Data for Merit: A multi-objective basket currency index for neutral global settlement

Data and code to replicate all results in the paper. Includes 6 Python scripts (data collection, index simulation, benchmark comparisons, sensitivity analysis, walk-forward out-of-sample validation, and performance/liquidity evaluation), 4 input datasets (exchange rates from FRED, GDP and CPI from IMF DataMapper), and 22 output CSV result tables. All simulations are deterministic (random seed 42). Requires Python 3.10+ with NumPy, pandas, SciPy, Matplotlib, Seaborn, and a free FRED API key.