Determinants of Tourism Stocks During the COVID-19: Evidence From the Deep Learning Models

This paper examines the determinants of tourism stock returns in China from October 25, 2018, to October 21, 2020, including the COVID-19 era. We propose four deep learning prediction models based on the Back Propagation Neural Network (BPNN): Quantum Swarm Intelligence Algorithms (QSIA), Quantum St...

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Detalles Bibliográficos
Autores principales: Pan, Wen-Tsao, Huang, Qiu-Yu, Yang, Zi-Yin, Zhu, Fei-Yan, Pang, Yu-Ning, Zhuang, Mei-Er
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Public Health
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062709/
https://www.ncbi.nlm.nih.gov/pubmed/33898386
http://dx.doi.org/10.3389/fpubh.2021.675801

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062709/
https://www.ncbi.nlm.nih.gov/pubmed/33898386
http://dx.doi.org/10.3389/fpubh.2021.675801

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