Likely lower · avg analogue -0.57%
Moderate convictionPattern Intelligence · TOR
OGI quant read
The nearest historical setups point to downside risk, and the live chart evidence supports that caution.
Likely lower · avg analogue -0.17%
Moderate conviction4 of the core evidence blocks are acting as headwinds.
Downside risk is confirmed while price remains below trend and relative strength keeps 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
- 1.68
- Trend Line
- 1.69
- Fair value
- 2.08
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 close to trend, so direction still needs confirmation.
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 |
|---|---|---|---|---|
| A1TH34 SAO |
2026-06-12 | 0.6693 | higher | +35.36% |
| SMD100 SET |
2026-06-12 | 0.6604 | lower | -2.56% |
| 600155 SHH |
2026-06-12 | 0.6575 | lower | -0.56% |
| FINOPB NSI |
2026-06-12 | 0.6538 | lower | -0.59% |
| 601136 SHH |
2026-06-12 | 0.6536 | higher | +0.50% |
| 200596 SHZ |
2026-06-12 | 0.649 | lower | -6.62% |
| 300294 SHZ |
2026-06-12 | 0.642 | lower | -12.24% |
| BILVYAPAR NSI |
2026-06-12 | 0.6399 | higher | +5.01% |
| MDNA TOR |
2026-06-12 | 0.6392 | lower | -11.90% |
| MHLA NYSE |
2026-06-12 | 0.6392 | lower | -7.09% |
| MADAME SET |
2026-06-12 | 0.6381 | flat | 0.00% |
| 688366 SHH |
2026-06-12 | 0.6357 | lower | -0.06% |
Distinctive drivers
What made this setup unusual
These are the largest deviations from the run baseline, renamed into plain market language.
- Quality context 0.78435
- Momentum context 0.77187
- Yield context 0.76747
- Market Activity -0.63428
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.