11th Conference in Actuarial Science & Finance on Samos
May 25 - 29, 2022




After discussion in the frame of the scientific and organizing committee, the new conditions of the rapid expansion of Covid-19, compel us to postpone the Samos meeting. The new date is 25-29 May 2022.

The Department of Statistics and Actuarial – Financial Mathematics of the University of the Aegean is pleased to host the 11th Samos Conference in Actuarial Science and Finance, to be held on May 25 - 29, 2022. This event, jointly organized with the Katholieke Universiteit Leuven, the Kobenhavns Universitet and the New York University provides a forum for state-of-the-art results in the areas of insurance, finance and risk management. The meeting is open to people from Universities, Insurance Companies, Banks, Consulting Firms and Regulatory Authorities.

Topics
1. Stochastic Models in Non-Life Insurance (Chair: Jan Beirlant)
2. Risk Management (Chair: Fabio Bellini)
3. Financial Theory and Practice (Chair: Udi Makov)
4. Life, Health and Pension Insurance (Chair: Mogens Steffensen)
5. Risk and Stochastic Control (Chair: Serguei Foss)
6. Statistical and Computational Methods (Chair: Claude Lefevre)


Announcement



Days
Hours
Minutes
Registrations are open

Topics

1. Stochastic Models in Non-Life Insurance
(Chair: Jan Beirlant)
2. Risk Management
(Chair: Fabio Bellini)
3. Financial Theory and Practice
(Chair: Udi Makov)
4. Life, Health and Pension Insurance
(Chair: Mogens Steffensen)
5. Risk and Stochastic Control
(Chair: Serguei Foss)
6. Statistical and Computational Methods
(Chair: Claude Lefevre)

Why to Attend?

Attend ASF2020 in order to meet the leaders in the actuarial science and finance and keep abreast of all advances in the field.

Participate

Participate in ASF2020 in order to present your own research achievements and accomplishments and gain insight or new ideas from colleagues from Universities, Insurance Companies, Banks, Consulting Firms or Regulatory Authorities, interested in actuarial-financial mathematics. 

 

Speaker Lineup

Prof. Mogens Bladt

Professor, Applied Probability and Insurance Mathematics, University of Copenhagen, Denmark

Mogens graduated as a statistician from the University of Aarhus in 1991 and received his PhD from Alborg University in 1993. He then moved to the Institute for Applied Mathematics at the Universidad Nacional Autonoma de Mexico (UNAM) where he has done research in and taught applied probability with a view to ...
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Prof. Ruodu Wang

Associate Professor, Actuarial Science, University of Waterloo, Canada

Research areas – Statistics – Probability – Actuarial Science – Financial Engineering – Quantitative Risk Management – Operations Research
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Prof. Thomas S. Salisbury

Professor, Department of Mathematics and Statistics, York University, Canada

THOMAS S. SALISBURY received his BSc in 1979 from McGill University, and his PhD in mathematics in 1983 from the University of British Columbia. After a postdoctoral position at Purdue University, he moved to York University, in whose department of Mathematics and Statistics he is a Professor and former department ...
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Prof. Lukasz Delong

Associate Professor, Warsaw School of Economics, Poland

Scientific interests: · insurance and financial mathematics/statistics · backward stochastic differential equations · stochastic control theory · financial modelling with Lévy processes · Monte Carlo simulations · static and dynamic hedging of life insurance and financial liabilities · generalized linear ...
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Prof. Boualem Djehiche

Professor of Mathematical Statistics, KTH Royal Institute of Technology, Stockholm, Sweden

His research interests are in the area of Stochastic Analysis and include the Theory of Large Deviations, Superprocesses and Interacting Particle Systems, with applications in Euclidean Quantum Mechanics, Insurance Mathematics, Mathematical finance and Mathematical Epidemiology.
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Prof. Xavier Milhaud

Assistant Professor, Institute of Financial and Actuarial Sciences, University of Lyon1, France

Current research interests: -Statistical learning, machine learning, bagging and boosting, -Discriminant analysis, segmentation models, -Survival analysis, -Generalized linear models, -Finite mixture models, -Latent variables and hidden Markov models (regime switching).
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