Aleksandr V. MATYTSYN

Enhancing forecasting performance in complex commodity markets: A TimeGAN-based approach applied to oil prices

This study addresses the challenge of limited historical data and high volatility in oil market forecasting by integrating synthetic time series generated with the generative adversarial networks (TimeGAN) model into the training process of a multilayer perceptron (MLP) neural ne...