United Overseas Bank Limited

Name: United Overseas Bank Limited
Creator: Agentic Investor

Equity · Monthly series · EQ-U11.SGX

Latest, October 2026

41.37 SGD

-3.4% from September 2026

Open interactive chartUnited Overseas Bank Limited in the app

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

Forecast

Forecast for October 2027: 40.31 SGD, with an 80% interval of 31.99 SGD to 48.39 SGD.

Forecast path. Intervals are shown where available.
Period	Forecast	80% low	80% high
November 2026	41.18 SGD	36.67 SGD	45.93 SGD
December 2026	41.01 SGD	36.54 SGD	45.84 SGD
January 2027	40.93 SGD	33.27 SGD	48.67 SGD
February 2027	40.84 SGD	33.03 SGD	48.84 SGD
March 2027	40.84 SGD	32.11 SGD	49.56 SGD
April 2027	40.77 SGD	31.08 SGD	50.36 SGD
May 2027	40.66 SGD	31.20 SGD	49.83 SGD
June 2027	40.55 SGD	30.53 SGD	50.54 SGD
July 2027	40.54 SGD	29.48 SGD	51.32 SGD
August 2027	40.43 SGD	29.82 SGD	50.75 SGD
September 2027	40.36 SGD	28.44 SGD	52.00 SGD
October 2027	40.31 SGD	31.99 SGD	48.39 SGD

Model: Agentic Investor TSFM (foundation model). Forecast generated 2026-11-14.

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: +5%Matches the no-change baseline over 12 tests (12 tests, 10 won)
Direction: 74%No clear edge over a coin flip (106 of 143 calls right in 12 tests)
Turning points: 34 of 74Anticipated some turns (74 turns in 12 tests, 0 without a turn)

Error vs baseline: 5% lowerError ratio 0.95; 1.00 is a tie.
Tests won: 10 / 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.

Band coverage uses all stored test windows, including model-selection windows when present; it does not determine the confidence label.
Evaluated 2026-11-14 against the cached history through 2026-10-01.
This is an evaluation of the serving model; it does not establish a winner across four model classes.

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 97% 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.
Period	Value
October 2026	41.37 SGD
September 2026	42.84 SGD
August 2026	41.56 SGD
July 2026	43.40 SGD
June 2026	39.76 SGD
May 2026	37.60 SGD
April 2026	36.15 SGD
March 2026	36.65 SGD
February 2026	36.97 SGD
January 2026	38.27 SGD
December 2025	35.06 SGD
November 2025	33.98 SGD
October 2025	34.67 SGD
September 2025	34.58 SGD
August 2025	35.19 SGD
July 2025	36.19 SGD
June 2025	36.00 SGD
May 2025	35.41 SGD
April 2025	34.64 SGD
March 2025	38.09 SGD
February 2025	38.20 SGD
January 2025	37.51 SGD
December 2024	36.33 SGD
November 2024	36.36 SGD

Source

Data: public market data feeds.