Recently, the decentralized prediction market platform Polymarket has initiated a new round of talent recruitment aimed at forming an internal team focused on market-making strategies. This team will operate directly on Polymarket's proprietary trading platform, interacting with other traders on the platform by providing two-way quotes and increasing market depth. Although this model has sparked controversy in the practices of its competitor Kalshi, Polymarket still views it as a crucial strategic step to improve platform liquidity and user experience.
According to informed sources, Polymarket has approached several professionals with backgrounds in financial trading and the gambling industry, including seasoned traders from traditional sports betting and quantitative trading fields. The company hopes that by bringing in such talent, it can establish a professional market-making department capable of responding to market dynamics while maintaining stable platform operations. However, regarding specific recruitment progress and team operational details, Polymarket has not yet publicly commented, reflecting a cautious approach in advancing this plan.
In the field of prediction markets and information trading platforms, the design of market-making mechanisms has long been a subject of debate and exploration. Polymarket's main competitor, Kalshi, has long established an internal division called "Kalshi Trading," which actively quotes prices on its trading platform, essentially acting as the counterparty for some client trades. Kalshi executives have publicly explained that the primary goal of this division is to enhance market liquidity and narrow bid-ask spreads, thereby improving the trading experience for ordinary users. However, this practice has also drawn criticism from some users and industry observers. Critics point out that the platform's direct involvement in trading may create potential conflicts of interest, especially when the platform enjoys informational and systemic advantages that could pit it against ordinary users, making its operational model more akin to a traditional sportsbook rather than a neutral trading venue.
In fact, debates over the fairness of market-making activities have already manifested at the legal level. According to a proposed class-action lawsuit filed last month, the plaintiff accused Kalshi Trading of gaining an unfair trading advantage by setting odds structures unfavorable to clients. This lawsuit has further spurred industry reflection on the role and transparency of platforms in decentralized prediction markets, subjecting Polymarket, which is about to launch similar features, to stricter public scrutiny.
Despite the controversies, the role of market-making mechanisms in improving market efficiency is still valued by many platforms. For Polymarket, establishing an internal market-making team is not only a technical deployment but also crucial for the healthy development of its long-term ecosystem. Against the backdrop of decentralized prediction markets still being an emerging field, insufficient liquidity often remains a major bottleneck limiting user participation and market expansion. Through the operation of a professional market-making team, Polymarket aims to reduce irrational price spreads during market volatility, attract more institutional and retail users, and thereby drive sustainable growth in overall trading volume.
Furthermore, this move may also signal further expansion in Polymarket's product and market strategies. From sports events and political occurrences to macroeconomic trends and social phenomena, the scope of prediction market topics is gradually broadening, with their functions of hedging risks and price discovery gaining increasing attention. An active and stable internal market-making system can provide continuous quote support for various prediction contracts, helping users more easily express views and manage risks, thereby strengthening the platform's comprehensive competitiveness in the field of information derivatives trading.
However, maintaining procedural fairness and transparency while promoting market-making functions will become a core issue Polymarket must address. In the future, the platform may need to balance the commercial nature of market-making activities with user trust through clearer information disclosure, stricter internal risk controls, and decentralized safeguards at the technical level. Only by fully considering the prevention of conflicts of interest and the protection of user rights in its mechanism design can Polymarket advance more steadily and further in this new market phase.
Overall, Polymarket's formation of an internal market-making team is both a natural evolution in its development process and a reflection of the ongoing exploration in liquidity building and operational models within the prediction market industry. As this team gradually becomes operational, its actual effectiveness and industry responses will provide an important case study for observing the future development path of decentralized finance and prediction markets.
