Taiwan Remittances

Taiwan · Quarterly series · EC-TW-REM

Latest, Q4 2015

52.0M USD

-7.1% from Q3 2015

Open interactive chartTaiwan Remittances in the app

89.91M48.95M8MQ1 2001Q4 2016
History through Q4 2015, the forecast path to Q4 2016 (dashed) and its 80% interval (shaded).

Forecast

Forecast for Q4 2016: 54.3M USD, with an 80% interval of 40.9M USD to 69.1M USD.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
Q1 201672.1M USD53.8M USD89.9M USD
Q2 201653.8M USD37.6M USD72.0M USD
Q3 201657.8M USD41.1M USD75.1M USD
Q4 201654.3M USD40.9M USD69.1M USD

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

AI confidence

Supported evidence

The point forecast beat the no-change baseline overall and in a majority of the evaluated tests.

Model: Agentic Investor TSFM (foundation model)

Accuracy vs naive
+17%Beats the no-change baseline over 8 tests (8 tests, 7 won)
Direction
68%No clear edge over a coin flip (21 of 31 calls right in 8 tests)
Turning points
16 of 18Anticipated most turns (18 turns in 8 tests, 0 without a turn)
Error vs baseline
17% lowerError ratio 0.83; 1.00 is a tie.
Tests won
7 / 8Complete rolling backtests; ties count as no win.
Test period
2008-03-01 to 2015-12-014 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 92% of the 39 earlier readings since Q1 2006.

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
Q4 201552.0M USD
Q3 201556.0M USD
Q2 201548.0M USD
Q1 201565.0M USD
Q4 201441.0M USD
Q3 201442.0M USD
Q2 201444.0M USD
Q1 201455.0M USD
Q4 201336.0M USD
Q3 201336.0M USD
Q2 201334.0M USD
Q1 201349.0M USD
Q4 201229.0M USD
Q3 201231.0M USD
Q2 201228.0M USD
Q1 201235.0M USD
Q4 201128.0M USD
Q3 201123.0M USD
Q2 201124.0M USD
Q1 201131.0M USD
Q4 201029.0M USD
Q3 201019.0M USD
Q2 201021.0M USD
Q1 201025.0M USD

Source

Data: public market data feeds.

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