openclaw-backups/skills/us-market-bubble-detector/CHANGELOG.md

US Market Bubble Detector - Changelog

Version 2.1 (November 3, 2025)

Critical Issue Fixed

Problem Identified: v2.0 allowed excessive qualitative adjustments based on unmeasured "narratives" and subjective impressions, leading to inflated bubble risk scores.

Example Case (Nov 3, 2025):

• Quantitative Score (Phase 2): 9 points (objective, data-driven)
• Qualitative Adjustment (v2.0): +2 points
  • Media Narrative: +1 (based on "elevated AI narrative" - NO DATA)
  • Valuation: +1 (P/E 30.8 - DOUBLE COUNTED, ignored fundamental backing)
• Result: 11/16 points → Euphoria phase → 40% risk budget (overly defensive)

Root Cause: Confirmation bias - analyst had bearish conclusion first, then adjusted qualitative points to match expectation.

Changes in v2.1

1. Stricter Qualitative Criteria (MAX +3, down from +5)

A. Social Penetration (0-1 points)

• v2.0: Loose criteria, "general awareness" acceptable
• v2.1: ALL three required:
  • Direct user report of non-investor recommendations
  • Specific examples with dates/names
  • Multiple independent sources (minimum 3)

B. Media/Search Trends (0-1 points)

• v2.0: Subjective "many reports" acceptable
• v2.1: BOTH required:
  • Google Trends 5x+ YoY (measured data)
  • Mainstream coverage confirmed (Time covers, TV specials with dates)
• Critical: "Elevated narrative" without data = 0 points

C. Valuation Disconnect (0-1 points)

• v2.0: P/E >25 alone sufficient
• v2.1: ALL required AND avoid double-counting:
  • P/E >25 (if NOT in Phase 2)
  • Fundamentals explicitly ignored in discourse
  • "This time is different" documented in major media
• Self-check: If companies have real earnings supporting valuations → 0 points

2. Confirmation Bias Prevention

New mandatory checklist before adding ANY qualitative points:

□ Do I have concrete, measurable data? (not impressions)
□ Would an independent observer reach the same conclusion?
□ Am I avoiding double-counting with Phase 2 scores?
□ Have I documented specific evidence with sources?

3. Granular Risk Phases

New "Elevated Risk" Phase (8-9 points)

• v2.0: 9 points = Euphoria = 40% risk budget (extreme defensive)
• v2.1: 9 points = Elevated Risk = 50-70% risk budget (balanced caution)

Updated Risk Budget Matrix:

Score	Phase	v2.0 Risk Budget	v2.1 Risk Budget	Change
0-4	Normal	100%	100%	-
5-7	Caution	70%	70-80%	More flexible
8-9	Elevated Risk	40% (Euphoria)	50-70%	NEW PHASE
10-12	Euphoria	40%	40-50%	More balanced
13-15	Critical	20%	20-30%	Reduced max

4. Maximum Score Reduction

• v2.0: 0-16 points (Phase 2: 12, Phase 3: -1 to +5)
• v2.1: 0-15 points (Phase 2: 12, Phase 3: 0 to +3)

Impact on Nov 3, 2025 Analysis

Under v2.0:

• Score: 11/16 → Euphoria phase
• Risk Budget: 40%
• Positioning: Extreme defensive

Under v2.1 (corrected):

• Quantitative: 9/12 (unchanged, data-driven)
• Qualitative:
  • Media Narrative: 0 points (no Google Trends data)
  • Valuation: 0 points (AI has fundamental backing, double-counting)
• Score: 9/15 → Elevated Risk phase
• Risk Budget: 50-70%
• Positioning: Cautious but not extreme

Key Learnings

1. Data > Impressions: "Elevated narrative" is not measurable evidence
2. Avoid Double-Counting: Valuation in Phase 2 quantitative ≠ add again in Phase 3
3. Check Internal Consistency: If report admits "AI has fundamental backing," then valuation disconnect score must be 0
4. Independent Verification: All qualitative points must be verifiable by independent observers

Documentation Updates

• SKILL.md: Updated to v2.1 with strict criteria
• references/implementation_guide.md: Enhanced Phase 3 with bias prevention checklist
• references/quick_reference.md: Updated action matrix with new Elevated Risk phase
• references/bubble_framework.md: Updated risk budget table

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Version 2.0 (October 27, 2025)

Initial Major Revision

• Introduced mandatory quantitative data collection
• Eliminated reliance on impressions and speculation
• Established clear threshold settings for each indicator
• Two-phase evaluation process: Quantitative → Qualitative

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Version Control:

• v1.x: Original framework (deprecated)
• v2.0: Data-driven quantitative focus
• v2.1: Strict qualitative criteria + confirmation bias prevention