Spatial clustering is a fundamental instrument in modern geo-marketing. The complexity of handling of high-dimensional and geo-referenced data in the context of distribution networks imposes important challenges for marketers to catch the right customer segments with useful pattern similarities....

We examine machine learning and factor-based portfolio optimization. We find that factors based on autoencoder neural networks exhibit a weaker relationship with commonly used characteristic-sorted portfolios than popular dimensionality reduction techniques. Machine learning methods also lead to...

As machines replace humans in financial markets, how is informational efficiency impacted? We shed light on this issue by exploiting a unique data-set that allows us to identify when machines access important company information (8-K filings) versus when humans access the same information. We...