Prof. Mark Podolskij gives inaugural lecture

  • Faculty of Law, Economics and Finance (FDEF)
    Faculty of Science, Technology and Medicine (FSTM)
    14 February 2022
  • Category
  • Topic
    Finance, Mathematics

The Faculty of Science, Medicine and Technology (FSTM) and the Faculty of Law, Economics and Finance (FDEF) came together on 8 February 2022 to officially welcome Prof. Mark Podolskij, full professor of financial mathematics, to the University of Luxembourg with an in-person inaugural lecture and reception. Around 50 participants from both faculties gathered for Prof. Podolskij’s talk entitled “New developments in high dimensional statistics.”

Prof. Serge Haan, Vice-Dean of the FSTM and Prof. Katalin Ligeti Dean of the FDEF gave opening speeches, each underlining the transdisciplinary nature of Prof. Podolskij’s research in statistics, probability and financial mathematics. Affiliated to both the Department of Mathematics and the Department of Finance, Prof. Podolskij strengthens University of Luxembourg efforts to develop research and teaching excellence in statistics and applied data science. Prof. Haan cited the Master of Data Science, while Prof. Ligeti spoke about the Digital Transformation in Finance track of the Master of Science in Finance and Economics as new and innovative programmes which will benefit from Prof. Podolskij’s expertise. The two agreed that the addition of Prof. Podolskij further advances an already existing cooperation and partnership between the FSTM and the FDEF.

FDEF Dean Katalin Ligeti and FSTM Vice-Dean Serge Haan give opening speeches

Prof. Podolskij, who has previously taught at the University of Heidelberg and the University of Aarhus, is also an ERC Consolidator Grant holder with the project “STAMFORD: Statistical Methods for High Dimensional Diffusions”. At his inaugural lecture, he presented personal research on the emerging field of high dimensional statistics and its application, notably, to finance. Giving the example of global financial systems which contain many different clusters of networks with varying levels of connection, Prof. Podolskij explained that by using novel methods in high dimensional statistics which can account for models containing large numbers of parameters, it is possible to obtain information about the nature of these relationships, thereby identifying key players and dependencies. Such an analysis can be useful when applied to fields in finance such as risk management and asset pricing.

Prof. Podolskij explains his research

During the question-and-answer session following the lecture, a participant asked Prof. Podolskij what his next research pursuit would be. To answer, Prof. Podolskij referred to the complexity of high dimensional statistics and the various components which he has studied separately. “Now, I’d like to bring everything together,” he said, “to understand the whole picture.”