AgenticInvestor

Singapore Technologies Engineering Ltd

Equity · Monthly series · EQ-S63.SGX

Latest, October 2026

10.15 SGD

-7.1% from September 2026

Open interactive chartSingapore Technologies Engineering Ltd in the app

13.228.173.12November 2016October 2027
History through October 2026, the forecast path to October 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for October 2027: 8.83 SGD, with an 80% interval of 5.50 SGD to 11.97 SGD.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
November 202610.23 SGD9.38 SGD11.23 SGD
December 202610.17 SGD9.57 SGD10.78 SGD
January 202710.10 SGD8.80 SGD11.40 SGD
February 202710.06 SGD8.40 SGD11.56 SGD
March 20279.97 SGD7.69 SGD12.03 SGD
April 20279.83 SGD7.50 SGD11.97 SGD
May 20279.70 SGD6.87 SGD12.15 SGD
June 20279.52 SGD5.73 SGD12.89 SGD
July 20279.35 SGD4.90 SGD13.22 SGD
August 20279.19 SGD5.35 SGD12.68 SGD
September 20279.09 SGD6.03 SGD11.86 SGD
October 20278.83 SGD5.50 SGD11.97 SGD

Model: State-space model, 167M (foundation model). Forecast generated 2026-11-14.

AI confidence

Needs refresh

The data refresh is due. Confidence will be reassessed against the refreshed history.

Model: State-space model, 167M (foundation model)

Accuracy vs naive
n/aNot evaluated
Direction
n/aNot evaluated
Turning points
n/aNot evaluated
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.

Model comparison

Previous comparisonThe stored comparison uses earlier data or a previous model roster. An eligible nightly batch can compare both candidates, subject to call budgets and retry limits.

Models tested

State-space model, 167M scored lowest on the 6 older tests (0.94) and was chosen. The 6 recent tests played no part in the choice and give its grade (1.10). The search for a model that beats the naive forecast on both sets of tests goes on. Scores are MASE: a model's errors divided by the naive forecast's, so 1 is a tie.

4 model classes completed the tests: Foundation model, Statistical, Neural network, Machine learning. Previous model roster.

Every model tested on this series.
ModelClass and computeOlder testsRecent testsRole
State-space model, 167M (foundation model)Foundation model · CPU0.941.10Serving
Exponential smoothing (statistical)Statistical · CPU0.990.96Tested
Agentic Investor TSFM (foundation model)Foundation model · CPU1.001.03Tested
Naive forecast (last value held)Benchmark · CPU1.001.00Benchmark
Hierarchical neural network (neural network)Neural network · CPU1.181.13Tested
Gradient-boosted trees (machine learning)Machine learning · CPU1.190.88Tested

Uses ci-proto, released by Continuous Intelligence. Continuous Intelligence does not endorse or approve this product or service. (ci-proto is shown as State-space model, 167M.)

Reading

It is above 95% 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 202610.15 SGD
September 202610.92 SGD
August 202610.79 SGD
July 202610.08 SGD
June 202610.39 SGD
May 202611.38 SGD
April 202610.72 SGD
March 202610.81 SGD
February 20269.97 SGD
January 20269.80 SGD
December 20258.42 SGD
November 20258.30 SGD
October 20258.49 SGD
September 20258.61 SGD
August 20257.68 SGD
July 20258.77 SGD
June 20257.79 SGD
May 20257.82 SGD
April 20257.41 SGD
March 20256.79 SGD
February 20255.41 SGD
January 20254.84 SGD
December 20244.66 SGD
November 20244.50 SGD

Source

Data: public market data feeds.

More from Agentic Investor