dc.contributor.advisor | 黃泓智 | zh_TW |
dc.contributor.author (作者) | 張乃懿 | zh_TW |
dc.contributor.author (作者) | Chang, Nai Yi | en_US |
dc.creator (作者) | 張乃懿 | zh_TW |
dc.creator (作者) | Chang, Nai Yi | en_US |
dc.date (日期) | 2004 | en_US |
dc.date.accessioned | 2009-09-18 | - |
dc.date.available | 2009-09-18 | - |
dc.date.issued (上傳時間) | 2009-09-18 | - |
dc.identifier (其他 識別碼) | G0913580181 | en_US |
dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/34157 | - |
dc.description (描述) | 碩士 | zh_TW |
dc.description (描述) | 國立政治大學 | zh_TW |
dc.description (描述) | 風險管理與保險研究所 | zh_TW |
dc.description (描述) | 91358018 | zh_TW |
dc.description (描述) | 93 | zh_TW |
dc.description.abstract (摘要) | 本研究中以隨機模擬的方法應用於退休金最佳控制理論中,並將下跌風險(Downside Risks)加入二次最佳化函數中作為最適化準則,再以英國與美加地區不同提撥率模型做為研究對象,觀察不同情境下之結果。Haberman(1994)首先提出以最適化方法應用於固定給付制退休金基金上,並具體建立二次最適化準則,以提撥與資產的變異作為控制因子。Chang(2003)以下跌風險的觀念,指出退休金基金經營時管理人常較注意提撥過多與資產不足風險,若經營時考慮下跌風險,則會產生與原來考量不同之結果。本文以Chang(2003)之研究為基礎,將其建議之最佳化函數做為考量下跌風險之依據,並提出改良英國與美加地區之提撥率模型,採模擬的方式進行最佳化,探討其對不同提撥率模型之影響。研究結果發現若以隨機模擬作為最佳控制方法,在不同人口假設及精算模型下,會產生相同之結果,且發現下跌風險對於不同提撥率模型有不同之影響,其中建議的英式模型有效降低風險,而美式提撥率模型對於提撥率比例與資產負債比例在最佳化下有較理想之結果。最重要的,退休金基金管理人可利用隨機模擬的方式進行最佳化控制,以提供決策之參考依據。 | zh_TW |
dc.description.tableofcontents | 第一章、 緒論 1第一節 研究動機與目的 1第二節 文獻回顧 3第二章、 研究方法與模型 13第一節 研究方法 13第二節 精算模型 14第三節 提撥率模型 20第四節 最佳化模型 22第三章、 數值結果與分析 24第四章、 結論與建議 39第一節 結論 39第二節 後續研究之建議 41表目錄表一、最適化下風險、提撥率與資產比例模擬結果 25表二、最適化投資組合與攤提策略模擬結果 34表三、最適化下風險、提撥率與資產比例模擬結果(權重降低) 36表四、最適化下風險、提撥率與資產比例模擬結果(模擬時間縮短) 37圖目錄圖一、改進英式提撥模型之提撥率走勢 29圖二、英式提撥模型之提撥率走勢 30圖三、美式提撥模型提撥率走勢 31圖四、改進英式提撥模型資產負債比例走勢 32圖五、英式提撥模型資產負債比例走勢 32圖六、美式提撥模型資產負債比例走勢 33 | zh_TW |
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dc.language.iso | en_US | - |
dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0913580181 | en_US |
dc.subject (關鍵詞) | 下跌風險 | zh_TW |
dc.subject (關鍵詞) | 最佳化退休金基金 | zh_TW |
dc.subject (關鍵詞) | 隨機模擬 | zh_TW |
dc.subject (關鍵詞) | downside risks | en_US |
dc.subject (關鍵詞) | optimal pension planning | en_US |
dc.subject (關鍵詞) | stochastic simulation | en_US |
dc.title (題名) | 固定給付制退休金之最佳控管:隨機模擬方法之應用 | zh_TW |
dc.type (資料類型) | thesis | en |
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