Practical Aspects of Applying Deep Learning for Market Making
Deep Learning has been shown to outperform traditional methods in many learning tasks such as image and voice recognition, but its role in processing financial datasets is yet to be fully discovered. In this talk, I will share practical insights about applying Deep Learning for different aspects of market making. I will discuss some of the unique challenges and tradeoffs of this field.
I am a senior data scientist at Citi, working at the Technology Innovation Center in Tel Aviv. I apply Deep Learning to financial datasets to build models for different business units in Citi. Before joining Citi I worked as a senior quantitative researcher for a large hedge fund and before that as an algorithm engineer in the field of biomedical signal processing. I hold a PhD in Biomedical Engineering.