Deep Learning for Solving and Estimating Dynamic Macro-Finance Models

2023/05/05 by Fan, Benjamin, Qiao, Edward, Jiao, Anran +3 · 3 citations
#Computational Engineering #Computational Finance (q-fin.CP) #FOS: Computer and information sciences #FOS: Economics and business #Finance #Machine Learning (cs.LG) #and Science (cs.CE)

paper · doi:10.48550/arxiv.2305.09783

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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