Deep learning has seen tremendous successes in areas such as image recognition and natural language processing – but its adoption in finance has been slow.
Financial data is often plagued with a notoriously low signal-to-noise ratio as well as non-stationarity of the data. Applying deep learning techniques to financial time-series data thus often requires bespoke models.
The question is how.
At this interactive event, Stefan Zohren – an Associate Professor (Research) at the Machine Learning Research Group and the Oxford-Man Institute for Quantitative Finance (OMI) – will explore recent work on applying deep learning techniques to financial microstructure data. The importance of uncertainties as obtained from Bayesian deep learning approaches is pointed out and several similarities to other areas such as self-driving cars and modelling of climate data are highlighted.
Join Hewlett Packard Enterprise, Nvidia and select group of financial services industry- and thought leaders for one unique evening of peer-to-peer discussion about modern advances in the application of deep learning for finance.
Introduction from Master of Ceremonies
Keynote speaker: Stefan Zohren
Three-course dinner complemented with table discussion points
Wrap up from table champions and closing remarks from host