Thalesians/QFGG (Frankfurt) - Dr. Miguel Vaz - Finding structure in fin data

NOTE: the event is at 6.30pm Frankfurt time (please ignore the Outlook invite time)

Full title: Thalesians/Quant Finance Group Germany (Frankfurt) - Dr. Miguel Vaz - Finding structure in financial data: from point clouds to graphs

Thanks for Jochen Papenbrock and Adrian Zymolka for organising and for d-fine for hosting. Tickets will be FREE for this event!

You can access the Thalesians/Quant Finance Germany (Frankfurt) LinkedIn Group page here (https://www.linkedin.com/grp/home?gid=8321682).

Abstract

Choosing the right model for your problem or application is a challenging task. It requires a fine balance between correctness and complexity, so that problems are solved but implementation, maintenance and communication efforts are minimized.

Knowing the underlying structure of the data is an important step in the process. In many real-world problems, the structure will be inferred from data and can be seen as a graph or network, describing dependencies between the model's variables or even the observations of these variables.

Graph and network theory complement the classic linear algebra literature by giving precise definitions for intuitive concepts such as connectedness, centrality, or community. I will talk about their usage in quantitative finance problems using concrete examples:

• the usage of network and centrality measures as a diversification criterion in asset allocation
• market phase characterization and detection of asset groups,
• identifying concentration risks in credit portfolios.

Colorful diagrams and real code will complement and illustrate the concepts.

Speaker: Currently with d-fine GmbH, Dr. Miguel Vaz works as a risk management consultant for large financial institutions, with a focus on the quantitative and functional aspects of market risk. In a former life, or so it feels like sometimes, Miguel researched learning methods for interacting with a humanoid robot at the Honda Research Institute Europe. Miguel is passionate about (financial) network models, information visualization, robots and all things communication and interaction.