1 hr 32 min

Beyond Markowitz With Machine Learning in Portfolio Management with Alejandro Rodriguez Dominguez The Ensemble Podcast, by CrunchDAO

    • Mathematics

Alejandro Rodriguez Dominguez is Head of Quantitative Research and Analysis at Miralta Bank, Madrid. With extensive experience in financial engineering, he leads Data Analytics and Solutions in Quantitative Finance for the group. Through the creation of AI financial solutions for their clients, Alejandro develops data architecture for both regulatory and strategic reporting. Alongside the modeling and implementation of risk management practices for Miralta Bank, he creates data-driven market analysis tools for brokerage clients.


Alejandro holds a PhD in Computer Science from the University of Reading, and a Master’s degree in Artificial Intelligence from Munster Technological University. His research interests include Solutions for Continual Learning and Catastrophic Forgetting in AI, Information Geometry and AI, Correlation Dynamics (changes and forecasting), AI for Pricing, and Risk Management of Financial Products, and Systematic Trading Strategies with a focus on Pricing, Nowcasting, Dynamical Systems, and Statistics and Probability.


Our conversation focused on the interaction of classic quantitative finance with machine learning, the use of random matrix theory in finance.


Hosted by Ausha. See ausha.co/privacy-policy for more information.

Alejandro Rodriguez Dominguez is Head of Quantitative Research and Analysis at Miralta Bank, Madrid. With extensive experience in financial engineering, he leads Data Analytics and Solutions in Quantitative Finance for the group. Through the creation of AI financial solutions for their clients, Alejandro develops data architecture for both regulatory and strategic reporting. Alongside the modeling and implementation of risk management practices for Miralta Bank, he creates data-driven market analysis tools for brokerage clients.


Alejandro holds a PhD in Computer Science from the University of Reading, and a Master’s degree in Artificial Intelligence from Munster Technological University. His research interests include Solutions for Continual Learning and Catastrophic Forgetting in AI, Information Geometry and AI, Correlation Dynamics (changes and forecasting), AI for Pricing, and Risk Management of Financial Products, and Systematic Trading Strategies with a focus on Pricing, Nowcasting, Dynamical Systems, and Statistics and Probability.


Our conversation focused on the interaction of classic quantitative finance with machine learning, the use of random matrix theory in finance.


Hosted by Ausha. See ausha.co/privacy-policy for more information.

1 hr 32 min