Abstract
In this article, we develop a framework for asset-liability management for pension funds in a time-varying volatility environment. We use sophisticated dynamic econometric models for the variances–covariances of the asset classes in which the pension fund is investing, while for the liability structure we employ two standard approaches that have been used in the relevant actuarial literature. The models implemented are used in the asset allocation process of the pension fund, as well as for risk management purposes. The constructed portfolios have significant economic value according to well-known performance measures.
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Notes
Formerly known as Salomon Brothers Pension Liability Index, available on the website of Society of Actuaries, www.soa.org.
Details about the use of downside risk measures in pension funding can be found in Haberman et al (2003).
The functional we use is the mean of the previous 12 monthly returns.
Data are from Bloomberg Professional Services.
Details can be found in Hedge Fund Research, www.hedgefundresearch.com.
Hedge fund returns can look better than they actually are, because of the empirical biases of the hedge fund databases that are used to construct the relevant indices. Some of the most common biases that arise are the self-selection bias and the survivor bias. Self-selection arises because funds voluntarily report their information to data vendors and may decide to stop doing so. Survivor bias occurs if the hedge funds database, and thus the index employed contains information only on ‘surviving’ funds, that is, funds that continue to operate and report information to the database vendor. Pension fund managers should keep these points in mind during the asset allocation process.
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Acknowledgements
The authors would like to acknowledge financial support from the Committee on Knowledge Extension Research’s (CKER) of the Society of Actuaries (SOA). Furthermore the authors would like to thank Citi Research for providing the Citigroup Pension Liability Index used. The usual disclaimer applies.
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1received his PhD degree in Statistics from Athens University of Economics and Business, Greece, in 2005. Currently he is Senior Lecturer in Finance at the department of Accounting, Finance and Governance, Westminster Business School, University of Westminster, London, UK and on academic leave from Department of Statistics and Insurance Science, University of Piraeus, Piraeus, Greece. His principal research is concerned with asset-liability management, predictability of financial and macroeconomic time series, actuarial and financial modeling, performance evaluation of fund managers and stochastic analysis with applications in insurance and finance.
2received his PhD degree in Statistics from Athens University of Economics and Business, Greece, in 2001. Currently, he is Assistant Professor at the department of Statistics, Athens University of Economics and Business. His main research interests include financial econometrics, optimal asset portfolio allocation, Bayesian inference and Bayesian model choice, time series modeling and analysis.
3received her PhD degree in Statistics from Lancaster University, UK, in 2005. She is currently Lecturer of Statistics at the department of Mathematics, University of Athens, Greece. Her research interests include Bayesian inference and model comparison, computational statistics, filtering methods and Markov chain Monte Carlo methods, econometrics and financial econometrics.
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Vrontos, S., Vrontos, I. & Meligkotsidou, L. Asset-liability management for pension funds in a time-varying volatility environment. J Asset Manag 14, 306–333 (2013). https://doi.org/10.1057/jam.2013.24
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DOI: https://doi.org/10.1057/jam.2013.24