Asset Liability Modelling and Pension Schemes: The Application of Robust Optimization to USS

European Journal of Finance, Forthcoming

42 Pages Posted: 9 Apr 2014 Last revised: 18 Jan 2016

Emmanouil Platanakis

University of Bradford School of Management

Charles Sutcliffe

University of Reading - ICMA Centre

Date Written: January 17, 2016

Abstract

This paper uses a novel numerical optimization technique - robust optimization - that is well suited to solving the asset-liability management (ALM) problem for pension schemes. It requires the estimation of fewer stochastic parameters, reduces estimation risk and adopts a prudent approach to asset allocation. This study is the first to apply it to a real-world pension scheme, and the first ALM model of a pension scheme to maximise the Sharpe ratio. We disaggregate pension liabilities into three components - active members, deferred members and pensioners, and transform the optimal asset allocation into the scheme’s projected contribution rate. The robust optimization model is extended to include liabilities and used to derive optimal investment policies for the Universities Superannuation Scheme (USS), benchmarked against the Sharpe and Tint, Bayes-Stein, and Black-Litterman models as well as the actual USS investment decisions. Over a 144 month out-of-sample period robust optimization is superior to the four benchmarks across 20 performance criteria, and has a remarkably stable asset allocation - essentially fix-mix. These conclusions are supported by six robustness checks

Keywords: Robust Optimization; Pension Scheme; Asset-Liability Model; Sharpe Ratio; Sharpe-Tint; Bayes-Stein; Black-Litterman

JEL Classification: G11, G12, G22, G23

Suggested Citation

Platanakis, Emmanouil and Sutcliffe, Charles, Asset Liability Modelling and Pension Schemes: The Application of Robust Optimization to USS (January 17, 2016). European Journal of Finance, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2422303 or http://dx.doi.org/10.2139/ssrn.2422303

Emmanouil Platanakis

University of Bradford School of Management ( email )

Emm Lane
Bradford, West Yorkshire Bd9 4JL
United Kingdom

Charles M. Sutcliffe (Contact Author)

University of Reading - ICMA Centre ( email )

Whiteknights Park
P.O. Box 242
Reading RG6 6BA
United Kingdom

Paper statistics

Downloads
483
Rank
46,530
Abstract Views
3,373