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Abstract

The thesis discusses various actuarial aspects of the management of a pension fund, in particular, those related to valuation of the pension fund. The investigation covers three main areas; the funding mechanism, investment and matching and control of the fund. In the part dealing with the funding mechanism, a model is introduced in order to assist analyses of the mechanism of a pension fund. The model notionally separates the fund into individual pots and a common pool, and notional moves of the assets between them, X-functions, are defined. Using this model, various events in the pension fund are analysed. Particularly, the model is shown to be useful for explaining the financial impact of withdrawals and the problem of cross-subsidy. In the next part, investment and matching are discussed referring to a collection of papers and books written by actuaries and economists. Two different types of matching are defined according to the definition of risk, which are named V-matching and S-matching. Based on this discussion on matching, the meanings of the use of a particular portfolio for valuation purposes are analysed. Finally, various means of controlling a pension fund are discussed in the light of control theory. A particular focus is set on the choice of the valuation basis as a means of control, and an extensive series of long term cashflow projections are carried out to explore the optimum way to choose the valuation basis under various scenarios of changing experience. The projections are carried out separately for three different aspects of the experience; the real rate of investment return, the dividend growth rate and the dividend yield, and the withdrawal rates. The results suggest that the use of averages of past experience over a long period suits best for different circumstances, and that delayed changes in the valuation basis after the corresponding changes in experience are useful for identifying more clearly the trend in the actual experience.

Publication Type:	Thesis (Doctoral)
Subjects:	H Social Sciences > HA Statistics
Departments:	Bayes Business School > Actuarial Science & Insurance > Statistical Research Reports Doctoral Theses Bayes Business School > Bayes Business School Doctoral Theses

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