IGWO-MALSTM: An Improved Grey Wolf-Optimized Hybrid LSTM with Multi-Head Attention for Financial Time Series Forecasting

IGWO-MALSTM: An Improved Grey Wolf-Optimized Hybrid LSTM with Multi-Head Attention for Financial Time Series Forecasting

In the domain of financial markets, deep learning techniques have emerged as a significant tool for the development of investment strategies. The present study investigates the potential of time series forecasting (TSF) in financial application scenarios, aiming to predict future spreads and inform...

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Bibliographic Details
Main Authors: Mingfu Zhu, Haoran Qi, Panke Qin
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Applied Sciences
Subjects:
time series forecasting (TSF)
financial markets
long short-term memory (LSTM)
improved Grey Wolf Optimization (IGWO)
multi-head attention mechanism (MA)
model optimization
Online Access:https://www.mdpi.com/2076-3417/15/12/6619
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