AgenticInvestor

Thailand Interbank Rate

Thailand · Monthly series · EC-TH-INBR

Latest, November 2026

1.1%

+0.00pp from October 2026

Open interactive chartThailand Interbank Rate in the app

2.6541.6230.5915December 2016November 2027
History through November 2026, the forecast path to November 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for November 2027: 1.2%, with an 80% interval of 0.6% to 2.4%.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
December 20261.2%1.1%1.2%
January 20271.2%1.1%1.2%
February 20271.2%1.1%1.3%
March 20271.2%1.0%1.4%
April 20271.1%1.0%1.4%
May 20271.1%0.9%1.5%
June 20271.1%0.9%1.6%
July 20271.2%0.9%1.7%
August 20271.2%0.7%2.0%
September 20271.2%0.6%2.3%
October 20271.2%0.6%2.4%
November 20271.2%0.6%2.4%

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
+17%Beats the no-change baseline over 12 tests (12 tests, 5 won)
Direction
66%No clear edge over a coin flip (92 of 140 calls right in 12 tests)
Turning points
12 of 45Anticipated some turns (45 turns in 12 tests, 2 without a turn)
Error vs baseline
17% lowerError ratio 0.83; 1.00 is a tie.
Tests won
5 / 12Complete rolling backtests; ties count as no win.
Test period
2014-12-01 to 2026-11-0112 observations ahead per test.
80% band coverage
81%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 26% of the 119 earlier readings since December 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
November 20261.1%
October 20261.1%
September 20261.1%
August 20261.1%
July 20261.1%
June 20261.1%
May 20261.1%
April 20261.1%
March 20261.1%
February 20261.1%
January 20261.4%
December 20251.4%
November 20251.6%
October 20251.6%
September 20251.6%
August 20251.6%
July 20251.9%
June 20251.9%
May 20251.9%
April 20252.1%
March 20252.1%
February 20252.1%
January 20252.4%
December 20242.4%

Source

Data: public market data feeds.

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