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.

翻译：我们开发了一种利用深度学习同时求解和估计金融经济学中典型连续时间一般均衡模型的方法。通过两个示例展示该方法的应用：（1）企业产业动态模型；（2）包含金融摩擦的宏观经济模型。这些应用案例凸显了我们方法的优势：通用性、同步求解与估计能力、利用最先进机器学习技术的特性，以及处理大规模状态空间的能力。该方法具有广泛的适用性，可应用于多种研究问题。