The post Season 1 of Aster’s Human vs AI Trading Battle Wraps Up ⋆ ZyCrypto appeared on BitcoinEthereumNews.com. Advertisement &nbsp &nbsp Disclaimer: The belowThe post Season 1 of Aster’s Human vs AI Trading Battle Wraps Up ⋆ ZyCrypto appeared on BitcoinEthereumNews.com. Advertisement &nbsp &nbsp Disclaimer: The below

Season 1 of Aster’s Human vs AI Trading Battle Wraps Up ⋆ ZyCrypto

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Disclaimer: The below article is sponsored, and the views in it do not represent those of ZyCrypto. Readers should conduct independent research before taking any actions related to the project mentioned in this piece. This article should not be regarded as investment advice.

Aster has announced the final results of its “Human vs AI” live trading competition. The event, conducted over a two-week period under highly volatile market conditions, clearly revealed the difference between discretionary human trading and AI-driven strategies.

Although human trader ProMint claimed the championship with positive net profits, AI demonstrated superior risk control. The human trading team recorded an overall ROI of -32.22%, reflecting significant performance dispersion across participants, while AI agents delivered significantly more stable results at the aggregate level, thus limiting total losses to approximately USD 13,000 and achieving an overall ROI of -4.48% across all participating AI strategies.

The competition data also highlighted a clear contrast in risk behavior between human traders and AI agents. In total, 43% of human participants were liquidated, while none of the 30 AI agents were liquidated, achieving a 100% survival and completion rate in the competition. 

Aster, the high-performance and privacy-focused on-chain trading platform backed by YZi Labs, said the competition’s outcome highlights the advantages of AI-driven strategies in stable, risk-controlled market environments, where systematic execution and disciplined risk management help mitigate large drawdowns.

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Conversely, the results also suggest that in market conditions driven by human emotion, rapid market shifts, and nonlinear price dynamics, discretionary human traders with strong judgment and narrative awareness can still capture asymmetric opportunities and outperform purely systematic approaches.

Aster further stressed that the competition was meant to reveal how human traders and AI can complement each other rather than to find which will replace the other. While AI is becoming a foundational tool for execution and risk management, human traders contribute judgment, context awareness, and narrative interpretation in complex market conditions. 

These varying strengths, Aster believes, mean future competitiveness will be driven by collaboration between humans and AI rather than direct confrontation. The goal of the competition was to observe how different trading participants behave on the same decentralized infrastructure under real market conditions, rather than relying on backtesting or simulated data.

Going forward, Aster intends to continue exploring infrastructure designs that better serve professional trading needs, enabling strategies, risk management, and execution to achieve greater on-chain certainty as the decentralized derivatives market continues to grow.

Leonard, CEO of Aster, in the post-event summary, said:

“This was not a competition with a predetermined conclusion, but a starting point. As markets become more complex, traders need more than individual tools. They need integrated systems that can evolve alongside the market.”

As season 1 of the competition comes to a close, Aster said the next season of live trading showdown will officially kick off on January 22 and take place on the Aster Chain Testnet. Participation will be open to a newly expanded group of traders, including professionals from around the world. More information on the upcoming event’s mechanics, rewards, and participation criteria is available in Aster’s official X competition announcement.

Source: https://zycrypto.com/season-1-of-asters-human-vs-ai-trading-battle-wraps-up/

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