Enhanced LFTSformer: A Novel Long-Term Financial Time Series Prediction Model Using Advanced Feature Engineering and the DS Encoder Informer Architecture

arXiv:2310.01884v2 Announce Type: replace
Abstract: This study presents a groundbreaking model for forecasting long-term financial time series, termed the Enhanced LFTSformer. The model distinguishes itself through several significant innovations:
(1) VMD-MIC+FE Feature Engineering: The incorporation of sophisticated feature engineering techniques, specifically through the integration of Variational Mode Decomposition (VMD), Maximal Information Coefficient (MIC), and feature engineering (FE) methods, enables comprehensive perception and extraction of deep-level features from complex and variable financial datasets. (2) DS Encoder Informer: The architecture of the …

abstract advanced architecture arxiv cs.ai cs.lg encoder engineering feature feature engineering financial forecasting groundbreaking innovations long-term novel prediction series study through time series type