Machine Learning for Algorithmic Trading - Second Edition

21

Generative Adversarial Networks for Synthetic Time-Series Data

Following the coverage of autoencoders in the previous chapter, this chapter introduces a second unsupervised deep learning technique: generative adversarial networks (GANs). As with autoencoders, GANs complement the methods for dimensionality reduction and clustering introduced in Chapter 13, Data-Driven Risk Factors and Asset Allocation with Unsupervised Learning.

GANs were invented by Goodfellow et al. in 2014. Yann LeCun has called GANs the "most exciting idea in AI in the last ten years." A GAN trains two neural networks, called the generator and discriminator, in a competitive setting. The generator aims to produce samples that the discriminator is unable to distinguish ...