As prediction markets continue to gain momentum, platforms such as Polymarket and Kalshi are driving event trading from niche applications toward broader market participation. Different platforms exhibit distinct characteristics in trading mechanisms, market coverage, funding systems, and compliance architectures, reflecting that the prediction market industry is still exploring new product forms. Building on the mature experience of existing markets, URIGHTMARKET further explores the integration of prediction trading, risk hedging, and copy-trading systems to provide users with a more diversified on-chain trading experience.
I. Starting from the Strengths of Existing Prediction Platforms to Identify New Product Space
Polymarket’ strengths lie in its crypto-native architecture, rich event markets, and on-chain asset-based trading and settlement model, covering politics, cryptocurrency, sports, economics, culture, and other domains. Its market prices can provide users with a reference for observing event expectations; however, the actual trading experience may still be affected by factors such as market depth, bid-ask spreads, event rules, and outcome disputes. Kalshi, by contrast, is distinguished by its exchange model and event-contract markets under the U.S. regulatory framework, establishing advantages in market rules, trading systems, and compliant operations. Nevertheless, different platforms vary in access conditions, capital utilization methods, market coverage, and product design, requiring users to choose according to their jurisdiction and specific trading needs.
The development of these platforms demonstrates that competition in prediction markets is no longer solely about the number of markets, but also involves liquidity, trading efficiency, risk management, and user experience. URIGHTMARKET aims to continue exploring these critical areas to form a product system with its own distinctive characteristics.
II. Exploring Hedging Mechanisms to Enable Prediction Markets to Serve Risk Management
Traditional prediction markets typically focus on judging event outcomes. However, for users who hold crypto assets, participate in futures trading, or monitor macroeconomic developments, prediction markets may also offer applications in risk management. URIGHTMARKET seeks to further explore the combination of prediction trading platforms with asset hedging. For example, when a user holds a certain amount of BTC and is concerned that a macroeconomic event may trigger a price decline, they can research YES/NO contracts related to that event or related market movements and evaluate whether to establish an opposite-direction position to diversify part of the potential risk. Similarly, if a user has taken a heavy position in one direction on BTC price movements on Polymarket and is concerned about the possibility of the opposite outcome, they may open a position in the opposite direction on the same event on URIGHTMARKET to partially diversify risk. Where correlations exist between different assets and events, users can also formulate corresponding strategies based on market prices, position size, and risk tolerance.
The key to this mechanism is not merely providing reverse trading but helping users understand the relationship between their existing asset exposures and prediction-market positions. Actual hedging effectiveness depends on correlation, price movements, liquidity, fees, and final settlement results, and cannot guarantee the complete offset of losses. Through richer market selection and trading tools, URIGHTMARKET aims to provide users with the possibility of researching and implementing risk-management strategies.
III. From Observing Excellent Traders to Systematic Copy Trading
In the existing prediction-market ecosystem, on-chain transaction records provide conditions for analyzing traders’ historical performance. However, observing wallet addresses, manually tracking trades, and automated copy trading are not the same. Taking Polymarket as an example, users can utilize public on-chain data to study trading behavior, but automated copy trading usually requires third-party tools or self-developed systems, and differences may exist in execution efficiency, capital management, and risk control.
URIGHTMARKET aims to treat the copy-trading system as a further product direction for exploration, enabling users to analyze trader performance, historical profit and loss, trading frequency, position changes, and risk levels, and—where rules permit—to follow trades according to set ratios and capital limits. A well-designed copy-trading system must also address practical issues such as execution price deviation, order delays, partial fills, insufficient liquidity, and position handling after stopping copy trading.
By combining the display of trading strategies with copy-trading execution, the platform seeks to lower the operational threshold for users researching trading behavior while retaining users’ autonomous control over copy-trading capital and risk limits. Copy trading does not mean replicating all returns, and historical performance cannot guarantee future results.