Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction-Reference-Cited by-同舟云学术

Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction

Published:2022-10-26 Issue: Volume: Page:
ISSN:
Container-title:3rd ACM International Conference on AI in Finance
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Author:

Ziyin Liu¹,Minami Kentaro²,Imajo Kentaro²

Affiliation:

1. University of Tokyo, JP

2. Preferred Networks, Inc., JP

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3533271.3561720

Reference37 articles.

1. Antreas Antoniou Amos Storkey and Harrison Edwards. 2017. Data augmentation generative adversarial networks. arXiv preprint arXiv:1711.04340(2017). Antreas Antoniou Amos Storkey and Harrison Edwards. 2017. Data augmentation generative adversarial networks. arXiv preprint arXiv:1711.04340(2017).

2. Generating synthetic data in finance

3. The Pricing of Options and Corporate Liabilities

4. Deep hedging

5. Rama Cont. 2001. Empirical properties of asset returns: stylized facts and statistical issues. Quantitative Finance(2001). Rama Cont. 2001. Empirical properties of asset returns: stylized facts and statistical issues. Quantitative Finance(2001).

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