Gate News reports that on March 19, as institutional and quantitative funds continue to enter prediction markets, the industry trading structure is undergoing a transformation. Data shows that by March 2026, the monthly trading volume of prediction markets has surpassed $13.7 billion, with platforms like Polymarket gradually evolving into new battlegrounds for professional capital.
Analysts point out that prediction markets have shifted from early speculative behavior to strategy competition driven by quantification. Hedge funds are beginning to incorporate mature financial models to achieve stable returns. Six core methods have become mainstream frameworks.
First, the Logarithmic Market Scoring Rule (LMSR) is used to analyze pricing mechanisms, helping traders anticipate the market impact of orders. The Kelly criterion is employed to optimize position management by mathematically determining the proportion of funds for each trade, avoiding emotional decisions.
For opportunity identification, expected value gap scanning constructs independent probability models to find deviations between market prices and true probabilities; KL divergence captures inconsistencies across related markets to build hedging strategies. The Bregman projection extends to multi-outcome events, identifying complex pricing errors. Meanwhile, Bayesian updating dynamically adjusts probabilities based on new information, keeping strategies aligned with market changes.
On the technical side, quant teams typically access real-time data via APIs and use Python and related mathematical libraries for modeling and backtesting. Before deployment, forward-looking tests based on historical data are necessary to reduce overfitting risks. Automated execution systems often combine scheduled tasks with real-time alerts to improve response speed.
However, such strategies require high execution standards, including data quality, liquidity depth, and transaction cost control, all of which directly impact profitability. Industry insiders believe prediction markets are gradually evolving toward a professional structure similar to options and futures markets, but ordinary investors lacking modeling skills and discipline management will still find it difficult to replicate institutional advantages.
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