Synthetic Financial Time Series Generation with Regime Clustering
Author:
Publisher
Engineering and Technology Publishing
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Information Systems,Software
Link
https://www.jait.us/uploadfile/2023/JAIT-V14N6-1372.pdf
Reference32 articles.
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2. [2] R. Bhowmik and S. Wang, "Stock market volatility and return analysis: A systematic literature review," Entropy, vol. 22, no. 5, 522, 2020.
3. [3] W. Lu, J. Li, J. Wang et al., "A CNN-BiLSTM-AM method for stock price prediction," Neural Computing and Applications, vol. 33, pp. 4741-4753, 2021.
4. [4] A. Parot, K. Michell, and W. D. Kristjanpoller, "Using artificial neural networks to forecast exchange rate, including VAR-VECM residual analysis and prediction linear combination," Intelligent Systems in Accounting, Finance and Management, vol. 26, no. 1, pp. 3-15, 2019.
5. [5] S.A. Assefa, D. Dervovic, M. Mahfouz et al., "Generating synthetic data in finance: Opportunities, challenges and pitfalls," in Proc. the First ACM International Conference on AI in Finance, 2020, pp. 1-8.
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