Unlocking prediction markets potential: Roundtable with Azuro, Polygon and Gnosis

Decentralized prediction markets provide a transparent and efficient way to play everything from political events and sports outcomes to crypto prices and even Taylor Swift’s life details.

🇺🇸 Betting on whether Barron Trump launched $DJT?

After you listen the AMA with @azuroprotocol, you’ll learn how to use your knowledge of prediction markets to your advantage.

[Brought to you by Azuro]https://t.co/VF9O7BkGzV

— Cointelegraph (@Cointelegraph) June 20, 2024

A recent X Spaces session hosted by Cointelegraph Accelerator brought together participants and partners to discuss the role of prediction markets in the crypto space.

The conversation focused on the reasons behind the recent uptick in activity, the challenges these markets face, and how artificial intelligence (AI) might play a role in the future. Additionally, the discussion explored how Azuro’s passive liquidity approach and oracles offer potential solutions to existing problems.

Prediction markets gaining traction

Sandeep Nailwal, co-founder of Polygon and CBO of Polygon Labs

I think it’s the fundamental human desire to put money on opinions, so the interest in prediction markets has always existed. However, prediction markets in Web3 are different from Web2 because they experience more pronounced cycles.

Major events, like elections or the World Cup, drive activity across all prediction markets, especially in Web3.

Stefan George, co-founder and chief technology officer of Gnosis

The current bull market has brought heightened attention and significant financial resources to prediction markets, making them more attractive to participants. Elections, particularly those in the United States, have historically been a major driver of prediction market activity. However, the dependence on a single event highlights a potential weakness – a lack of diversification. Ideally, the market would offer a wider range of engaging events.

Rossen, core contributor at Azuro protocol

Compared to earlier years, the blockchain space has matured significantly. Lower transaction costs, improved infrastructure, and better user interfaces contribute to a more user-friendly experience.

What has made the most impact is passive liquidity. Prediction markets traditionally relied on peer-to-peer (P2P) models or active liquidity management by entities like Polymarket. They struggle with smaller, niche markets. In contrast, passive liquidity allows for a wider range of markets like sports to be viable, as liquidity is readily available. With passive liquidity, which we also utilize in Azuro, all markets can become liquid and price themselves correctly, fundamentally changing the user experience.

Liquidity challenges

Stefan George

Liquidity has been tough due to the capital costs involved in providing it, as returns are only viable if there’s enough trading activity. Predicting where the most activity will happen was a risk, often resulting in losses.

Market making is another hurdle. Successful trading on diverse markets requires sophisticated algorithms, especially for big or recurring events like U.S. elections or sports. While automated market makers exist, they don’t perform as well as specialized algorithms.

Rossen

In P2P prediction markets, you need another person on the opposite side of your bet. This approach is quite challenging, especially for niche or short-term markets, because finding a counterparty is tough. The peer-to-pool approach is different: here, liquidity is provided by a pool, much like in decentralized finance (DeFi).

This pool, filled with assets like USDT, provides liquidity for various markets priced by an oracle. The oracle doesn’t trade but provides market prices, ensuring there’s always liquidity for users. It means that markets are always liquid, similar to an AMM, but tailored for prediction markets.

We’ve successfully deployed sizable liquidity pools on Gnosis and Polygon for nearly two years, with the Polygon pool currently delivering a 20% return. This is significant because it demonstrates a sustainable model in which liquidity providers aren’t losing money.

Additionally, Azuro functions as a middleware layer within the blockchain infrastructure, providing liquidity and oracle solutions without being a direct application. This setup allows developers to easily build their own decentralized apps (DApps), websites or bots using Azuro’s protocol.

Sandeep Nailwal

As an infrastructure provider, we focus on creating an environment where builders can innovate. Prediction markets are a prime example, which we see as one of the key areas for growth. Polygon offers several advantages for them: a large retail user base, low gas fees for smooth user experiences, and decent on-ramps and off-ramps to attract new users.

Azuro’s place in the industry

Rossen

Right now, we’re heavily focused on sports prediction markets, with plans to expand into politics and social markets. We’re seeing various implementations of our technology, including web applications and Telegram bots, which offer seamless user experiences within the Telegram environment. DEXs and wallets are also interested in integrating Azuro to enhance user engagement, as these platforms compete to retain and attract users by offering more interactive and engaging features.

Moreover, we’re looking at potential collaborations with tier-one DEXs and wallet providers later this year. In the future, I see exciting opportunities in creating derivative products that leverage Azuro’s liquidity and oracle solutions. These could include leveraged trading and more adventurous crypto products.

I’m also particularly excited about integrating Azuro with gaming. Imagine playing a game where you can predict outcomes within the game itself. This adds a unique risk layer to gaming, providing a novel way for game economies to utilize their tokens and create more engaging experiences.

AI potential for prediction markets

Stefan George

Humans are limited in how we can price things and make concrete predictions. We think in binary terms, like “Trump will win” or “Trump won’t win,” but putting a specific probability on these outcomes is tough. Our framework allows for nested predictions, like Tesla’s share price based on whether Musk gets his pay package approved, but such complexity is beyond most people’s cognitive capacity.

AI changes the game by applying massive brainpower to make detailed predictions. We’ve been building and using different AI models for predictions on the Gnosis Chain. This is exciting because it opens up many more markets and allows us to better understand likely events. Multiple AI models competing in the market will give us the most accurate outcomes, leading to more liquidity and numerous new markets.

Rossen

We’ve been amazed at how quickly AI integrates into various fields, especially in market pricing and trading for sports. Many traders thought it would take longer, but with advancements like ChatGPT, it’s moving faster than expected. AI’s potential isn’t limited to market making; it can also enhance market curation. Interesting markets attract participation, so AI can help create more engaging markets.