Ronald is Principal Investigator of the project ReKlaSat 3D (Reconstruction and Classification of Satellite Images) using contemporary Deep Learning technologies at the WU Vienna University of Economics and Business as well as President and CEO of the Academy of Data Science in Finance (dsf.academy). He is actively teaching Quantitative Finance, Machine Learning and AI at different WU Executive Academy MBA programs as well as various Bachelor and Master programs at the WU Vienna University of Economics and Business, Austria and the University of Bergamo, Italy.
Contemporary Deep Learning Methods for Building Investment Models Based on Graphical Time-series Representations
AI and Machine Learning methods can be used to generate investment decisions successfully. A clever combination of Data Science methods with methods from the field of Decision Science (Prescriptive Analytics) may lead to even more successful models. In this talk a general outline for such a successful methodological combination will be presented as well as a concrete novel Deep Learning investment model which is based on graphical TTR series representations instead of using time-series directly. It will be shown how important Feature Engineering for Deep Learning in Finance actually is.