The new wave in pulse forecasting/
Can AI outsmart chaos in commodity markets?

For decades, traders, economists, and policymakers have relied on a set of well-established models to make commodity forecasts. These include ARIMA (Auto-Regressive Integrated Moving Average), Exponential Smoothing, VAR (Vector Auto Regression), GARCH (Generalized Autoregressive Conditional Heteroskedasticity), and even Forecast Combination approaches that blend multiple models. These methods, as noted in reports by the International Monetary Fund and the European Central Bank over the past decade, have been useful in capturing broad price trends and volatility patterns.