Research angle
The question behind the note
The lab treats a candidate as a lifecycle, not a one-day label. A name may begin as a quiet early observation, graduate into a stronger bucket, become visible, and then need caution as attention builds.
What the evidence showed
What repeated review changed
Early candidates are often less obvious but require more patience and verification.
Visible candidates are easier to notice but can carry larger reaction risk.
A lifecycle record helps the notebook remember when the name first appeared and whether improvement was gradual or abrupt.
Evidence checklist
Evidence to record before the outcome
- Record the first date the candidate entered the workbook.
- Note whether it improved gradually or jumped into visibility.
- Compare lifecycle stage with risk distance.
- Reduce confidence when the path becomes too crowded or too extended.
Historical ticker results
PRU, HPQ, TGT, J
| Ticker | Signal dates | 5-day raw | 5-day excess vs QQQ | 20-day raw |
|---|---|---|---|---|
| PRU | 48 | 2.09% | 2.47% | 7.10% |
| HPQ | 33 | 3.26% | 2.35% | 13.75% |
| TGT | 73 | 0.05% | -0.50% | 3.39% |
| J | 23 | -1.42% | -1.31% | 1.78% |
V4.67.1 historical sample. Next-session-open entry assumption. A zero count means no matching observation, not a negative rating.
Failure modes
How the observation can be misused
- Treating a late-stage visible name like an early-stage candidate.
- Forgetting prior appearances after a ticker returns to the list.
- Ignoring the history of failed follow-through.
- Promoting a descriptive pattern into a forecast without an out-of-sample test.
- Reporting the favorable horizon while omitting weaker horizons or the benchmark.
Open the full V4.67.1 model audit | Read the data methodology
Reader replication guide
How to evaluate Candidate Lifecycle: From Early Watch to Visible Leader
Treat this case as a documented research example rather than a current recommendation. First identify the original question and observation date. Then separate company-reported facts, market data, model-derived results, and editorial interpretation. Each layer can update on a different schedule.
Reproduce the evidence
Open the cited primary source, confirm the covered period, preserve the raw input, and recalculate the reported comparison. If a historical model result is discussed, keep its entry assumption, horizon, benchmark, and overlapping-sample limitation attached.
Test an alternative explanation
Ask whether sector performance, rates, currency, acquisition effects, reporting-definition changes, or a small sample could explain the observation. Record the strongest contradictory evidence before accepting the interpretation.
A useful conclusion states what the example supports, what it does not establish, and which new filing or dated result would require an update. Preserving the earlier version prevents hindsight from silently changing the research question.