When to Trust (and Distrust) the Score
ShareValue.ai scores are powerful tools, but they're not perfect. Let's understand when to trust them and when to be skeptical.
When Scores Work Best ✅
1. Stable, Mature Companies
Companies with:
- Long operating history
- Consistent financials
- Predictable business models
Why: Historical data is reliable and likely to continue.
2. Normal Market Conditions
When markets are:
- Functioning normally
- Not in crisis mode
- Reasonably efficient
Why: Scores assume rational pricing will eventually prevail.
3. Comparing Similar Companies
When evaluating:
- Companies in the same sector
- Similar business models
- Comparable size
Why: Apples-to-apples comparison is most meaningful.
4. As a Starting Point
When using scores to:
- Screen for candidates
- Identify areas to research
- Compare alternatives
Why: Scores narrow the universe efficiently.
The GPS
GPS is great for navigation, but:
- It doesn't know about road construction
- It can't see traffic in real-time (older models)
- It might route you through a bad neighborhood
You still need to use judgment. ShareValue.ai scores are similar—helpful guides, not infallible oracles.
When to Be Skeptical
1. Rapidly Changing Situations
Be cautious when:
- Company is undergoing major transformation
- Industry is being disrupted
- Recent management change
Why: Historical data may not reflect the future.
2. Extreme Events
During:
- Market crashes
- Sector bubbles
- Company crises
Why: Normal patterns break down in extremes.
3. Special Situations
For:
- Turnarounds
- Spin-offs
- Mergers/acquisitions
- Restructurings
Why: Standard metrics may not apply.
4. Very Small Companies
Micro-caps with:
- Limited trading volume
- Sparse analyst coverage
- Volatile financials
Why: Data may be less reliable, manipulation possible.
Key Takeaways
- Scores work best for stable companies in normal conditions
- Be skeptical during rapid change or extreme events
- Scores are starting points, not final answers
- Always combine quantitative scores with qualitative research
What Scores Can't Capture
1. Future Events
- Earnings surprises
- New product launches
- Competitive threats
- Regulatory changes
2. Qualitative Factors
- Management quality
- Corporate culture
- Innovation pipeline
- Customer satisfaction
3. Macro Factors
- Interest rate changes
- Recession timing
- Geopolitical events
- Currency movements
4. Sentiment Shifts
- Narrative changes
- Investor psychology
- Momentum reversals
The 80/20 Rule
Scores can probably get you 80% of the way to a good decision. The last 20% requires:
- Reading about the company
- Understanding the industry
- Assessing management
- Considering macro factors
Don't skip the 20%.
Combining Scores with Research
The Ideal Process
- Screen with scores — Find high-scoring candidates
- Read the AI thesis — Understand the story
- Check recent news — Any developments?
- Review financials — Confirm the numbers
- Assess qualitatively — Management, competition, trends
- Make your decision — Informed by all inputs
Red Flags to Investigate
Even with high scores, dig deeper if:
- The company is unfamiliar to you
- The sector is outside your expertise
- Recent news seems concerning
- Something feels "too good to be true"
Trust But Verify
Trust the scores for:
- Efficient screening
- Relative comparisons
- Identifying outliers
- Tracking changes over time
Verify independently:
- Why is the score high/low?
- What could go wrong?
- What are analysts saying?
- Does the story make sense?
Score Reliance Traps
- Buying solely based on high scores
- Ignoring qualitative red flags
- Assuming scores predict the future
- Not understanding the business behind the score
The Bottom Line
ShareValue.ai scores are powerful tools, not crystal balls.
Use them to:
- Save time screening
- Identify opportunities
- Compare alternatives
- Monitor your portfolio
But always:
- Do your own research
- Understand the business
- Consider what could go wrong
- Make informed decisions
Congratulations! You've completed Track 2: Understanding the Scores!
You now deeply understand:
- Valuation Score and its metrics
- Quality Score and business fundamentals
- Growth and Health Scores
- The Final Score and signals
- When to trust (and question) the analysis
Next Track: Practical Investing—applying everything you've learned.