Recently, I've been paying more attention to prediction markets. The overall trading volume has skyrocketed from less than $100 million per month in 2024 to over $13 billion per month at its peak. Prediction markets have grown into a highly dynamic sector. The essence of prediction markets isn't about gambling (like sports betting or casino games); it's the infrastructure for pricing information. Understanding this is crucial—otherwise, it might be oversimplified and categorized as betting, which doesn't help in gaining deeper insights into prediction markets. From both mechanism design and data perspectives, the competition landscape in prediction markets is just beginning and far from reaching its endgame. As of now, Polymarket seems to be a disruptor, but it's facing strong competition from Opinion. Based on recent market trading volume data, Polymarket no longer holds an absolute advantage and is sometimes even surpassed by Opinion. Recent data from Opinion shows it has exceeded the trading volumes of both Polymarket and Kalshi. How this evolves in the future is something we can keep an eye on. For prediction markets, how can they gain a competitive edge? Here are a few key points: 1. Oracle reliability: Can disputes be minimized? This is extremely important. 2. User experience: User experience includes: - Quickly finding prediction events that interest users. For example, users interested in macroeconomic events might not be the same as those interested in sports predictions. - Liquidity depth: The more liquidity there is, the more funds (even institutional funds) it can attract. - Low transaction fees and speed. - Interaction barriers: Features like seamless participation interfaces. 3. Regulatory compliance and funding sources: Compliance helps expand the user base and attract large-scale institutional investors. 4. Community support: Trust from the community is also a key factor for the platform.