Wilmar International Limited

Equity · Monthly series · EQ-F34.SGX

Latest, October 2026

3.01 SGD

-16.6% from September 2026

Open interactive chartWilmar International Limited in the app

5.423.6841.947November 2016October 2027
History through October 2026, the forecast path to October 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for October 2027: 3.05 SGD, with an 80% interval of 2.35 SGD to 3.73 SGD.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
November 20263.01 SGD2.42 SGD3.63 SGD
December 20263.00 SGD2.52 SGD3.51 SGD
January 20273.01 SGD2.26 SGD3.76 SGD
February 20273.01 SGD2.56 SGD3.45 SGD
March 20273.02 SGD2.27 SGD3.75 SGD
April 20273.02 SGD2.40 SGD3.63 SGD
May 20273.03 SGD2.42 SGD3.63 SGD
June 20273.04 SGD1.95 SGD4.10 SGD
July 20273.04 SGD2.25 SGD3.81 SGD
August 20273.04 SGD2.31 SGD3.76 SGD
September 20273.05 SGD2.22 SGD3.85 SGD
October 20273.05 SGD2.35 SGD3.73 SGD

Model: Agentic Investor TSFM (foundation model). Forecast generated 2026-11-15.

AI confidence

Mixed evidence

The tests show no consistent, material advantage over the no-change baseline.

Model: Agentic Investor TSFM (foundation model)

Accuracy vs naive
0%Matches the no-change baseline over 12 tests (12 tests, 6 won)
Direction
50%No clear edge over a coin flip (71 of 143 calls right in 12 tests)
Turning points
14 of 62Anticipated some turns (62 turns in 12 tests, 0 without a turn)
Error vs baseline
About the sameError ratio 1.00; 1.00 is a tie.
Tests won
6 / 12Complete rolling backtests; ties count as no win.
Test period
2014-11-01 to 2026-10-0112 observations ahead per test.
80% band coverage
80%Observed outcomes inside the band across all stored test windows.
How this assessment is made

AI confidence describes historical evidence for this forecast, not a probability of being correct. Each backtest fits on data available before its test window. The baseline carries the last value forward. Supported evidence requires at least six complete, non-overlapping tests, an error ratio below 0.90 (rounded to two decimals), and wins in a majority of tests. Ratios from 0.90 to below 1.10 are on par; 1.10 or above is weak evidence. Inconsistent wins produce mixed evidence. For a selected model, only the recent tests excluded from model selection determine this label. These are historical simulations using the available data, not a live trading track record; revisions and foundation-model pretraining can limit how closely they reproduce a past decision. Past performance can change.

Replay past tests

Model comparison

Comparison pendingA new ticker first receives its serving model's forecast and evaluation. An eligible nightly batch can compare both candidates, subject to call budgets and retry limits.

Reading

It is above 3% of the 119 earlier readings since November 2016.

Written from the figures by a fixed template; no AI model is involved.

Recent history (24 observations)
The 24 most recent observations, newest first.
PeriodValue
October 20263.01 SGD
September 20263.61 SGD
August 20263.84 SGD
July 20263.93 SGD
June 20263.61 SGD
May 20263.59 SGD
April 20263.61 SGD
March 20263.85 SGD
February 20263.52 SGD
January 20263.39 SGD
December 20253.08 SGD
November 20253.24 SGD
October 20253.13 SGD
September 20252.85 SGD
August 20252.95 SGD
July 20252.95 SGD
June 20252.87 SGD
May 20253.05 SGD
April 20253.06 SGD
March 20253.35 SGD
February 20253.21 SGD
January 20253.12 SGD
December 20243.10 SGD
November 20243.08 SGD

Source

Data: public market data feeds.

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