KGC AI Trading Agent Reports +164% Annualized Return

AUSTIN, Texas - Nov. 13, 2025 - PRLog -- Tickeron, a global leader in AI-powered trading technology, announced outstanding performance results from its KGC AI Trading Agent. Over a 136-day period, the agent’s 15-minute strategy delivered an impressive +164% annualized return, generating $43,903 in closed P/L while trading Kinross Gold Corporation (KGC).

Company Overview and Strategic Fit

Kinross Gold (KGC), a major Canada-based gold producer, delivered approximately 2.1 million gold-equivalent ounces in 2024, supported by more than a decade of reserves. Operating mines across the Americas and West Africa, the company divested its Russian assets in 2022 and strengthened its portfolio with the high-potential Great Bear project—expected to produce over 500,000 ounces annually at top-quartile costs.

Tickeron’s AI Trading Agent is specifically calibrated for KGC’s price behavior, merging intraday and daily signals to offer a beginner-friendly yet institution-grade trading experience.

Breakthrough 15-Minute AI Strategy

Built on Tickeron’s proprietary Financial Learning Models (FLMs), the agent delivers a transformative 15-minute trading framework. These FLMs combine deep learning, adaptive pattern recognition, and advanced technical analysis to forecast trends in real time—removing emotional bias and refining trade execution.

Key capabilities include:

Ideal for beginners, the system offers clarity, discipline, and AI-driven consistency even in fast-changing markets.

Insight from Tickeron’s CEO

“Tickeron’s FLMs merge artificial intelligence with advanced technical analysis to help traders navigate volatility with confidence,” said Sergey Savastiouk, Ph.D., CEO of Tickeron. “Our high-liquidity, beginner-friendly agents empower users with transparent, real-time insights that support smarter, more controlled decision-making.”


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View all AI Trading Agents: AI Trading for Stock Market | Tickeron (https://tickeron.com/app/ai-robots/virtualagents/all/)

Disclaimers and Limitations

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