CERA 0: A Refresher Course in Financial Mathematics & Risk Measurement
Announcement from the EAA organiser:
In computational science, deep learning probably is one of the most heralded techniques of present time and recent history, mainly due to its versatility and impressive achievements likewise. Indeed, applications of deep learning range from beating the (human) world champion of the highly complicated Go game to the promise of deploying self-driving cars in the near future, on a large scale and all over the world.
Deep learning (DL) pertains to the field of artificial intelligence and is great at extracting and mastering the often highly non-linear patterns of a given process, whatever this process might be. The only main requirement is the availability of a large amount of data that describes the behaviour of the process under different conditions and a truckload of computational power. However, since the price of data storage and the effort of sampling data has dropped dramatically over the last years, and since Moore’s law on the increase of computational power does even nowadays not show any signs of a slowdown, fitting deep learning models that are able to produce extremely useful predictions are a reality and this already for some years now.
The main purpose of this web session is to get the participants acquainted with DL models, and applications on text analysis will help achieving this. To this end, a healthy mix between theory and practice will be provided, however, it is important to note that some time will be spent to go through the theoretical foundations of neural networks and hence DL, as the inner workings of these models are a bit different from the ones of the classic statistical models. .
The web session is open to all persons who are interested in deepening their quantitative skills in the fields of financial mathematics and risk measurement.
Technical Requirements
Please check with your IT department if your firewall and computer settings support web session participation (the programme Zoom is used for this online training). Please also make sure that you are joining the web session with a stable internet connection.
Click here for reservation Your early-bird registration fee is € 450.00 plus 19% VAT for bookings by 13 October 2022. After this date, the fee will be € 585.00 plus 19% VAT.
Rüdiger Frey
Rüdiger Frey is Professor of Mathematics and Finance at the Vienna University of Economics and Business (WU). Prior to that, he held positions as Professor of Optimization and Financial Mathematics at the University of Leipzig and various academic positions at the University of Zurich and at the Federal Institute of Technology (ETH) in Zurich. He holds a diploma in mathematics from the University of Bonn where he received his PhD in financial economics in 1996. His main research fields are quantitative risk management, dynamic credit risk models and the pricing and hedging of derivatives under incompleteness and market frictions. Rüdiger has published research papers in leading international academic journals and has given seminars at a number of important international conferences and institutions. He is co-author of the popular book "Quantitative Risk Management: Concepts Techniques & Tools" (Princeton University Press, second edition 2015), which was rated as one of the Top 10 Technical Books of 2006 on Financial Engineering, by Financial Engineering News. Rüdiger has also been involved in consulting projects for Swiss and German insurance companies and banks and is frequently giving practitioner training courses.
Jochen Wolf
Since 2005, Jochen Wolf has been Professor for Mathematics and Economics at the Hochschule Koblenz. Before, he worked for several years at the German financial supervisor BaFin where he was responsible for various aspects of insurance supervision. At BaFin he was also involved in the Solvency II project. Prior to joining BaFin, Prof. Wolf held various research positions in stochastic analysis at Universität Jena and at the Université Paris-Nord. He holds a diploma in mathematics from the Universität Mainz and a doctorate in mathematics (focus probability) from the Universität Jena. Professor Wolf is actively involved in the actuarial education at the German actuarial association (DAV).