Japan CPI macro intelligence workspace with inflation, yen, yield-curve, and supply-chain signal panels

Zweispace vertical AI token family

CPI

Public-good inflation prediction research for Japan's CPI, yen, JGB yield curve, and real-economy price signals.

MIC Japan CPI May 2026 release: Jun 19
BOJ Core CPI 2 business days later, 14:00
Mode Research simulation only

Core thesis

Prediction-market mechanics, public-good purpose.

CPI combines a Tokyo signal network with prediction-market probability boards. Official CPI and BOJ core indicators arrive with delay and different lenses, while firms, markets, and households react earlier. When people see inflation risk, move on it, and reprice around it, expectations can become part of the CPI path itself. This board makes that uncertainty visible for public-good learning.

CGPI lead signal

Upstream prices move before household CPI.

Updated local seed

Corporate goods pressure vs consumer CPI

Prototype lead-lag model. Public charts should be regenerated from official or licensed time-series data before external publication.

Upstream price pressure Consumer CPI

JGB yield curve

Inflation surprise should map into rates, not noise.

Prototype curve map

JGB curve under CPI scenarios

Prototype research view. Replace seed points with licensed JGB curve data before formal publication.

Baseline curve Hot CPI Cool CPI
Data status: seeded prototype JGB curve source: licensed feed required Last updated: local research seed

ZweiPredict CPI Board

Four macro probability boards.

Browser demo Local research credits 0 CPI-R

Resolution anchors

Official statistics first, live signals around them.

Source notes
01

MIC official CPI

National CPI and Tokyo-area releases anchor the headline government-visible statistic.

Release schedule
02

BOJ underlying CPI

Core indicators help separate institutional and transitory factors from underlying price pressure.

Core CPI indicators
03

Market reaction

JGB curve, yen, import prices, resource baskets, and supply-chain data show how the real economy absorbs CPI.

Board plan
04

$CPI thesis

The original release frames CPI as inflation observation, statistical-mechanics modeling, and real-economy research.

PR Times reference

Method

From one delayed number to a living price map.

CPI should explain the composition behind the headline: shrinkflation, substitution, energy, FX pass-through, wages, regional differences, resource inputs, marketing behavior, and policy effects.

Official anchorMIC CPI release calendar, survey month, basket structure, and first-resolution rule.
Live proxiesRetail, procurement, freight, energy, FX, commodities, company disclosures, and sentiment data.
Distribution modelBucket probabilities, volatility, diffusion, scenario paths, and statistical-mechanics inspired basket proposals.
Learning ledgerForecast performance, model drift, contributor attribution, and post-release policy interpretation.

Token path

CPI starts as research credit, not a tradable promise.

CPI can organize contribution, model runs, review workflows, source attribution, and forecast-score reputation inside the vertical. Any public token, real-money market operation, exchange activity, ETD-style index token, or Japan license pathway requires legal and regulator review first.

Build order

Make the research useful before the market is live.

Working README
  1. Static board: publish a clear public-good CPI page with simulation-only probability buckets.
  2. Five-bucket market sandbox: model 1.5%, 2.0%, 2.5%, 3.0%, and 3.5% CPI outcomes with paper wallet accounting.
  3. Official calendar: load MIC and BOJ release dates, source URLs, and resolution rules.
  4. Historical backtest: score CPI surprise buckets against past releases and JGB/yen reactions.
  5. Basket lab: test better CPI compositions from live price proxies, supply-chain data, and policy factors.
  6. Review gate: prepare counsel and regulator memos before token issuance or regulated market activity.