Joined-Up Pensions Policy in the UK: An Asset-Libility Model for Simultaneously Determining the Asset Allocation and Contribution Rate

The trustees of funded defined benefit pension schemes must make two vital and inter-related decisions - setting the asset allocation and the contribution rate. While these decisions are usually taken separately, it is argued that they are intimately related and should be taken jointly. The objective of funded pension schemes is taken to be the minimization of both the mean and the variance of the contribution rate, where the asset allocation decision is designed to achieve this objective. This is done by splitting the problem into two main steps. First, the Markowitz mean-variance model is generalised to include three types of pension scheme liabilities (actives, deferreds and pensioners), and this model is used to generate the efficient set of asset allocations. Second, for each point on the risk-return efficient set of the asset-liability portfolio model, the mathematical model of Haberman (1992) is used to compute the corresponding mean and variance of the contribution rate and funding ratio. Since the Haberman model assumes that the discount rate for computing the present value of liabilities equals the investment return, it is generalised to avoid this restriction. This generalisation removes the trade-off between contribution rate risk and funding ratio risk for a fixed spread period. Pension schemes need to choose a spread period, and it is shown how this can be set to minimise the variance of the contribution rate. Finally, using the result that the funding ratio follows an inverted gamma distribution, shortfall risk and expected tail loss are computed for funding below the minimum funding requirement, and funding above the taxation limit. This model is then applied to one of the largest UK pension schemes - the Universities Superannuation Scheme

Optimal enterprise risk management and decision making with shared and dependent risks

Includes bibliographical references (pages 27-29).Published as: Journal of Risk and Insurance, vol. 84, no. 4, December 2017, pp. 1127–1169. https://doi.org/10.1111/jori.12140.Dynamic enterprise risk management (ERM) entails holistic decision-making for critical corporate functions such as capital budgeting and risk management. The interplay across business divisions, however, is complicated due to their natural interactions through the shared and dependent risk exposures within an intricate corporate structure. This paper develops an integrated optimization framework via a copula-based decision tree interface to facilitate ERM decision making to meet the specified enterprise goal in a multi-period setting. We illustrate our model and provide managerial insights with a case study for a financial services company engaged in both banking and insurance businesses

Accountants\u27 index. Twenty-eighth supplement, January-December 1979, volume 1: A-L

https://egrove.olemiss.edu/aicpa_accind/1033/thumbnail.jp

Multi-Objective Stochastic Optimization Programs for a non-Life Insurance Company under Solvency Constraints

In the paper, we introduce a multi-objective scenario-based optimization approach for chance-constrained portfolio selection problems. More specifically, a modified version of the normal constraint method is implemented with a global solver in order to generate a dotted approximation of the Pareto frontier for bi- and tri-objective programming problems. Numerical experiments are carried out on a set of portfolios to be optimized for an EU-based non-life insurance company. Both performance indicators and risk measures are managed as objectives. Results show that this procedure is effective and readily applicable to achieve suitable risk-reward tradeoff analysis