Roberto-Rafael is interested in the application of neural networks for causal inference and its potential uses when dealing with high dimensional data, in particular in the context of financial data and asset pricing problems.
Roberto-Rafael has a BSc in Mathematics (2018) and a BA in Business (2020), both from the University of Barcelona. During his undergraduate studies, he did an exchange year in the University of Pennsylvania-Wharton. He has worked for the tech. department of JP Morgan, implementing machine learning tools (NLP, Neural Networks) in the investment banking division; and at the Bank of Spain, applying Neural Networks to credit default prediction.
Econometrics, Machine Learning, Asset Pricing
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