A flexible hybrid approach to probabilistic stock forecasting that combines statistical model with ARCH effects, offering an alternative to traditional ARMA-GARCH models
Examples of use of Probabilistic Machine Learning (for longitudinal data) Reserving with scikit-learn, glmnet, xgboost, lightgbm, pytorch, keras, nnetsauce
A flexible hybrid approach to probabilistic stock forecasting that combines machine learning with ARCH effects, offering an alternative to traditional ARMA-GARCH models