Corpus ID: 202734171

PAGAN: Portfolio Analysis with Generative Adversarial Networks

@article{Mariani2019PAGANPA,
  title={PAGAN: Portfolio Analysis with Generative Adversarial Networks},
  author={G. Mariani and Y. Zhu and Jian-bo Li and F. Scheidegger and R. Istrate and C. Bekas and A. C. I. Malossi},
  journal={arXiv: Computational Finance},
  year={2019}
}
  • G. Mariani, Y. Zhu, +4 authors A. C. I. Malossi
  • Published 2019
  • Mathematics, Economics
  • arXiv: Computational Finance
  • Since decades, the data science community tries to propose prediction models of financial time series. Yet, driven by the rapid development of information technology and machine intelligence, the velocity of today's information leads to high market efficiency. Sound financial theories demonstrate that in an efficient marketplace all information available today, including expectations on future events, are represented in today prices whereas future price trend is driven by the uncertainty. This… CONTINUE READING
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