Duan, Y., et al. “FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns”. Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, no. 4, 2022, pp. 4468–76, https://doi.org/10.1609/AAAI.V36I4.20369.
APA
Duan, Y., Wang, L., Zhang, Q., & Li, J. (2022). FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns. Proceedings of the AAAI Conference on Artificial Intelligence, 36(4), 4468–4476. https://doi.org/10.1609/AAAI.V36I4.20369
Chicago
Duan, Y., L. Wang, Q. Zhang, and J. Li. 2022. “FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns”. Proceedings of the AAAI Conference on Artificial Intelligence 36 (4): 4468–76. https://doi.org/10.1609/AAAI.V36I4.20369.
Harvard
Duan, Y. et al. (2022) “FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns”, Proceedings of the AAAI Conference on Artificial Intelligence, 36(4), pp. 4468–4476. Available at: https://doi.org/10.1609/AAAI.V36I4.20369.
Vancouver
1. Duan Y, Wang L, Zhang Q, Li J (2022) FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns. Proceedings of the AAAI Conference on Artificial Intelligence 36:4468–4476
BibTeX
@article{Duan_2022, title={FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns}, volume={36}, ISSN={2159-5399}, url={http://dx.doi.org/10.1609/AAAI.V36I4.20369}, DOI={10.1609/aaai.v36i4.20369}, number={4}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, publisher={Association for the Advancement of Artificial Intelligence (AAAI)}, author={Duan, Yitong and Wang, Lei and Zhang, Qizhong and Li, Jian}, year={2022}, month=June, pages={4468–4476} }