Sequential Monte Carlo Samplers for Capital Allocation Under Copula-Dependent Risk Models

In this paper we assume a multivariate risk model has been developed for a portfolio and its capital derived as a homogeneous risk measure. The Euler (or gradient) principle, then, states that the capital to be allocated to each component of the portfolio has to be calculated as an expectation conditional to a rare event, which can be challenging to evaluate in practice. We exploit the copula-dependence within the portfolio risks to design a Sequential Monte Carlo Samplers based estimate to the marginal conditional expectations involved in the problem, showing its efficiency through a series of computational examples.

Keywords: Risk Management, Capital Allocation, Sequential Monte Carlo (SMC), Copula Models

JEL Classification: C15, G21, G22

Suggested Citation: Suggested Citation

Targino, Rodrigo and Peters, Gareth and Shevchenko, Pavel V., Sequential Monte Carlo Samplers for Capital Allocation Under Copula-Dependent Risk Models (February 18, 2015). Insurance: Mathematics and Economics, Vol. 61, 2015, Available at SSRN: https://ssrn.com/abstract=2505539 or http://dx.doi.org/10.2139/ssrn.2505539