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Jumping over a low hurdle: personal pension fund performance

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Abstract

This paper provides a comprehensive analysis of the annual and of the long-term performance of personal pension funds relative to their Primary Prospectus Benchmarks (PPBs) and T-bills. The study covers 9659 personal pension funds from across all 30 ABI investment sectors that operated in the UK in the 1980–2009 period. Of these, 4531 pension funds are compared against their PPBs. The performance measured by ordinary excess returns over the UK T-bills and over PPBs, as well as the Sharpe ratio, Sharpe ratio adjusted for skewness and kurtosis, Sortino ratio in relation to the UK T-bills and PPBs, and the Modigliani–Modigliani measure are calculated for arithmetic, geometric and log returns. We find convincing evidence that pension funds lack challenging long-term performance targets. We argue that the existing PPBs are easy to outperform given that funds are allowed to diversify in assets not included in their PPBs. We discuss policy implications of our findings.

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Notes

  1. In the UK, occupational pension provision has a longer history than state pension. Individual cases of an early form of occupational pensions have been recorded in the thirteenth and fourteenth centuries, although the first funded occupational pension was set up in 1743 to provide for widows of the Church of Scotland ministers. Personal pension plans were set up by the 1986 Social Security Act and became available from July 1988. In 2001 the Welfare Reform and Pensions Act 1999 introduced stakeholder pension schemes.

  2. For a discussion of the importance of using the right benchmark see Lakonishok et al. (1992), Shukla and Trzcinka (1994), Blake et al. (1999), Dor et al. (2003), Chan et al. (2009), Ferruz et al. (2010). Prospectus benchmarks have also been used by Sensoy (2009) in a study of mutual fund performance. Non-benchmark evaluations have also been proposed to mitigate problems with inappropriate benchmarking (e.g., Grinblatt and Titman 1993).

  3. E.g., Ippolito and Turner (1987), Lakonishok et al. (1992), Coggin et al. (1993), Brown et al. (1997), Ambachtsheer et al. (1998), Blake et al. (1999, 2002), Thomas and Tonks (2001), Blake (2003), Bailey et al. (2005), Chu and McKenzie (2008), Novy-Marx and Bauh (2011).

  4. E.g., investment skills of fund managers are studied by Henriksson (1984), Coggin et al. (1993), Daniel et al. (1997), Bollen and Busse (2005), Cohen et al. (2005), Cuthbertson et al. (2008), Fama and French (2010); tests for potential departures from the EMH are investigated by Brown and Goetzmann (1995), Elton et al. (1996, 2001, 2011), Carhart (1997), Blake and Timmermann (1998), Davis (2001), Bollen and Busse (2005), Cuthbertson et al. (2008), Ferruz et al. (2009), Huij and Verbeek (2009); practices of wooing investors are studied by Cooper et al. (2005), Massa (2003), Agudo and Lázaro (2005), Sensoy (2009), Aydogdu and Wellman (2011).

  5. For instance, in 2010 the UK funded pensions accounted for $1.9 trillion of AUM, i.e., they were twice as big as mutual funds which by the end of 2010 had only $0.85 trillion of AUM (ICI 2012).

  6. Owadally (2014) documents that pension losses follow nonlinear dynamic processes.

  7. “Reveal: The scandal of how pension providers rake in the money”, The Independent, 12 December 2010.

  8. There are strong time-series properties (e.g., long memory) in the higher frequency data (e.g., monthly, and even quarterly) which raised a question on stationarity. We use yearly data, and consequently, yearly panels. This gives first order autocorrelation in the residuals i.e. we have effectively “shortened” the memory effect.

  9. Given that T-bills are not totally risk free we also defined the Sharpe ratio using the standard deviation of R-Tbills and PPB-Tbill for the funds and the PPBs, respectively (e.g., Lo 2002). The results were practically identical which is consistent with the fact that the volatility of the annual fund and PPB returns is much higher than the annual volatility of the T-bills. We do not present these results, but they can be obtained from the authors on request.

  10. In the UK there is legal ambiguity as to whether pension funds are allowed to engage in short-selling. Hence, in practice funds either don’t short-sell or if they do, it is to a very small degree. Our data show that on average the short positions are below 0.1 % of funds’ AUM. Even if it is unlikely that the Sharpe ratios can be distorted by short-selling, we use the SharpeAdj to control for effects of non-normal distribution of returns.

  11. The small difference in the numbers of observations between Tables 2 and 3 results from the fact that a few funds created in the second half of 2007 are excluded from the performance analysis of 1980–2007 but enter the regressions for the 2008–2009 period.

  12. Given that it is rather unlikely that perfectly negative assets will be added to the existing portfolios, and there is a restriction on how much of these ‘non-PPB’ assets can be added (max 20 % according to the ABI classification), it is unlikely that the risk of this new, ‘extended’, portfolio can be reduced to zero.

  13. We do not present the corresponding YRs graphs to save space. They are very similar to the presented ones.

  14. There is growing pressure on pension funds providing define contribution schemes to disclose their full costs (“UK pension providers set to be forced to disclose costs”, Financial Times, 24 February 2014).

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Acknowledgments

The authors would like to thank an anonymous sponsor for funding Dr. Anastasia Petraki’s post-doctoral position at the Centre for Governance and Regulation (CGR), University of Bath, which made this research possible. We would also like to thank Morningstar for granting us access to their Morningstar Direct™ database, and participants of the Paris Financial Management Conference 2013, the 2014 ESRC-CMPO conference at the University of Bristol, and of seminars in the Hanken Business School, Maastricht University, University of Illinois at Chicago, D’Amore-McKim School of Business at the Northeastern University and NYU Stern School of Business, as well as the Editor, the Associate Editor, two anonymous Reviewers, Paul Grout, Lawrence Kryzanowski and Sofia Ramos for their useful comments.

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Correspondence to Anna Zalewska.

Appendix

Appendix

Classification of ABI sectors into investment style categories

Allocation

Equity

Fixed income

Other

Equity UK

Emerging markets

International markets

Balanced (up to 85 % equity) managed

Cautious (up to 60 % equity) managed

Defensive (up to 35 % equity) managed

Flexible (up to 100 % equity) managed

UK all companies

UK smaller companies

UK equity income

Global emerging markets equities

Asia Pacific excl. Japan

Asia Pacific incl. Japan

Europe excl. UK

Europe incl. UK

Global Equities

Japan Equities

North America

Global fixed interest

Global high yield

Sterling corporate bond

Sterling fixed interest

Sterling high yield

Sterling long bond

Sterling other fixed interest

UK index-linked gilts

UK gilt

Commodity/energy

Money market

Protected/guaranteed funds

Global property

UK direct property

Specialist

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Petraki, A., Zalewska, A. Jumping over a low hurdle: personal pension fund performance. Rev Quant Finan Acc 48, 153–190 (2017). https://doi.org/10.1007/s11156-015-0546-9

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