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Global Asset Liability Management

Published online by Cambridge University Press:  10 June 2011

M. A. H. Dempster
Affiliation:
Centre for Financial Research, Judge Institute of Management, University of Cambridge, Cambridge CB2 1AG, U.K., Tel: +44(0)1223-339641, Fax: +44(0)1223-339652, Email: mahd2@cam.ac.uk
M. Germano
Affiliation:
Pioneer Investment Management Ltd, 5th Floor, 1 George's Quay Plaza, George's Quay, Dublin 2, Ireland., Tel: +353-1-636-4500, Fax: +353-1-636-4600, Email: matteo.germano@pioneerinvest.ie
E. A. Medova
Affiliation:
Centre for Financial Research, Judge Institute of Management, University of Cambridge, Cambridge CB2 1AG, U.K., Tel: +44(0)1223-339593, Fax: +44(0)1223-339652, Email: eam28@cam.ac.uk
M. Villaverde
Affiliation:
Centre for Financial Research, Judge Institute of Management, University of Cambridge, Cambridge CB2 1AG, U.K., Tel: +44(0)1223-339651, Fax: +44(0)1223-339652, Email: mv228@cam.ac.uk

Abstract

Dynamic financial analysis (DFA) is a technique which uses Monte Carlo simulation to investigate the evolution over time of financial models of funds, complex liabilities and entire firms. Although of increasing popularity, the drawback of DFA is the dearth of systematic methods for optimising model parameters for strategic financial planning. This paper introduces strategic DFA which employs the only recently mature technology of dynamic stochastic optimisation to fill this gap. The new approach is described in terms of an illustrative case study of a joint university/industry project to create a decision support system for strategic asset liability management involving global asset classes and defined contribution pension plans. Although the application of the system described in the paper is to fund design and risk management, the approach and techniques described here are much more broadly applicable to strategic financial planning problems; for example, to insurance and reinsurance firms, to risk capital allocation in financial institutions and trading firms and to corporate investment and business development involving real options. As well as describing the mathematical and statistical models used in the case study, the paper treats econometric estimation, asset return and liability scenario generation, model specification and optimisation, system evaluation and historical backtesting. Throughout the system visualisation plays an important role.

Type
Sessional meetings: papers and abstracts of discussions
Copyright
Copyright © Institute and Faculty of Actuaries 2003

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