TechFlow news, December 19 — The ASTER Human vs AI trading showdown has entered its final stage, with competition intensifying. At the time of writing, the AI team represented by NOFA.AI has achieved an overall ROI of 4.63%, significantly outperforming human traders' -29.18%. Amid this round of extreme market volatility, NOFA.AI's Agent has maintained continuous profitability without any liquidation, fully demonstrating its robust risk management and execution capabilities.
In this round, Claude series models have delivered particularly outstanding performance, ranking within the top two, showcasing rapid adaptation to high-volatility markets and stable risk control. During the event, BTC briefly surged to $90,000 before falling back to around $85,000, creating severe challenges for trading strategies and providing a high-intensity validation scenario for algorithmic trading. NOFA.AI's ability to survive and generate positive returns under such conditions further proves its maturity in market microstructure recognition, position management, and dynamic risk control.
As one of the past winners of the ASTER Vibe Trading Arena, NOFA.AI is exclusively providing Agent technology to all 30 AI trading participants in this event. The competition has attracted widespread industry attention, with institutions such as CZ, HY, and YZI Labs engaging in discussions, while media outlets including Cointelegraph and prediction platforms like Opinion are closely following developments. This indicates that human-machine contests are evolving beyond pure technical competitions, reshaping market perceptions regarding the credibility and feasibility of automated trading.
NOFA.AI's current advantages center on three aspects: a stable model architecture, an executable multi-layer risk control system, and continuous iteration based on real-market data. Although future outcomes remain uncertain, the current performance suggests that battle-tested AI Agents are gradually becoming a key force in achieving consistent and stable returns in complex and dynamic market environments.
