Likely lower · avg analogue -1.77%
Moderate convictionPattern Intelligence · SAO
F1NI34 quant read
The nearest historical setups point to downside risk rather than follow-through strength.
Likely lower · avg analogue -1.26%
Moderate conviction5 of the core evidence blocks are acting as headwinds.
Evidence improves only if price stabilises and relative strength stops lagging.
Current weekly tape
Price, trend line, and fair value
Use this to anchor the probability read to the actual chart. A bearish analogue read is more serious when price is below trend or stretched above fair value.
- Close
- 13.17
- Trend Line
- 15.96
- Fair value
- 22.04
Hover chart for weekly context.
Signal stack
What changed underneath price?
Each signal is standardized against its own recent history, so the lines show whether the current reading is unusually strong or weak for this stock.
Hover for standardized signal values.
Historical memory
Nearest 4-week analogue returns
Bars are the forward 4-week returns from the closest resolved examples, ordered by similarity. Red clustering is the warning sign.
Hover for analogue return and similarity rank.
Outcome frame
Range of outcomes from the nearest 4-week analogues
This is not a forecast range. It is the historical distribution of similar setups, translated into bear/base/bull context.
What weaker historical analogues tended to deliver.
The middle outcome from the nearest resolved examples.
What stronger historical analogues tended to deliver.
Evidence stack
Why the model sees this setup
These are the current conditions feeding the analogue read. The point is not the number alone; it is whether the evidence agrees with the probability read.
Price is below trend, which keeps pressure on the setup.
Price is trading below Fair Value, which can create recovery potential if pressure improves.
Market Dynamics are neutral.
The stock is lagging relative strength.
This component is a drag.
This component is a drag.
Historical rhymes
Closest resolved setups
The table keeps the model honest: these are the actual examples behind the headline odds.
| Ticker | Week | Similarity | Outcome | 4W return |
|---|---|---|---|---|
| ETH MIL |
2024-08-30 | 0.7849 | lower | -21.35% |
| SML NZE |
2021-06-11 | 0.7808 | higher | +13.39% |
| KINO JKT |
2023-02-17 | 0.7796 | lower | -10.06% |
| 4265 JPX |
2025-03-28 | 0.7771 | lower | -9.68% |
| KOM MCE |
2023-03-17 | 0.772 | flat | 0.00% |
| 6548 JPX |
2024-06-28 | 0.7712 | higher | +1.56% |
| PEAN EBS |
2023-03-10 | 0.7706 | lower | -22.12% |
| UMI VIE |
2024-11-15 | 0.7677 | lower | -1.15% |
| F2VR34 SAO |
2026-06-12 | 0.7676 | higher | +4.96% |
| 1323 HKG |
2024-04-05 | 0.7665 | higher | +5.71% |
| HDIL NSI |
2023-07-07 | 0.7652 | flat | 0.00% |
| 9857 HKG |
2025-03-14 | 0.764 | lower | -23.31% |
Distinctive drivers
What made this setup unusual
These are the largest deviations from the run baseline, renamed into plain market language.
- Sector structure 0.97266
- Market Activity -0.80284
- Price Cycle -0.47153
- Price vs Fair Value -0.46502
This is historical analogue evidence, not advice. It becomes more useful when probability, average return, chart evidence, and nearby examples all point in the same direction.