Forecasting Stock Market Indices Using Integration of Encoder, Decoder, and Attention Mechanism

Accurate forecasting of stock market indices is crucial for investors, financial analysts, and policymakers. The integration of encoder and decoder architectures, coupled with an attention mechanism, has emerged as a powerful approach to enhance prediction accuracy. This paper presents a novel frame...

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Bibliographic Details
Published in:	Entropy (Basel, Switzerland) Vol. 27; no. 1; p. 82
Main Author:	Thach, Tien Thanh
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 01.01.2025 MDPI
Subjects:	Accuracy attention mechanism Bayesian optimization Coders Comparative analysis Computational linguistics Deep learning encoder–decoder architecture Forecasting gated recurrent units Language processing long short-term memory Machine translation Natural language interfaces Neural networks Recurrent neural networks Securities markets Stock exchanges Stock markets Stock price indexes Stock prices Stocks Time series Voice recognition Vietnam gated recurrent units encoder–decoder architecture recurrent neural networks Bayesian optimization attention mechanism long short-term memory
ISSN:	1099-4300, 1099-4300
Online Access:	Get full text
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