🌐 中文

RMB-Macro-Sim Macro-Policy Sandbox · Research Dashboard

Monte Carlo · 2000 runs x 8 scenarios
Chain: FX (GBM) → import inflation → exports (Marshall-Lerner) → 11-sector profits → asset pricing + capital inflow (financing & deepening).
6.0%
-5% ~ +15% · step 0.5% (41 grids) · 400 MC/grid · backtest-calibrated

🛫 USD/CNY path (median ± 25-75%)

5-year band; end value annotated
Median path 25-75% band

⚖️ Net-benefit waterfall (5y, T$)

Net = financing + deepening − export loss

🔮 Annual outlook: most-likely CNY path model × news events

Three envelopes: low = depreciation-side events only (weakest), base = all events, high = appreciation-side only (strongest). Edit news_watch.yaml to add/remove events (impact +3.2pp / -1.0pp); amount = CNY per USD 10k.

🏭 11-sector 5y cumulative profit shock 按影响排序 ↓

Profit change vs baseline (positive = gain, negative = loss)

🧭 Signal → action rules linked to GOR / Deep-Risk-OPP

Threshold-based; spot rules auto-checked, others manual (verify 10Y/VIX/fixing against the GOR daily card)

🗺️ Sector × year shock heatmap Y1–Y5 cumulative profit shock (%)

Rows = sectors · columns = years · color = shock intensity
loss -40%
neutral 0
gain +40%

🎯 Policy algorithm · Lu three principles

Three principles: ① absorb import inflation (oil +30%) ② surplus 1.2T → near balance ③ block flight / avoid deindustrialization

🔗 Deep-Risk-OPP link · GOR × easing refreshed daily 00:00 UTC

cross-site read of GOR (relative pricing) and easing (gold macro bias) for cross-reference
⚠️ Research framework, not investment advice. Parameters are calibrated assumptions; scenarios are probabilistic, not forecasts.
📊 Sources: FRED / Tencent / akshare, as of 2026-09 | generated:
🔁 Live calibration: —
Reproduce: python run_all.py · run_real.py · export_dashboard.py