The Economic Scenario Generators are at the core of stochastic models used by insurance companies. The applications of stochastic models are very diverse and include such applications as economic capital under Solvency II, ALM projections, dynamic hedging etc. All these applications impose different requirements upon the generation and the validation of economic scenarios.

Organised by the EAA - European Actuarial Academy GmbH GmbH in cooperation with the Svenska Aktuarieföreningen.

This web session has NOT been designed for those participants eager to find out which capital market scenario will materialize in the coming months and years so that they can maximize their wealth. Unfortunately, we have lost our crystal ball, which is a real shame.

This course has been developed for professionals who are interested in Economic Scenario Generators because they deal with one or more applications of those and who are familiar with the basic concepts of financial maths. In-depth knowledge of capital market models is clearly NOT a pre-requisite, as the content does not aim at ESG experts.

Technical requirements and test session
Please check with your IT department if your firewall and computer settings support web session participation (the programme GoToTraining is used for the web session). Please also make sure that you are joining the web session with a stable internet connection. 

On 23 March 2020, 10:00 – 10:30 CET, there will be a test session offered to all registered participants to test the software.

In the web session, we begin by describing random number simulation techniques, which underpin ESG work. We also talk about variance reduction techniques, which improve the efficiency / the precision of stochastic modelling. We move on to discuss risk-neutral equity modelling and interest rate modelling. We conclude our program on day 1 by considering real-world scenario generation.

On day 2, we talk about ESG validation aspects before moving on to the ESG applications. First, we introduce the ESG Rebasing technology, which allows the users to produce univariate and combined stress scenarios by recycling their baseline ESG package. We continue by discussing a case study of a UK Internal Model Firm, which has implemented Daily Solvency Monitoring to operationalize their Solvency II calculations for risk management purposes.

Pierre-Edouard Arrouy
is leading the financial modelling team inside the Research & Development section of Milliman Paris; his consulting work relates to the design, the implementation and the review of financial models within risk-neutral and real-world ESGs. His current research topics deal with calibration methods for interest rates models with stochastic volatility, modelling of credit risk, as well as the pricing of complex derivatives. He is also actively involved in the development of the cloud based ESG solution Milliman CHESS.

Michael Leitschkis
is a Principal with Milliman. Michael has been dealing with various ESG aspects for about 15 years, notably in the context of Solvency II, including proxy modelling techniques such as Least Squares Monte Carlo. He has been part of the German Actuarial Society (DAV) working party dedicated to Economic Scenario Generators and taught Financial Mathematics at the University of Cologne.

Russell Ward
is a Principal with Milliman, focusing on capital modelling, guarantee product development and ALM all of which involve the use of ESGs. Prior to joining Milliman, Russell headed Ernst & Young’s actuarial modelling services for Europe leading implementation of stochastic asset-liability models and the review of ESGs for some of the firm’s audit clients. While on secondment to the FSA, Russell played a key role in the development of the regulator’s approach to the review of risk-based capital under the Individual Capital Assessment (ICA) regime.