Long short-term memory autoencoder based network of financial indices

Long short-term memory autoencoder based network of financial indices

Abstract We present a novel approach for analyzing financial time series data using a Long Short-Term Memory Autoencoder (LSTMAE), a deep learning method. Our primary objective is to uncover intricate relationships among different stock indices, leading to the extraction of stock networks. We examin...

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Bibliographic Details
Main Authors:	Kamrul Hasan Tuhin, Ashadun Nobi, Mahmudul Hasan Rakib, Jae Woo Lee
Format:	Article
Language:	English
Published:	Springer Nature 2025-01-01
Series:	Humanities & Social Sciences Communications
Online Access:	https://doi.org/10.1057/s41599-025-04412-y
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