Mean-variance criterion in optimization AL problem aims at maximizing the final surplus; asset value minus liability value, subject to a given variance of the final surplus or, equivalently, minimizing the variance of the final surplus subject to a given expected final surplus. The stochastic optimal control theory is employed to analytically solve the AL management problem in continuous-time setting. Then the comparison of derived optimal AL management policy and the literatures are examined and the discrepancy in objectives between equity holders and investors of a mutual fund is discussed finally. / Portfolio selection in asset-liability (AL) management is to seek the best allocation of wealth among a basket of securities with taking into account the liabilities. There are a lot of portfolio selection criteria among in the literature. The two of them are mean-variance criterion and Roy's safety-first principle. This thesis investigates the optimal asset allocation for an investor who is facing an uncontrollable liability under either one of these two portfolio constructions. The relation between these two different principles are discussed in the context of AL management. / Roy's safety-first principle (Roy, 1956) asserts that the investor would specify a threshold level of the final surplus below which the outcome is regarded as disaster. The objective is then to minimize the ruin probability or the chance of disaster subject to a constraint that the expected final surplus is higher than the threshold. Roy however solves this problem by minimizing an upper bound of the ruin probability based on the Bienayme-Chebycheff inequality. With the same consideration of Roy, the analytical trading strategy of the safety-first. AL management, problem, in the sense of surplus, under both continuous- and multi-period-time settings are derived. We link this surrogated safety-first principle to the mean-variance ones. / The final objective of this thesis attacks the genuine safety-first AL problem. Without replacing the ruin probability in the objective function by its upper bound, we use a martingale approach and consider the funding ratio which is the total wealth divided by the total liability. Two important situations in the literature are investigated. In the first situation, the mean constraint of the original problem is removed, We show that removing the mean constraint makes the problem become a target reaching problem that can be solved analytically. However, the essence of safety-first is lost. In the second case in which the mean constraint is there, the problem becomes ill-posed and is then solved using an approximation using a martingale approach. The approximation relies on the assumption that the investor gives up unreasonably high profits and sets an upper bounded for the final funding ratio. / Chiu, Mei Choi. / "July 2007." / Adviser: Duan Li. / Source: Dissertation Abstracts International, Volume: 69-02, Section: B, page: 1304. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 121-126). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest dissertations and theses, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract in English and Chinese. / School code: 1307.
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_344063 |
| Date | January 2007 |
| Contributors | Chiu, Mei Choi., Chinese University of Hong Kong Graduate School. Division of Systems Engineering and Engineering Management. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, theses |
| Format | electronic resource, microform, microfiche, 1 online resource (x, 141 p. : ill.) |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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