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AI Double Trading Agent Yields 96% Annualized Return on AAPL/SOXS in 197 Days

AI Double Trading Agent Yields 96% Annualized Return on AAPL/SOXS in 197 Days

DUBAI, UAE - Sept. 18, 2025 - Tickeron, a leader in AI-driven financial technology, announces the remarkable performance of its AI Double Trading Agent, achieving a 96% annualized return over 197 days trading AAPL and SOXS. This innovative strategy combines Apple's long-term growth with the Direxion Daily Semiconductor Bear 3x Shares (SOXS) as a hedge, leveraging advanced Financial Learning Models (FLMs) and Machine Learning Models (MLMs).

Strategic AI-Powered Trading



The AI Double Trading Agent employs a 15- minute pattern recognition system, generating precise entry signals on the M15 chart. FLM-based trend filtering ensures accuracy by reducing market noise, while ML-powered optimization refines trade execution. The swing trading strategy capitalizes on larger market moves, with daily timeframe filters confirming exits, balancing profitability and stability.

Designed for All Traders

Built for accessibility, the robot simplifies trading for beginners while offering robust tools for experienced investors. It manages up to 10 open positions, supported by real-time analytics and automated risk management. The medium volatility approach and low universe diversification score enhance profit potential while mitigating sector-specific risks.

Revolutionizing Market Analysis

Sergey Savastiouk, Ph.D., CEO of Tickeron, states, "Our FLMs integrate AI with technical analysis to empower traders with actionable insights, reducing emotional decisions and optimizing outcomes." The platform's dual-perspective signal system provides clarity in fast-moving markets, making it ideal for medium volatility conditions.

About Tickeron

Tickeron pioneers AI-driven trading solutions, offering intuitive tools for beginners and sophisticated systems for active traders. Its real-time analytics and adaptive strategies redefine financial decision-making, delivering transparency and control

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