What is ensemble learning in financial forecasting systems?

Financial forecasting ensembles combine statistical and machine learning models to improve prediction stability.

Financial markets are noisy and non-stationary, so ensembles combine ARIMA, LSTM, gradient boosting, and regression models. Each captures different temporal and nonlinear structures. Ensemble averaging reduces volatility in predictions and improves robustness during market regime changes. Risk-aware systems also use quantile ensembles for uncertainty estimation.