AgenticInvestor

Philippines Money Supply M0

Philippines · Monthly series · EC-PH-M0

Latest, September 2026

2.38T PHP

+0.2% from August 2026

Open interactive chartPhilippines Money Supply M0 in the app

2.699T1.756T813.6BOctober 2016September 2027
History through September 2026, the forecast path to September 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for September 2027: 2.53T PHP, with an 80% interval of 2.36T PHP to 2.70T PHP.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
October 20262.44T PHP2.40T PHP2.47T PHP
November 20262.46T PHP2.41T PHP2.52T PHP
December 20262.61T PHP2.57T PHP2.66T PHP
January 20272.50T PHP2.48T PHP2.53T PHP
February 20272.51T PHP2.48T PHP2.54T PHP
March 20272.54T PHP2.48T PHP2.62T PHP
April 20272.58T PHP2.50T PHP2.67T PHP
May 20272.57T PHP2.47T PHP2.67T PHP
June 20272.53T PHP2.41T PHP2.66T PHP
July 20272.51T PHP2.37T PHP2.66T PHP
August 20272.51T PHP2.37T PHP2.65T PHP
September 20272.53T PHP2.36T PHP2.70T PHP

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
+67%Beats the no-change baseline over 12 tests (12 tests, 12 won)
Direction
100%Beats a coin flip (144 of 144 calls right in 12 tests)
Turning points
48 of 55Anticipated most turns (55 turns in 12 tests, 0 without a turn)
Error vs baseline
67% lowerError ratio 0.33; 1.00 is a tie.
Tests won
12 / 12Complete rolling backtests; ties count as no win.
Test period
2014-10-01 to 2026-09-0112 observations ahead per test.
80% band coverage
80%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 97% 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 20262.38T PHP
August 20262.38T PHP
July 20262.37T PHP
June 20262.38T PHP
May 20262.44T PHP
April 20262.44T PHP
March 20262.43T PHP
February 20262.36T PHP
January 20262.37T PHP
December 20252.52T PHP
November 20252.34T PHP
October 20252.30T PHP
September 20252.25T PHP
August 20252.22T PHP
July 20252.23T PHP
June 20252.24T PHP
May 20252.30T PHP
April 20252.35T PHP
March 20252.29T PHP
February 20252.23T PHP
January 20252.22T PHP
December 20242.37T PHP
November 20242.17T PHP
October 20242.11T PHP

Source

Data: public market data feeds.

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