Nonlinear quantile factor modelVariational autoencoderWe propose a new asset pricing model that is applicable to the big panel of return data. The main idea of this model is to learn the conditional distribution of the return, which is approximated by a step distribution function constructed from ...
[22] conducted studies on multiple energy datasets using deep generative models such as GAN and Variational Autoencoder (VAE). They have realized data generation for photovoltaic, wind power generation, and other scenarios. Zhang et al. [23] proposed a framework for generating wind power scenarios...