South Korea Tourism Revenues

South Korea · Monthly series · EC-KR-TR

Latest, September 2026

2.46B USD

-1.1% from August 2026

Open interactive chartSouth Korea Tourism Revenues in the app

3.496B2.016B536.3MOctober 2016September 2027
History through September 2026, the forecast path to September 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for September 2027: 2.31B USD, with an 80% interval of 1.40B USD to 3.18B USD.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
October 20262.52B USD2.11B USD2.98B USD
November 20262.42B USD2.14B USD2.71B USD
December 20262.37B USD2.05B USD2.67B USD
January 20272.17B USD1.56B USD2.76B USD
February 20272.17B USD1.75B USD2.58B USD
March 20272.36B USD1.73B USD2.96B USD
April 20272.36B USD1.14B USD3.49B USD
May 20272.35B USD1.14B USD3.50B USD
June 20272.23B USD1.18B USD3.22B USD
July 20272.21B USD953.8M USD3.40B USD
August 20272.28B USD1.19B USD3.35B USD
September 20272.31B USD1.40B USD3.18B USD

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, 5 won)
Direction
47%No clear edge over a coin flip (67 of 144 calls right in 12 tests)
Turning points
53 of 76Anticipated most turns (76 turns in 12 tests, 0 without a turn)
Error vs baseline
5% higherError ratio 1.05; 1.00 is a tie.
Tests won
5 / 12Complete rolling backtests; ties count as no win.
Test period
2014-10-01 to 2026-09-0112 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 96% of the 119 earlier readings since October 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
September 20262.46B USD
August 20262.49B USD
July 20262.62B USD
June 20262.78B USD
May 20262.58B USD
April 20262.40B USD
March 20262.65B USD
February 20261.56B USD
January 20261.64B USD
December 20252.03B USD
November 20251.89B USD
October 20251.72B USD
September 20251.83B USD
August 20251.69B USD
July 20251.77B USD
June 20251.63B USD
May 20251.69B USD
April 20251.85B USD
March 20251.54B USD
February 20251.16B USD
January 20251.08B USD
December 20241.58B USD
November 20241.48B USD
October 20241.84B USD

Source

Data: public market data feeds.

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