Stock Picker: Return on Equity (ROE) (FA)

Overview and Suitability: This robot is a cutting-edge AI-driven robot specifically designed to leverage Fundamental Analysis (FA), offering a unique intersection of two sophisticated strategies: value investing and profitability-focused screening. Its core focus is on identifying companies that are not only undervalued but also exhibit strong financial health and potential for growth.

This robot is particularly well-suited for long-term investors and portfolio managers who prioritize fundamental strength over short-term technical signals. By focusing exclusively on fundamental metrics, the robot aims to deliver robust, data-driven decisions that filter out market noise and concentrate on the true financial health of companies. Ideal users include those who value a data-backed approach, seeking consistent performance with a balance between value and quality stocks.

Strategic Features and Technical Basis: The robot operates by synthesizing two key fundamental strategies, creating a powerful blend that filters stocks based on both value and profitability criteria. This unique fusion ensures that selected stocks are not only undervalued but also positioned for future growth. Below is a detailed breakdown of each strategy:

First Strategy: Graham Value Resonance

At its core, this strategy relies on the Graham Number principle, a concept rooted in the teachings of Benjamin Graham, the father of value investing. The strategy targets stocks trading below their intrinsic value, determined by a combination of earnings power and tangible asset value.

• Graham Number Calculation: The robot calculates the Graham Number to find stocks whose price is significantly below their fair value, focusing on those that the market has undervalued based on traditional metrics like earnings per share (EPS) and book value per share (BVPS).
• Undervalued Companies: The emphasis is on identifying companies whose market prices fail to reflect their solid financial foundation, providing an opportunity for strategic investments at discounted prices.

This approach helps the robot identify companies with strong fundamentals, reducing exposure to speculative stocks and emphasizing those with a solid earnings base.

Second Strategy: Quality Value Filter

The Quality Value Filter focuses on companies that demonstrate financial health and profitability, ensuring that the companies identified not only trade at reasonable valuations but also show evidence of capital efficiency and growth in profitability.

• Return on Equity (ROE): This metric is central to the strategy. The robot seeks companies with high and improving ROE, indicating strong financial management and the ability to generate profits from shareholder equity.
• Price-to-Book (P/B) Ratio: This factor ensures that the company’s market valuation is in line with its book value, screening for stocks that are fairly priced yet exhibit robust profitability metrics, particularly in industries where capital efficiency is key.
• Growth Potential: Companies with improving ROE and expanding profitability ratios signal future earnings growth, making them attractive targets for long-term value investors.

Combined Strategy Overview

The Trend Trader: Value-ROE Synthesis excels by merging the two approaches outlined above, targeting stocks that meet stringent value criteria while also displaying solid financial health and improving profitability. The robot identifies stocks that:

• Are fundamentally undervalued, ensuring a margin of safety based on the intrinsic valuation principles of the Graham strategy.
• Exhibit robust profitability metrics, with a focus on upward trends in ROE and earnings growth, ensuring that these stocks are not just cheap but financially strong and poised for growth.

This dual-layered approach provides a comprehensive analysis, allowing the robot to select companies that offer both value and quality, resulting in a balanced, fundamentally sound portfolio.

Position and Risk Management: Effective position and risk management is crucial to the long-term success of any trading strategy, and the Trend Trader: Value-ROE Synthesis includes stringent controls to protect capital while maximizing opportunities. Here’s how the system manages positions and risk:

• Maximum Open Trades: The robot is programmed to hold a maximum of 35 open trades at any given time. This diversification ensures that no single position overly influences the portfolio’s overall performance.
• Stop Loss Management: A fixed stop loss of 15% is applied to each position. This conservative stop loss threshold ensures that losses are minimized while allowing room for fluctuations in stock prices, essential for long-term value-oriented strategies.
• Execution Timing: All trades are executed using market orders within 1-2 hours after the market opens. This approach capitalizes on early market liquidity, helping to secure favorable entry prices and minimizing slippage.
• Risk Mitigation: By using a combination of stringent fundamental filters and risk management controls, the robot ensures that investments are not only based on sound financial metrics but also safeguarded against undue risk.

Trading Dynamics and Specifications:

• Maximum Open Positions: Medium, allowing for diversified exposure while managing concentration risk.
• Robot Volatility: Medium, offering a balanced approach between capturing significant market movements and mitigating sharp declines.
• Universe Diversification Score: High, indicating a broad array of instruments to hedge against sector-specific downturns and enhance profit opportunities.
• Profit to Dip Ratio (Profit/Drawdown): High, suitable for traders who are able to tolerate and manage greater levels of risk in exchange for potentially higher returns.
• Optimal Market Condition: This robot shows its best performance when market volatility is high, making it particularly adept at navigating turbulent market phases.

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.