How Deja-view computes chart similarity

Deja-view compares normalized adjusted-close shapes. The output is a retrospective similarity table and outcome distribution, not a prediction model.

Method

  • Use adjusted close to reduce split and dividend artifacts.
  • Normalize each window so its first point starts at 100.
  • Resample windows to the configured canonical length.
  • Rank historical windows by shape distance.
  • Summarize what happened after 1, 7, and 30 trading days.

Limitations

Similar shape does not imply causality. The corpus can still contain survivorship bias, source-data delays, and missing historical cases. See sources.

Page Information

Frequently Asked Questions

Is deja-view investment advice?

No. Deja-view is a retrospective comparison tool for historical price patterns. It does not provide buy/sell signals, return guarantees, or investment advice.

How often are pages updated?

Static explanation pages are updated when their content changes. Data-backed stock pages and hubs show the generation timestamp from the data artifact.

Who writes and maintains this site?

Deja-view is created and maintained by Baek Kyoungjung (BK). The About page links to public Medium and LinkedIn profiles for author verification.