Grid search with a weighted error function: Hyper-parameter optimization for financial time series forecasting-Reference-Cited by-同舟云学术

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Grid search with a weighted error function: Hyper-parameter optimization for financial time series forecasting

Published:2024-03 Issue: Volume:154 Page:111362
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Zhao Yuan^ORCID,Zhang Weiguo,Liu Xiufeng^ORCID

Funder

Ministry of Science and Technology of the People's Republic of China

Chinese National Funding of Social Sciences

National Office for Philosophy and Social Sciences

Fundamental Research Funds for the Central Universities

Humanities and Social Science Fund of Ministry of Education of China

Ministry of Education of the People's Republic of China Humanities and Social Sciences Youth Foundation

Publisher

Elsevier BV

Reference65 articles.

1. Financial time series forecasting with deep learning: A systematic literature review: 2005–2019;Sezer;Appl. Soft Comput.,2020

2. Forecasting crude oil futures market returns: A principal component analysis combination approach;Zhang;Int. J. Forecast.,2022

3. Deep learning for time series forecasting: a survey;Torres;Big Data,2021

4. Forecasting: Principles and Practice;Hyndman,2018

5. Effective LSTMs with seasonal-trend decomposition and adaptive learning and niching-based backtracking search algorithm for time series forecasting;Wu;Expert Syst. Appl.,2024

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