Essays on robust portfolio selection and pension finance
Data(s) |
2016
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Resumo |
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. |
Formato |
text text |
Identificador |
http://centaur.reading.ac.uk/64081/12/21024185_Platanakis_thesis.pdf http://centaur.reading.ac.uk/64081/2/21024185_Platanakis_form.pdf Platanakis, E. (2016) Essays on robust portfolio selection and pension finance. PhD thesis, University of Reading. |
Idioma(s) |
en en |
Relação |
http://centaur.reading.ac.uk/64081/ |
Tipo |
Thesis NonPeerReviewed |