Deep Learning for Business and Finance Brian Freeman, PhD, PE

Machine Learning vs Artificial Intelligence Data Images Speech Sounds Measurements RNNs & CNNs

Perceptron model

Different types of architecture, Different types of learning

Machine learning model Data Pre-processing Model selection Training Testing

Business & Finance Application Investments Identification/Discovery Timing (Market Entrance/Exit) Portfolio optimization Credit risk Fraud/Compliance Market classification

Data Unsupervised Deep Learning Supervised Deep Learning <10,000 observations >10,000 observations Unsupervised Deep Learning Supervised Deep Learning Self-assembling Target objective

Natural Language Processing M. Kraus and S. Feuerriegel, Decision support from financial disclosures with deep neural networks and transfer learning, Decision Support Systems 104 (2017) 38–48, doi: 10.1016/j.dss.2017.10.001

Results L. Troiano, E. Mejuto, and P. Kriplani (2017), On Feature Reduction using Deep Learning for Trend Prediction in Finance, arXiv:1704.03205v1

Results Profitability (%) W. Bao, J. Yue, and Y. Rao (2017), A deep learning framework for financial time series using stacked autoencoders and long short term memory, PLoS ONE 12(7): e0180944. doi: 10.1371/journal.pone.0180944

It is unlikely that any theoretical models built from existing axiomatic foundations will be able to compete with the predictive performance of deep learning models. J. B. Heaton, N. G. Polson, and J. H. Witte, (2018) Deep Learning in Finance, arXiv:1602.06561v3