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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

考量保險業加入國外投資之最適組合 / Incorporating Foreign Equities in Optimal Portfolio Selection for Insurers and Investors with Significant Background Risks

洪莉娟, Li-Chuan Hung Unknown Date (has links)
本研究探討面臨顯著背景風險(諸如核保等風險)金融機構之投資策略,考量加入國外投資風險下,該金融機構如何決定最適動態資產配置策略,為充分反映市場風險、匯率風險及核保風險,本研究以隨機方程式描述資產價值及核保經驗之變動,並以假想之人壽保險公司作為討論對象,預估未來現金流量並建構公司財務資訊相關之隨機模型,給定最低資本限制下,於指定投資期限內達到全期淨值(盈餘)最佳效用值為目標。本文依照給定之背景風險建構隨機控制模型,利用動態規劃法求出最適資產配置。結果顯示最適投資組合將由三項要素組成:1.極小化盈餘變化之變異數之部位;2.類似於短期投資組合策略之避險部位;以及3.用以規避背景風險之避險部位。因為模型複雜性之限制,以逼近馬可夫理論之數值方法計算最適投資策略。 / This paper analyzes the optimal asset allocation for insurers and investors who are required to cope with significant background risks due to underwriting uncertainties and interest rate risks among a set of stochastic investment opportunities. In order to hedge properly the country risks due to local volatile financial market, the foreign investment opportunities are included in the optimal portfolio decision. In this study, detailed formulation using the projected cash flows of a hypothetical life insurance company and its related stochastic phenomena are constructed. The insurers are assumed to maximize the expected discounted utility of their surplus over the investment horizon under the minimal capital requirement. Our problem is formulated as a stochastic control framework. According to the optimal solution, the optimal portfolio can be characterized by three components: a hedging component minimizing the variance of the change in surplus, a hedging component familiar to myopic portfolio rule, and a risk hedging component against the background risks. Since the explicit solutions cannot be achieved due to model complexity, the Markov chain approximation methods are employed to obtain the optimal control solutions in our numerical illustration.

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