely on innovative methods to operate. We can roughly decompose the predicted protocol flow chart into two main parts.

  1. Market creation
  2. Market solution

Market creation

When creating a prediction market, there are two types of shares (result tokens) in the basic category of the market: YES (long) shares and NO (short) shares. The compensation is determined based on whether the event occurred.

In a simple prediction market, a single YES share (usually priced at 1 USD) requires a payment of 1 USD when the relevant event occurs, and 0 USD if the event does not occur. Correspondingly, if the event does not occur, each NO share needs to pay $1, and if the event occurs, it pays $0. Category-based markets can use this basic principle to create markets. For example, “BTC will exceed $100,000 before December 31, 2021?”

Another example of prediction is: “Who will be the President of the United States in 2025?”

In this case, there may be more than two options, for example:

A. Joe Biden

B. Kamala-Harris

C. Trump

The above function is similar to the basic category market, but includes three shares to represent three different answers instead of two. The price of the share is determined based on how much the buyer is willing to pay and how much the seller is willing to accept. In other words, the system is autonomous, and its ratio (that is, price) is determined by the market’s trade-off of probability.

On the other hand, a market with a series of answers and related rewards will operate in different ways. This kind of market is called a scalar market, and the results vary within certain parameters.

A good way to envision a scalar market is to treat it as a result of ownership and set out to determine who is the most right/wrong, rather than who is exactly right/wrong.

Here we use an example to illustrate. The assumption is as follows:

“What will the price of Bitcoin be on November 10, 2021?” The

accuracy is 10,000 USD and the range is 0-200,000 USD.

With this setting, the user can choose 10,000 USD , 20,000 U.S. dollars, 30,000 U.S. dollars, and so on.

Unlike the YES/NO and multiple-choice markets, the payouts in the scalar market are distributed to all participants. Each indemnity is based on the position of the price relative to the outcome. Therefore, if the price of BTC is $198,000 on the market closing date, the compensation will be distributed among all purchasers. However, the answer that is closest to the exercise price of $200,000 will receive the highest return amount proportional to their bet size.

For scalar markets, the price per share is converted into a specific exercise price of the relevant asset, or anything that is predicted.

Market solution

Using the same example as before, how to determine whether Bitcoin will exceed $100,000 before December 31, 2021? Is it referring to Coinbase or the total price of all exchanges on CoinGecko? In practice, the market maker will specify the source of the resolution before it is created. So in this case, Coinbase can be established as the source of resolution.

But the real question is who provides this information and how to verify it? For price-based markets, public APIs can be drawn and extracted from online materials. Oracles can also be used, but they may not cover all market types, such as “Will Vitalik Buterin get married before 2022?”

Considering the scale and scope of the prediction market, it is impossible to rely solely on technology. The forecast protocol recognizes this and relies on humans to ensure the accuracy of the information.

However, how to ensure that bad actors will not manipulate the market by providing false information? Unlike traditional prediction markets, prediction protocols are decentralized, and there are no resources to monitor and supervise each market. In order to solve this problem, the prediction protocol has proposed different solutions. We will introduce two examples in this chapter.

Forecast Market Agreement


"How to DeFi: Advanced": An article to understand the decentralized prediction market

Augur runs on the Ethereum network and uses a market solution model that encourages users to accurately report information through rewards and penalties. After the market is closed, it will enter a reporting period, and the market creator or others (depending on who is designated by the market creator as the designated reporter) can provide information to verify the results.

During the reporting period, the designated reporter (DR) will have 24 hours to submit a report on market results. It should be noted that DR must pledge the native tokens of the protocol before reporting their findings.

The protocol has two versions of local tokens: REP and REPv2. REPv2 tokens are only applicable to Augur’s v2 protocol update, while REP is transferable and can be exchanged for REPv2 tokens.

The key difference is that if there is a substantial dispute about the outcome, then REP holders may not participate in the fork. However, for the sake of simplicity, we will refer to them collectively as REP tokens because they are similar in function.

Any result selected by the DR becomes a provisional victory result (TOR). Once the DR submits the TOR, it can be disputed. The controversial result will start a one-week dispute period, and anyone with REP can pledge the answer they think is correct. One round lasts for one week, but up to 16 rounds can be reached.

If there is no dispute, part of the profit will be used to compensate DR. This fee rate is variable and is determined based on the total value of all REP tokens in circulation.

If there is a dispute, the user who bet on the winning result will get the share of the REP who bet on the losing result. This is on top of the fees that the reporter will receive. Users who lose the pledge will not receive any fees and lose all their REP tokens.


"How to DeFi: Advanced": An article to understand the decentralized prediction market

Omen is a prediction protocol developed by DXdao and driven by the Gnosis protocol – it runs on Ethereum and xDai sidechains. Gnosis allows Omen users to participate in their token framework, which is an event-based asset class that includes the building blocks of prediction markets.

Unlike Augur, Omen does not incentivize the community to report and resolve the market. Instead, they rely on a decentralized community-driven oracle called Reality.eth to verify real-world events for smart contracts.

Most markets will be resolved through Reality.eth, and community members will decide the theme based on the cost. Users on Reality.eth issue bonds for the results they choose, and they can be challenged by others posting new answers and double bonds. This situation may last for several cycles until the issuance ceases, and the answer is determined by the person who issued the bond last.

Once Reality.eth has completed their settlement obligations internally, they will provide the results to various Omen markets. If the Omen user is not satisfied with the results of the investigation, he/she can (via Reality.eth) appeal to the external arbitrator Kleros.

Kleros randomly selects jurors from the juror pool and provides incentives based on game theory to ensure that anonymous voters reach a consensus. Those who bet on the correct result collect money from those who bet on the wrong result (much like Augur).

It is worth noting that DXdao, the autonomous organization behind Omen, may also decide to play a role as a qualified arbitrator in the future.

What are the other key differences between Augur and Omen?

As we have just discussed, Augur and Omen have very different approaches in the solution process. Augur solves the problem of oracles by creating an ecosystem of incentives and punishments, and regulates the reliability of reported information. Omen outsourced their reporting requirements to an external DAO (using principles similar to Augur’s approach). In this sense, Augur is more self-sufficient.

In terms of liquidity, the Augur v2 market uses 0x’s off-chain order book-orders are collected off-chain and settled on-chain. In contrast, the operation of Omen’s automatic market maker is similar to DEX such as Uniswap, which creates a large liquidity pool for the token pair.

Although both result tokens use the ERC-1155 standard, Omen’s tokens can be packaged into the ERC-20 standard and accessed outside of its network-this allows Omen to access DEX and enter a larger liquidity pool . On the other hand, Augur’s resulting tokens are restricted to the internal liquidity pool of its agreement.

For a concise comparison between Augur and Omen, you can refer to the following table:

"How to DeFi: Advanced": An article to understand the decentralized prediction market

We are unable to obtain the market data of these two agreements, but if you browse the websites of these two agreements (conducted on April 28, 2021), you will find that there are very few activities.

"How to DeFi: Advanced": An article to understand the decentralized prediction market

For Augur, only seven markets were created. Only the top three have actual trading volume, and these trading volumes add up to less than $3,000.

"How to DeFi: Advanced": An article to understand the decentralized prediction market

As for Omen, there are only four markets, but with a combined trading volume of approximately $7,200 (not reflected in the picture, but shown on another webpage).

Related risks

The biggest concern of the prediction market is the reliability of the data. Although there are various profit-based incentives to minimize data manipulation, irrational actors may try to undermine the results. In addition, the questioned results can lead to time-consuming and expensive situations.

It is worth mentioning that

● Polymarket

As of April 2021, a test product of Polymarket has been launched on Ethereum. The white paper of the agreement has not yet been published, but it seems to be a hybrid structure of centralization and decentralization.

The agreement seems to be more popular than Augur or Omen-we found that there are more than 60 prediction markets on the agreement during a quick review on April 28, 2021, and market activity is booming. Among them, the transaction volume of the most popular market alone reached about 2 million US dollars.

to sum up

The prediction market is an interesting area because it has a meaning beyond gambling and allows users to hedge risks. Traditional derivatives allow buyers and sellers to hedge the risk of specific outcomes by holding the right to trade specific commodities at specific prices in the future. For example, a rice farmer can sign a derivative contract to sell 1,000 kilograms of rice for $5,000 on December 31, 2021, if he anticipates that the price will decrease during this period.

The prediction market can be based on anything, not just rice. Rice farmers may decide not to hedge the price of rice, but to hedge against the weather. In other words, prediction markets allow users to hedge more specific risks .

The forecast protocol provides a platform for anyone to hedge against anything. Not only that, the prediction market can also act as a “de facto” poll. Participants of the prediction protocol effectively share their opinions on different matters, and these opinions can be inferred to general insights on a wide range of topics.

Predicting the future of protocols is exciting because their principles can become the basis for use cases in real life. One can imagine using a similar settlement system to put legal contracts on the chain, because the function of the arbitration method is very similar to the jury-based judicial system. However, in the short term, we expect that more agreements can take advantage of the power of forecast agreements and use them to create innovative hedging tools.

Recommended reading

1. Basic knowledge of prediction markets https://augur.net/blog/prediction-markets

2. Prediction market pricing https://medium.com/veil-blog/a-guide-to-augur-market- economics-16c66d956b6c

3. How the prediction market is resistant to market manipulation https://blog.gnosis.pm/how-manipulation-resistant-are- prediction-markets-710e14033d62

4. The main difference between Augur and Omen https://blog.gnosis.pm/omen-and-the-next-generation-of- prediction-markets-2e7a2dd604e

Posted by:CoinYuppie,Reprinted with attribution to:https://coinyuppie.com/how-to-defi-advanced-an-article-to-understand-the-decentralized-prediction-market/
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