Risk Measures for DC Pension Plan Decumulation

TL;DR

This paper develops and compares optimal decumulation strategies for DC pension plans using various tail risk measures, providing computational methods and robustness testing under market uncertainty.

Contribution

It introduces a unified framework for optimal DC decumulation strategies incorporating different tail risk measures and demonstrates their computational determination and robustness.

Findings

Optimal controls for expected reward and certain risk measures coincide.

Strategies are computationally derived using a parametric market model.

Robustness is validated through out-of-sample testing with historical data.

Abstract

As the developed world replaces Defined Benefit (DB) pension plans with Defined Contribution (DC) plans, there is a need to develop decumulation strategies for DC plan holders. Optimal decumulation can be viewed as a problem in optimal stochastic control. Formulation as a control problem requires specification of an objective function, which in turn requires a definition of reward and risk. An intuitive specification of reward is the total withdrawals over the retirement period. Most retirees view risk as the possibility of running out of savings. This paper investigates several possible left tail risk measures, in conjunction with DC plan decumulation. The risk measures studied include (i) expected shortfall (ii) linear shortfall and (iii) probability of shortfall. We establish that, under certain assumptions, the set of optimal controls associated with all expected reward and expected shortfall Pareto efficient frontier curves is identical to the set of optimal controls for all expected reward and linear shortfall Pareto efficient frontier curves. Optimal efficient frontiers are determined computationally for each risk measure, based on a parametric market model. Robustness of these strategies is determined by testing the strategies out-of-sample using block bootstrapping of historical data.