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Risk diversification is at the heart of insurance. In a modern
Enterprise Risk Management (ERM) approach, a company's entire risk
profile - including risk diversification and concentration - must
be considered in decision-making processes such as insurance
pricing, product design, asset allocation and reinsurance. The
impact on risk-oriented performance measures such as return on
risk-adjusted capital (RORAC) and economic value added (EVA) must
also be assessed.For risk managers, it is therefore essential to
assess not only the overall risk of the enterprise, but also the
impact of individual risks, business units and hedging instruments
on the overall risk. In this context, the term "capital allocation"
is a widely discussed and used concept. The gradient (also known as
Euler) capital allocation principle plays an important role. The
principle is directly linked to "marginal capital requirements" and
is compatible with the performance measures mentioned
above.However, the proper implementation of capital allocation in
risk management, risk limiting, and decision making often imposes
significant challenges. On the computational side, the gradient
allocation principle requires determining the derivative of the
risk measure-typically Value-at-Risk or Expected Shortfall-with
respect to business volumes or other decision variables. Obtaining
these derivatives is numerically challenging, especially when risk
measurement relies on Monte Carlo simulations. We demonstrate
methods to enhance the stability of these estimations, such as
kernel estimation. In addition, the allocation has the limitation
of accounting only for the risk diversification effects of the
current portfolio, which can easily become invalid if the portfolio
changes and new risk concentration and diversification patterns
emerge. To tackle this issue, we present a recently developed
methodology called "Orthogonal Convexity Scenarios" (OCS), which
helps to proactively identify potentially adverse portfolio shifts
and integrate them into risk management and business
steering.Participants will gain an in-depth understanding of two
techniques for allocating aggregate capital to business units or
individual risks that are valuable for risk assessment and business
management.Using R, we provide a practical case study on the (often
challenging) estimation of gradient capital allocation and
Orthogonal Convexity Scenarios using kernel estimation methods,
providing in-depth guidance on how to apply the two methods in
practice.Your early-bird registration fee is € 150.00 (net) / €
178.50 (incl. VAT, if applicable) for bookings by 18 December 2024.
After this date, the fee will be € 195.00 (net) / € 232.05 (incl.
VAT, if applicable).
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