Crypto Futures Trade Arena: Revolutionizing Trading with VALR's Performance-Based Prizes

Wednesday, 23 October 2024, 13:00

Crypto enthusiasts will be thrilled as VALR launches its Futures Trade Arena, offering performance-based prizes. This innovative platform rewards traders based on their ROI and PnL, ensuring a level playing field for all participants. Starting on October 1, 2024, the competition promises exciting opportunities for both professional and retail traders in the cryptocurrency landscape.
Finbold
Crypto Futures Trade Arena: Revolutionizing Trading with VALR's Performance-Based Prizes

Unveiling VALR's Crypto Futures Trade Arena

VALR, a Pantera-backed cryptocurrency exchange, has launched the Futures Trade Arena, a groundbreaking trading platform that rewards participants based on their Return on Investment (ROI) and Profit and Loss (PnL) performance. Running from October 1, 2024, to at least April 30, 2025, this platform aims to level the playing field for investors.

Exclusive Monthly and Weekly Prizes

Participants in the Futures Trade Arena can win up to 120,000 Tether (USDT) in monthly prizes. The rewards will adjust based on the number of eligible participants. Top traders will compete for monthly winnings of between 2,000 and 10,000 USDT, while the top 10 weekly performers can secure prizes ranging from 25 to 2,880 USDT.

  • To qualify for the competition, traders must have traded at least $2,000 on VALR’s Futures pairs within 14 days before a Weekly Competition Round.
  • The competition includes Monthly Rounds made up of four Weekly Rounds, allowing traders multiple opportunities to win.

Fostering a Fair Trading Environment

VALR is prioritizing fairness and opportunity in its contest by excluding employees and contractors. This approach encourages an inclusive trading atmosphere where strategies take precedence over trade size.


This article was prepared using information from open sources in accordance with the principles of Ethical Policy. The editorial team is not responsible for absolute accuracy, as it relies on data from the sources referenced.


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