VTWO - Trading Results AI Trading Agent, 60min
Description:
Overview: (VTWO) The investment seeks to track the performance of the Russell 2000® Index which measures the investment return of small-capitalization stocks in the United States. The fund advisor employs an indexing investment approach designed to track the performance of the Russell 2000® Index. The index is designed to measure the performance of small-capitalization stocks in the United States. The advisor attempts to replicate the target index by investing all, or substantially all, of its assets in the stocks that make up the index, holding each stock in approximately the same proportion as its weighting in the index.
Suitability: This robot is built to analyze and trade VTWO, making stock trading easier for beginners. It uses a combination of intraday and daily timeframes to provide a clear, structured, and user-friendly trading experience.
60-Minute ML Overview:
Tickeron’s Financial Learning Models (FLMs) represent a comprehensive integration of artificial intelligence and machine learning into the fabric of financial market analysis. In a 60-minute deep dive, one would explore how Tickeron’s models utilize complex algorithms trained on vast datasets to identify patterns, trends, and anomalies in the market. These models go beyond basic charting tools by combining advanced technical indicators with predictive analytics, allowing traders to anticipate potential price movements with enhanced accuracy. An in-depth session would cover the architecture of these models, the data sources feeding into them, and the continuous learning cycles that improve their accuracy over time. Additionally, users would examine the functionality of Tickeron’s trading agents, which include AI-generated buy/sell signals, strategy backtesting, and real-time risk assessment tools tailored for both novice and experienced traders. The session would also delve into regulatory considerations, ethical AI practices, and the implications of AI-driven trading in modern financial ecosystems.
Strategic Features and Technical Basis
The AI Trading Agent combines advanced pattern recognition with cutting-edge Financial Learning Models (FLMs) to deliver precise and adaptive trading strategies.
- 60-Minute Pattern Recognition: Entry signals are generated on the 60-minute (M60) chart based on high-frequency pattern analysis.
- FLM-Based Trend Filtering: Financial Learning Models validate price trends and reduce market noise, increasing the accuracy of trade signals.
- ML-Powered Optimization: Machine Learning enhances the detection of tradeable patterns and refines strategy execution for optimal performance.
- Smart Swing Trading Strategy: The agent employs a swing trading approach—holding trades to capitalize on larger market moves, with exit signals confirmed on the daily timeframe.
- Automated Risk Management: Trade activity is capped at six open positions simultaneously, supported by real-time data monitoring and decision support.
Position and Risk Management:
Designed with novice traders in mind, the robot’s strategic integration of daily timeframe filters ensures reduced emotional trading and improved stability. Its AI-powered FLMs systematically assess market data, minimizing risks and maximizing gains by dynamically responding to market shifts. Users can develop confidence and skills while the system handles complex technical aspects.
Trading Dynamics and Specifications:
- Maximum Open Positions: High, enabling the robot to diversify across numerous trades and reduce risk through market exposure.
- 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): Medium, offering a balanced profit vs. drawdown scenario that makes it an ideal intermediate and expert.
- Optimal Market Condition Medium: 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
Actual Performance (82 days)
Simulated Performance
This Robot is recommended to be used when the markets are growing in general. The core algorithm makes only long The core algorithm makes only long