Deep Learning for Solving and Estimating Dynamic Macro-Finance Models

Benjamin Fan, Edward Qiao, Anran Jiao, Zhouzhou Gu, Wenhao Li +1 more
5/5/2023
q-fin.CPcs.CEcs.LG

No official code found. Best implementation: lu-group/pinn-macro-finance (19 stars, Apache-2.0, last commit 2025-08-23).

Abstract

We develop a methodology that utilizes deep learning to simultaneously solve and estimate canonical continuous-time general equilibrium models in financial economics. We illustrate our method in two examples: (1) industrial dynamics of firms and (2) macroeconomic models with financial frictions. Through these applications, we illustrate the advantages of our method: generality, simultaneous solution and estimation, leveraging the state-of-art machine-learning techniques, and handling large state space. The method is versatile and can be applied to a vast variety of problems.

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Code Implementations(1)

lu-group/pinn-macro-financeCommunity100%
Apache-2.0

Deep learning for solving and estimating dynamic macro-finance models

199PythonDec 11, 20221 years agoApache-2.0

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Cite this paper

@article{fan2023deep,
  title  = {Deep Learning for Solving and Estimating Dynamic Macro-Finance Models},
  author = {Benjamin Fan and Edward Qiao and Anran Jiao and Zhouzhou Gu and Wenhao Li and Lu Lu},
  year   = {2023},
  eprint = {2305.09783},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2305.09783v1}
}

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