CI-301f · Module 2

False Trend Filtering

3 min read

Not every signal cluster is a trend. False trends are common — they appear as converging signals but are actually noise amplified through echo chambers, temporary reactions to a single event, or deliberate market manipulation by a vendor promoting its narrative. False trend filtering separates genuine market shifts from noise through three tests: the independence test (are the signals from genuinely independent sources?), the persistence test (do the signals persist beyond the initial event?), and the action test (are market participants changing behavior, not just talking?).

Do This

  • Apply the independence test — trace signal sources to verify they are not all citing the same upstream origin
  • Apply the persistence test — wait 30 days after initial detection to see if signals persist or decay
  • Apply the action test — look for behavioral changes (hiring, investing, building) not just narrative changes (talking, presenting, blogging)

Avoid This

  • Classify every signal cluster as a trend — most are noise, temporary reactions, or echo chamber effects
  • Report a trend based on media buzz alone — media amplifies existing narratives, it does not validate market shifts
  • Skip the persistence test because the signals are high-volume — high volume can indicate an event, not a trend