Idiosyncrasies and challenges of data driven learning in electronic trading

By Vangelis Bacoyannis, Vacslav Glukhov, Tom Jin, Jonathan Kochems, Doo Re Song. 2018

21 citations recorded by the source corpus.

We outline the idiosyncrasies of neural information processing and machine learning in quantitative finance. We also present some of the approaches we take towards solving the fundamental challenges we face.

Subfields: Artificial Intelligence, Management Science and Operations Research