# Deep Learning in Finance

arXiv: https://arxiv.org/abs/1602.06561 · HTML: https://mlsanity.com/paper/1602.06561/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Feb 2016.

## Built on by (most cited first, 18 of 18)

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## Abstract (arXiv)

We explore the use of deep learning hierarchical models for problems in financial prediction and classification. Financial prediction problems -- such as those presented in designing and pricing securities, constructing portfolios, and risk management -- often involve large data sets with complex data interactions that currently are difficult or impossible to specify in a full economic model. Applying deep learning methods to these problems can produce more useful results than standard methods in finance. In particular, deep learning can detect and exploit interactions in the data that are, at least currently, invisible to any existing financial economic theory.