Machine Learning for Algorithmic Trading - Second Edition

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Autoencoders for Conditional Risk Factors and Asset Pricing

This chapter shows how unsupervised learning can leverage deep learning for trading. More specifically, we'll discuss autoencoders that have been around for decades but have recently attracted fresh interest.

Unsupervised learning addresses practical ML challenges such as the limited availability of labeled data and the curse of dimensionality, which requires exponentially more samples for successful learning from complex, real-life data with many features. At a conceptual level, unsupervised learning resembles human learning and the development of common sense much more closely than supervised and reinforcement learning, which we'll cover in the next chapter. It is also called ...