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    政大典藏 > College of Commerce > Department of MIS > Theses >  Item 140.119/31134


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/31134


    Title: 應用模擬最佳化來求解產險公司之資產配置的兩篇論文
    Authors: 黃孝慈
    Contributors: 陳春龍
    蔡政憲
    黃孝慈
    Keywords: 模擬最佳化
    財產保險
    資產配置
    simulation optimization
    property-casualty insurance
    asset allocation
    Date: 2008
    Issue Date: 2009-09-14 09:19:12 (UTC+8)
    Abstract: 當產險公司需要同時兼顧競爭力並免於破產時，適當的資產配置就是一項相當重要的決策。然而採用均數-變異數分析(mean‐variance analysis)將受到許多限制，而動態控制理論則是難以實作，因此，我們提出一個新的解決方法。這個方法主要係應用模擬最佳化的演算法，例如基礎的基因演算法(basic genetic algorithm, GA)，多階層演化策略(multi-phase evolutionary strategies, MPES)及多階層基因演算法(multi-phase genetic algorithm, MPGA)等並結合模擬模型，來求解保險公司之資產配置的問題。首先我們建立投資市場及保險業務市場的模擬模型，之後再利用本研究所發展出新的最佳化演算法來搜尋最佳的資產配置。在實務上無法實現的多期投資策略，在我們的研究架構下得以被採用，並且在比較求解結果下，多期投資策略(reallocation strategies)較定額投資策略(re‐balancing strategies)有顯著較佳的績效。在兼顧保險公司投資收益並避免破產的目標函數下，我們所提出的研究方法已證明可以用來協助保險公司建立較佳的資產配置。
    Proper asset allocations are vital for property‐casualty insurers to be competitive and remain solvent. However, popular mean‐variance analysis is limited while dynamic control theory is difficult to implement. We thus propose to apply simulation optimizations such as basic genetic algorithm (GA), multi‐phase evolutionary strategies (MPES) and multi‐phase genetic algorithm (MPGA) to the asset allocation problems of the insurers. We first construct a simulation model of the property‐casualty insurer and then develop simulation optimization techniques to search optimal investment strategies upon the simulation results.
    The resulted reallocation strategies perform better than re‐balancing strategies used in practice with significant margins. Therefore, our proposal researches can be used to assist insurers to construct better asset allocations.
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    Description: 博士
    國立政治大學
    資訊管理研究所
    92356508
    97
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0923565081
    Data Type: thesis
    Appears in Collections:[Department of MIS] Theses

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