Forecasting Crude Oil Prices using a Hybrid Model Combining Long Short-Term Memory Neural Networks and Markov Switching Model-Reference-Cited by-同舟云学术

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Forecasting Crude Oil Prices using a Hybrid Model Combining Long Short-Term Memory Neural Networks and Markov Switching Model

Published:2023-06-12 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Future Energy Solutions (FES)
language:
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Author:

Shahbazbegian Vahid¹,Hosseininesaz Hamid¹,Shafie-Khah Miadreza¹,Elmusrati Mohammed¹

Affiliation:

1. University of Vaasa,School of Technology and Innovations,Vaasa,Finland

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10182286/10182373/10182444.pdf?arnumber=10182444

Reference28 articles.

1. Impact of financial instability on international crude oil volatility: New sight from a regime-switching framework

2. Exchange rates and oil price under uncertainty and regime switching: A Markov-switching VAR approach

3. A multiple adaptive wavelet recurrent neural network model to analyze crude oil prices

4. Forecasting energy market indices with recurrent neural networks: Case study of crude oil price fluctuations

5. A Markov switching long memory model of crude oil price return volatility

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Effect of Hyperparameter Tuning in Long Short-Term Memory for Crude Oil Price Prediction;2024 IEEE 6th Symposium on Computers & Informatics (ISCI);2024-08-10

2. A Combined Framework Based on Feature Selection and Multivariate Mixed-Frequency for Crude Oil Prices Point and Interval Forecasting;IEEE Access;2023

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