# Rewards

## Reward System

BullNBear is built to reward active users, traders, and community members who help grow the platform.

Users can earn through trading activity, referral activity, and future reward mechanics connected to the BullNBear ecosystem.

### Referral Rewards

BullNBear offers a referral system where users can earn from the trading fees generated by people they invite to the platform.

When someone joins BullNBear through your referral link and starts trading, you receive a share of the trading fees generated by their activity.

### Referral Fee Share

BullNBear referral rewards start at:

**40% of trading fees**

This means that for every eligible trade made by your referred users, you can receive 40% of the platform fee generated from that trade.

<figure><img src="/files/eYP2sP9QTJBGW5QVy9me" alt=""><figcaption></figcaption></figure>

### Future Rank System

BullNBear plans to introduce a Rank System that gives users more advantages based on their trading activity and platform volume.

With the Rank System, referral rewards may increase from:

**40% up to 50%**

The more users trade and participate on BullNBear, the more benefits they may unlock through higher ranks.

### Built for Active Users

The BullNBear reward system is designed to support users who actively trade, invite others, and help expand the ecosystem.

Instead of only using the platform, users can also benefit from its growth by referring traders, building communities, and participating in future reward programs.

{% hint style="info" %}
Referral rewards, rank benefits, and reward mechanics may be expanded over time as BullNBear continues to develop.
{% endhint %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://bullnbear.gitbook.io/trade/start-here/rewards.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.