INFINITECH Stakeholders Workshop Series: “BigData and Artificial Intelligence for Portfolio Risk Assessment”

Published On: March 16th, 2021| Tags: , , , , |

VIDEO

INFINITECH Workshop - BigData and Artificial Intelligence for Portfolio Risk Assessment - Session 1

INFINITECH Workshop - BigData and Artificial Intelligence for Portfolio Risk Assessment - Session 2

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Speakers

  • Pablo Carballo Nieto, Prive Technologies, Gmbh. Austria;
  • Nikolaos Droukas, National Bank of Greece;
  • Dr. Richard Mccreadie, University of Glasgow, UK;
  • Petra Ristau, JRC Capital Management, Gmbh, Germany;
  • George Fatouros, INNOV-ACTS Ltd, Cyprus and George Markidis, University of Pireaus, Greece.

Description

How AI and BigData Enables Novel Approaches to Portfolio Risk Assessment and Asset Management.

Workshop Agenda

Session 1: Portfolio Risk Assessment and Value-at-Risk Calculation

  • 09:30 – 09:40: Workshop Introduction
  • 09:40 – 10:00: “Data-Driven Customer Risk Assessment for Personalized Asset Recommendations”, Pablo Carballo Nieto, Prive Technologies, Gmbh. Austria
  • 10:00 – 10:20: “An Automated, Personalized, Investment Recommendations System for Retail Customer”, Nikolaos Droukas, National Bank of Greece
  • 10:20 – 10:25: Short Break
  • 10:25 – 10:45: “What Investments are Right for You?: Supporting Financial Advisors with Customer Risk Aware Investment Recommendations”, Dr. Richard Mccreadie, University of Glasgow, UK
  • 10:45 – 11:00: “Value at Risk (VaR) Assessment Challenges in High Frequency Trading”, Petra Ristau, JRC Capital Management, Gmbh, Germany
  • 11:00 – 11:15: “Machine Learning Techniques for Value at Risk (VaR) Calculation”, George Fatouros, INNOV-ACTS Ltd, Cyprus and George Markidis, University of Pireaus, Greece
  • 11:15 – 11:25: Break

Session 2: Demonstrations, Open Discussion and Stakeholders Feedback

  • 11:25 – 11:45: System Demonstrations
  • 11:45 – 11:55: Open Questions and Answers Session – (Questions from the Audience)
  • 11:55 – 12:00: Meeting Close & Conclusions

Duration

2h30

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