The future returns for property required by UK pension funds

In the 1970s Real Estate represented over 17% of the average pension funds total assets. Today such funds hold less than 4%, a figure not seen since the 1960s. This reduction in Real Estate holdings is mainly attributable to the relatively poor performance of Real Estate against other asset classes since the 1980s. Whether pension funds will increase their holding at any point in the future depends therefore on the expected return of Real Estate by comparison with that required to justify a particular asset holding. Using the technique of Modern Portfolio Theory (MPT), this paper assesses the required return that Real Estate would have to offer to justify a 15% holding in a mixed asset portfolio. This figure and the risk/return characteristics of the major asset classes is taken from survey data. Under a number of scenarios it is found that Real Estate can play a part in a mixed asset portfolio at the 15% level. In some cases however, the expected returns of Real Estate are not sufficient to justify a weight of 15% in this asset.

The future returns for property required by UK pension funds: the BHS data

Previous studies of the place of Property in the multi-asset portfolio have generally relied on historical data, and have been concerned with the supposed risk reduction effects that Property would have on such portfolios. In this paper a different approach has been taken. Not only are expectations data used, but we have also concentrated upon the required return that Property would have to offer to achieve a holding of 15% in typical UK pension fund portfolios. Using two benchmark portfolios for pension funds, we have shown that Property's required return is less than that expected, and therefore it could justify a 15% holding.

Required returns for real estate in UK pension fund portfolios

The position of Real Estate within a multi-asset portfolio has received considerable attention recently. Previous research has concentrated on the percentage holding property would achieve given its risk/return characteristics. Such studies have invariably used Modern Portfolio Theory and these approaches have been criticised for both the quality of the real estate data and problems with the methodology itself. The first problem is now well understood, and the second can be addressed by the use of realistic constraints on asset holdings. This paper takes a different approach. We determine the level of return that Real Estate needs to achieve to justify an allocation within the multi asset portfolio. In order to test the importance of the quality of the data we use historic appraisal based and desmoothed returns to examine the sensitivity of the results. Consideration is also given to the Holding period and the imposition of realistic constraints on the asset holdings in order to model portfolios held by pension fund investors. We conclude, using several benchmark levels of portfolio risk and return, that using appraisal based data the required level of return for Real Estate was less than that achieved over the period 1972-1993. The use of desmoothed series can reverse this result at the highest levels of desmoothing although within a restricted holding period Real Estate offered returns in excess of those required to enter the portfolio and might have a role to play in the multi-asset portfolio.

Asset liability modelling and pension schemes: the application of robust optimization to USS

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.

Pension scheme redesign and wealth redistribution between the members and sponsor: the USS rule change in October 2011

The redesign of defined benefit pension schemes usually results in a substantial redistribution of wealth between age cohorts of members, pensioners, and the sponsor. This is the first study to quantify the redistributive effects of a rule change by a real world scheme (the Universities Superannuation Scheme, USS) where the sponsor underwrites the pension promise. In October 2011 USS closed its final salary scheme to new members, opened a career average revalued earnings (CARE) section, and moved to ‘cap and share’ contribution rates. We find that the pre-October 2011 scheme was not viable in the long run, while the post-October 2011 scheme is probably viable in the long run, but faces medium term problems. In October 2011 future members of USS lost 65% of their pension wealth (or roughly £100,000 per head), equivalent to a reduction of roughly 11% in their total compensation, while those aged over 57 years lost almost nothing. The riskiness of the pension wealth of future members increased by a third, while the riskiness of the present value of the sponsor’s future contributions reduced by 10%. Finally, the sponsor’s wealth increased by about £32.5 billion, equivalent to a reduction of 26% in their pension costs.

Essays on robust portfolio selection and pension finance

This thesis examines three different, but related problems in the broad area of portfolio management for long-term institutional investors, and focuses mainly on the case of pension funds. The first idea (Chapter 3) is the application of a novel numerical technique – robust optimization – to a real-world pension scheme (the Universities Superannuation Scheme, USS) for first time. The corresponding empirical results are supported by many robustness checks and several benchmarks such as the Bayes-Stein and Black-Litterman models that are also applied for first time in a pension ALM framework, the Sharpe and Tint model and the actual USS asset allocations. The second idea presented in Chapter 4 is the investigation of whether the selection of the portfolio construction strategy matters in the SRI industry, an issue of great importance for long term investors. This study applies a variety of optimal and naïve portfolio diversification techniques to the same SRI-screened universe, and gives some answers to the question of which portfolio strategies tend to create superior SRI portfolios. Finally, the third idea (Chapter 5) compares the performance of a real-world pension scheme (USS) before and after the recent major changes in the pension rules under different dynamic asset allocation strategies and the fixed-mix portfolio approach and quantifies the redistributive effects between various stakeholders. Although this study deals with a specific pension scheme, the methodology can be applied by other major pension schemes in countries such as the UK and USA that have changed their rules.