usd-reserve-loss-gold-revaluation

To calculate the implied gold price under a reserve-loss scenario, divide money liabilities by gold reserves across selected currencies. This generates a headline implied price, per-entity backing ratios, leverages, and a ranked stress map.

You can apply multiple monetary aggregates such as M0 or M2 for gold backing stress tests. The analysis uses weighting schemes like FX turnover or reserve-share to produce per-entity backing ratios and leverage multiples.

Stress-testing central bank balance sheets involves evaluating multi-currency exposure like USD, EUR, JPY, and CNY under M0 or M2. It models extreme balance-sheet stress by replacing fiat anchors with gold to estimate implied prices.

Yes, the gold revaluation analysis requires Python dependencies including pandas, numpy, requests, and yfinance. The included Python scripts use these libraries to fetch data and perform the reserve-loss calculations.

When computing implied gold prices for de-dollarization scenarios, outputs are generated in structured JSON or Markdown format. The results include a headline implied price, backing ratios, and a ranked stress map with optional visualizations.

Yes, you can evaluate multiple currencies like CNY and GBP in a macro gold revaluation scenario analysis. The tool supports multi-currency exposure across USD, EUR, JPY, CNY, GBP and others to produce leverage insights and rankings.