TSM + SOXS AI Trading Bot Double Agent

Overview: TSM Taiwan Semiconductor Manufacturing Co., Ltd. engages in the manufacture and sale of integrated circuits and wafer semiconductor devices. SOXS is a software suite that creates simulated X-ray observations of astrophysical sources. 

Suitability: This Double Agent (TSM, SOXS) is an advanced trading algorithm designed to capitalize on market trends using a dual-strategy approach. The bot integrates pattern trading on multiple timeframes—H1 (hourly), M30 (30-minute), and H4 (4-hour)—while employing proprietary algorithms based on the Daily timeframe as filters. It operates as a swing trader, leveraging intraday patterns for trade entries while utilizing the Daily timeframe for exit signals. The system can manage up to six open trades simultaneously, making it a suitable choice even for beginners.

Double Agent: The Double Agent Trading Bot is designed for traders seeking a robust and dynamic trading strategy that adapts to market fluctuations. Whether an asset is trending upward or downward, the bot ensures profitability by deploying two specialized agents:
 

Strategic Features and Technical Basis: The Double Agent Trading Bot employs a sophisticated pattern-based approach to trading. It operates on the following technical foundations:

• Pattern Trading Across Timeframes:
  • H1, M30, and H4 timeframes for detecting trading opportunities.
  • Daily timeframe filters for validating patterns and confirming exit signals.
• Proprietary Algorithmic Filtering:
  • Ensures high-probability trade setups by filtering noise and identifying true trends.
  • Uses Financial Learning Models (FLMs) to enhance pattern recognition.
• Swing Trading Mechanism:
  • Designed to hold trades for a period that maximizes profitability without excessive risk.
  • Entry signals based on intraday movements, while exits are determined by higher timeframe signals for precision.
• Automated Execution and Risk Controls:
  • Manages a maximum of six open trades at any given time.
  • Provides traders with real-time market insights and decision-making assistance.

Position and Risk Management

The Double Agent Trading Bot integrates risk management principles to optimize performance and safeguard capital:

• Dual-Agent Risk Hedging:
  • If market conditions change, the bot can seamlessly transition between the Momentum Agent and Inverse Agent, minimizing drawdowns.
  • Reduces reliance on single-direction trades, enhancing resilience in unpredictable markets.
• Financial Learning Models (FLMs) for Precision:
  • Developed under Tickeron’s AI-powered trading framework, incorporating advanced pattern recognition.
  • Tickeron, emphasizes the significance of AI-driven technical analysis in mitigating volatility risks.
• Beginner-Friendly and Adaptive Trading:
  • Designed for traders of all experience levels, with built-in automated decision-making features.
  • Focuses on high-liquidity stocks and ETFs to ensure fast execution and enhanced control in dynamic market conditions.

Trading Dynamics and Specifications:

• Maximum Open Positions: Low, maintaining focused and strategic trading rather than volume, which is suitable for managing high volatility with precision.
• Robot Volatility: Medium, offering a balanced approach between capturing significant market movements and mitigating sharp declines.
• Universe Diversification Score: Low, indicating a narrow array of instruments to hedge against sector-specific downturns and enhance profit opportunities.
• Profit to Dip Ratio (Profit/Drawdown): Profit to Dip Ratio (Profit/Drawdown): Medium, offering a balanced profit vs. drawdown scenario that makes it an ideal intermediates and experts.
• Optimal Market Condition: If the current market volatility is Medium then you should use the Best Robots in Medium Volatility Market (VIX is Medium - this indicator is coming soon).  

Disclaimer:  Disclaimers and Limitations 

Simulated Performance: All simulated performance results are derived solely from real-time calculations using historical data. Algorithms receive minute-by-minute historical prices and other data from Morningstar and generate trades in real time based on these historical inputs, effectively eliminating any hindsight bias. 

Actual Performance: All actual performance results are derived solely from real-time calculations using current data. Algorithms receive minute-by-minute current prices and other data from Morningstar and generate trades in real time based on these current inputs, effectively eliminating any hindsight bias. 

Gross Performance: Gross performance results do not deduct any fees or expenses. These results reflect the total returns generated by the AI Robots without considering the costs associated with accessing the service. 

Net Performance (current performance chart): Net performance results deduct fees to provide a more accurate representation of returns experienced by the user. These deductions can include: Model Fee Deduction: Net performance results may deduct a model fee equivalent to the highest subscription fee charged to the intended audience. Actual Subscription Fees: Net performance results may also deduct the actual subscription fees paid by the user for access to AI Robots.