IIT Delhi quantifies skill in opinion trading through data and modeling

A recent study conducted by researchers at the Indian Institute of Technology (IIT) Delhi has offered a comprehensive analysis of "opinion trading" platforms, providing strong evidence that such activities are driven primarily by skill rather than chance. The research, titled “Quantifying Skill on Opinion Trading Platforms,” analyzes user behavior, trading outcomes, and mathematical models to assess the nature of skill in this emerging form of gamified information markets.

Opinion trading platforms facilitate the exchange of virtual contracts tied to the outcomes of future events, such as sports matches or elections. Each contract reflects a projected outcome for example, the expectation that a specific team will win a game. Users who hold contracts aligned with actual outcomes may realize profits, while those with incorrect projections incur losses. These platforms function in a manner akin to financial derivative markets, wherein users collectively assess and assign probabilities to real-world events.

Why Skill Matters Legally
In India, and many other jurisdictions, the legal status of games often hinges on the "predominance test" that is, whether skill or chance primarily influences outcomes. The IIT Delhi study sought to evaluate opinion trading against four widely accepted skill indicators:

1. Predominance of skill over chance
    
2. Consistency of player performance
    
3. Learning improvement over time
    
4. Presence of a skill gradient across the player base
    

Key Findings

1. Skill vs. Chance
Using both theoretical modeling and real-world market data, researchers found that skilled traders consistently outperform random strategies. Theoretical simulations showed that traders with even limited predictive insight could generate positive returns, while purely random traders often experienced net losses especially after accounting for platform fees.

An empirical “skill dilution” test was also performed, where event outcomes were randomly flipped with various probabilities. As randomness increased, traders' win rates and returns decreased significantly. The results demonstrated that success on these platforms cannot be attributed to luck alone, with statistical tests yielding extremely low p-values (as small as 10⁻¹⁰⁰), effectively ruling out chance as the dominant factor.

2. Performance Consistency
 The study analyzed trading data over an entire calendar year (2024), finding that users who performed well in one month often continued to perform well in subsequent months. Correlation coefficients for win rates and returns between months were in the range of 0.52 to 0.65 a high degree of consistency for such a large user base. A brief dip was observed during March–May, attributed to an influx of new users during a major sporting season, which temporarily increased variability.

3. Evidence of Learning
Researchers tracked over 37,000 new users and monitored their performance over their first 720 trades. Both win rates and returns improved with experience, especially during the initial phase, forming a curve commonly observed in skill-acquisition fields like chess or gaming. This "learning effect" was particularly pronounced among users who ultimately became high performers, suggesting that the most successful traders not only had innate ability but also learned faster.

4. Existence of a Skill Gradient
The presence of a "skill gradient" where some users consistently outperform others further supports the notion that opinion trading is not a game of chance. The study introduced a scoring mechanism known as the OpTraS (Opinion Trading Skill) score, which quantified individual users' trading success over time. This score showed a strong correlation with long-term performance, with top performers scoring significantly higher than average users. These differences persisted across various market conditions, further underscoring the role of skill.

Implications
The IIT Delhi findings contribute to the ongoing debate around the classification of opinion trading platforms. The robust analysis combining theory, large-scale data, and statistical validation presents a compelling case for recognizing opinion trading as a skill-based activity.

From a regulatory standpoint, these insights could influence how such platforms are governed under gaming and financial laws. Recognizing the role of skill may lead to clearer legal frameworks, user protections, and perhaps more innovation in the growing intersection of gaming, finance, and data-driven decision-making.

The full study, “Quantifying Skill on Opinion Trading Platforms,” is available through IIT Delhi’s institutional repository.