Index Forecasting

Index forecasting aims to predict future values of various indices, crucial for understanding economic trends and mitigating risks in diverse sectors like finance and space weather. Recent research emphasizes hybrid models combining deep learning architectures (like LSTMs and Transformers) with traditional statistical methods (e.g., VARMA) to improve accuracy and incorporate uncertainty quantification. This focus on hybrid approaches, coupled with advancements in explainable AI and Bayesian inference, enhances both predictive power and the interpretability of results, leading to more reliable decision-making across various applications.