> For the complete documentation index, see [llms.txt](https://docs.orioleinsights.io/home/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.orioleinsights.io/home/whitepaper/core-mechanics-and-reward-system-of-oriole-insights/roi-and-initial-listing-prediction-markets/engage-with-roi-prediction-markets-and-earn-reputation.md).

# Engage with ROI Prediction Markets and Earn Reputation

Users can engage with the ROI Prediction Market by predicting how many times they believe the price of a token will increase after it becomes publicly tradable. For instance, if the public sale price of a token is set at $1, and a user predicts it will double in value, they would place a bet on a '2x' increase. This feature gauges the community's sentiment and collective expectations of a token's initial market performance.

A correct prediction would result in a reputational reward, encouraging informed betting and active participation in the market. Conversely, incorrect predictions serve as a learning curve, slightly diminishing one's reputation and offering insight into market trends and prediction strategies.

## Eligibility and requirements for participation in ROI & Initial Listing Prediction Markets

In the ROI Prediction Market of Oriole Insights, access to participate in specific projects is contingent on meeting certain eligibility requirements. Each user must attain a particular [**Level**](https://docs.orioleinsights.io/home/whitepaper/user-engagement-growth-and-gamification/levels-and-leveling-up-mechanism) within the platform, which ensures that participants have a foundational understanding and experience with the system's mechanics. Additionally, specific [**Badges**](https://docs.orioleinsights.io/home/whitepaper/core-mechanics-and-reward-system-of-oriole-insights/user-types-and-their-role-in-oriole-insights) may be required, which can serve as credentials symbolizing a user's expertise or previous achievements. 

These restrictions are project-dependent and are set to ensure that those engaging with the prediction are well-equipped to contribute meaningfully to the collective forecasting effort. Restrictions also prevent market manipulations and misleading the community by spamming predictions from just-registered users.