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Economic Research-Ekonomska Istraživanja Volume 36, 2023 - Issue 1
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Volatility forecasting using deep neural network with time-series feature embedding

Wei-Jie Chena School of Economics, Zhejiang University of Technology, Hangzhou, China;b Zhijiang College, Zhejiang University of Technology, Shaoxing, ChinaORCID Iconhttps://orcid.org/0000-0001-5186-0279View further author information
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Jing-Jing Yaob Zhijiang College, Zhejiang University of Technology, Shaoxing, ChinaView further author information
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Yuan-Hai Shaoc Management School, Hainan University, Haikou, ChinaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-1628-6133View further author information
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Pages 1377-1401 | Received 17 Dec 2021, Accepted 06 Jun 2022, Published online: 22 Jun 2022

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Ajit Kumar Rout, Abhisek Sethy & Soumya Ranjan Nayak. (2022) Adaptive MLELM-AE model for efficient prediction of stock market data. Journal of Statistics and Management Systems 25:7, pages 1541-1552.
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Articles from other publishers (4)

Wenbo Ge, Pooia Lalbakhsh, Leigh Isai & Hanna Suominen. 2024. AI 2023: Advances in Artificial Intelligence. AI 2023: Advances in Artificial Intelligence 178 189 .
Hugo Gobato Souto & Amir Moradi. (2023) Forecasting realized volatility through financial turbulence and neural networks. Economics and Business Review 9:2.
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Mike G. Tsionas. (2022) Linex and double-linex regression for parameter estimation and forecasting. Annals of Operations Research 323:1-2, pages 229-245.
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Hugo Gobato Souto. (2023) TimesNet for Realized Volatility Prediction. SSRN Electronic Journal.
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