Reinforcement Learning in Economics and Finance-Reference-Cited by-同舟云学术

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Reinforcement Learning in Economics and Finance

Published:2021-04-23 Issue: Volume: Page:
ISSN:0927-7099
Container-title:Computational Economics
language:en
Short-container-title:Comput Econ

Author:

Charpentier Arthur^ORCID,Élie Romuald,Remlinger Carl

Funder

Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada

AXA Research Fund

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Economics, Econometrics and Finance (miscellaneous)

Link

https://link.springer.com/content/pdf/10.1007/s10614-021-10119-4.pdf

Reference165 articles.

1. Abbeel, P., & Ng, A. (2004). Apprenticeship learning via inverse reinforcement learning. In Proceedings of the 21st International Conference in Machine Learning (ICML 2004).

2. Abel, D. (2019). Concepts in Bounded Rationality: Perspectives from Reinforcement Learning. PhD thesis, Brown University.

3. Aguirregabiria, V., & Mira, P. (2002). Swapping the nested fixed point algorithm: a class of estimators for discrete markov decision models. Econometrica, 70(4), 1519–1543.

4. Aguirregabiria, V., & Mira, P. (2010). Dynamic discrete choice structural models: a survey. Journal of Econometrics, 156(1), 38–67.

5. Almahdi, S., & Yang, S. Y. (2017). An adaptive portfolio trading system: a risk-return portfolio optimization using recurrent reinforcement learning with expected maximum drawdown. Expert Systems with Applications, 87, 267–279.

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