After a decade of investing, I built a comprehensive AI-powered system to identify undervalued stocks. Objective: Find great companies that offer favorable entry points at scale.
Here's is summary of the methodology (feel free to ask the link to the detailed methodology by DM):
**Initial Filtering:**
* Focus on NYSE/NASDAQ for standardized reporting
* Exclude sectors requiring specialized analysis (Financial Services, Real Estate, Utilities, Healthcare)
* Apply minimum thresholds for market cap and volume and use sector-specific filters (ex: different expectations for Tech vs. mature industries)
**Peer Group Comparison:**
* Group stocks by market cap bracket and industry classification
* Rank companies on growth and profitability within their peer groups
* Eliminate bottom quartile performers across multiple metrics (avoiding value traps)
**Multi-Dimensional AI Analysis:**
1. **Financial Statement Analysis:** Three specialized AI agents analyze balance sheet, income statement, and cash flow independently
2. **Fundamental Synthesis:** Another agent integrates findings to assess real earnings power and cash generation capability
3. **Peer Comparison:** Evaluates relative valuation using sector-appropriate multiples and competitive positioning
4. **Technical Analysis:** Identifies momentum patterns and potential entry points
5. **Macro-Environmental Analysis:** Examines interest rate sensitivity and broader economic factors
6. **Insider Trading Assessment:** Analyzes buy/sell patterns of executives and major shareholders
**Why AI works:** The system leverages advanced LLMs (Claude and OpenAI latest models) to function like a team of specialized analysts without emotional biases or conflicts of interest. Example: investment banks that must serve both rated companies and investors (remember 2008's AAA-rated garbage).
This methodology has consistently helped me identify quality companies trading at fair prices.
I'm curious to know what metrics do you prioritize - for value investing - and why.