| dc.contributor.advisor | 黃泓智 | zh_TW |
| dc.contributor.author (Authors) | 林昆亭 | zh_TW |
| dc.creator (作者) | 林昆亭 | zh_TW |
| dc.date (日期) | 2005 | 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 (Other Identifiers) | G0923580241 | en_US |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/34172 | - |
| 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) | 92358024 | zh_TW |
| dc.description (描述) | 94 | zh_TW |
| dc.description.abstract (摘要) | 現行各國的退休金計畫逐漸地由確定給付制轉變為確定提撥制。這表示投資的風險由原本退休金計畫的發起者(雇主)轉移到了參與者(員工)的身上。為了減少每個確定提撥制計畫參與者的投資風險，本文中採用退休時所得替代率為預估的目標，藉由模擬與最適化的方法找到最適投資策略與最適提撥率。 能反映出時間性的隨機模型在精算科學的領域是日漸重要，本文試著藉由隨機性的變化來估計代替以往精算上各種假設下所求得的負債。本文藉由隨機模擬的方式，得到各種資產在市場上或者是經濟上的價值來建構相關投資標的之報酬率，並利用動態隨機規劃模型去改善財務上避險以及資產負債管理。此外，為了避免模擬分析時間過長的問題，本文採用了情境抽樣的方法去改善電腦模擬分析計算時的效率。 我們主要得到以下結論： (一)確定提撥制下的負債受薪資水準波動的影響，所以此時會持有較 多的指數連結型債券以反應薪資水準及通貨膨脹的影響。整體投 資的結果與Vigna & Haberman (2001) 文中的結果及實務上生命 週期型態(lifestyle)投資方式呈現相同的現象。 (二)考慮每期下跌風險(downside risk)時，期中的投資可能會偏向 於投資風險較高的股票。在每年觀察下跌風險的情況下其投資因 為必須考慮避免每一年的下跌風險，需要比每五年觀察下跌風險 的情況做風險較大的投資，以達到其目標。 (三)在本文的調整投資組合策略下，因為調整次數不多，所以在考慮 交易成本的情況，當交易成本很小時對於整體的最適化資產配置 與最適化提撥率的影響是很小的。在本文的調整投資組合策略 下，交易成本的影響只有在交易成本非常大的情況下才能看得出 來。 (四)均勻抽樣法抽出的400組情境幾乎可以完全的代替4000組情境， 其結果可以看出與未抽樣相同的生命週期型態(lifestyle)投資 方式。而隨機抽樣法的結果雖然也可看出趨勢，但準確性相對於 均勻抽樣法仍稍嫌不足，並不適合用來代替原先的4000組情境。 | zh_TW |
| dc.description.abstract (摘要) | A shift from defined-benefit pension plan towards defined-contribution pension plan is currently popular around the world. This means that a serious investment risk transfers from defined-benefit sponsors to the individual members of defined-contribution plans. In order to reduce the risk of individual DC member, we investigate the methodology of finding the optimal contribution rate and asset allocation to reach a certain target of the retirement replacement rate in this paper. Stochastic processes are getting more important to the field of actuarial science. Instead of trying to approximate liabilities by a single deterministic set of actuarial assumption, we seek to take account of market or economic valuation for both assets and liabilities using stochastic simulation. We applied dynamic stochastic programming models to improve financial hedging and asset liability management. Moreover, in order to avoid the problem of time-consuming, we use scenario sampling method to improve the efficiency of computer calculation. We draw four conclusions from our investigations： (1)We will hold more assets in indexed-linked bonds because the pension liability is highly related to the wage- index and inflation rate. The optimal investment strategy is very like the so called "lifestyle" investment strategy. (2)When we consider downside risk, we should hold more risky equities. The investment strategy is more risky when we consider downside risk every year than every 5 years. (3)Under our rebalancing strategy, if the transaction cost is small, the influence on the investment strategy and contribution rate is small. We can see the influence of the transaction cost in a situation that the transaction cost is very big only. (4)There are almost no different between uniform sampling scenarios and original simulation scenarios, so uniform sampling scenarios may replace the original simulation scenarios perfectly. And random sampling method is unsuitable to replace the original simulation scenarios. | en_US |
| 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、投資模型與最適化目標建構……………………………………-16- 第一節 Wilkie投資模型…………………………………………………-16- 第二節 最適化目標函數………………………………………………..-19-第三章、資產模型建構……………………………………………………-24- 第一節 未考慮交易成本之資產模型……………………………………-24- 第二節 考慮交易成本之資產模型………………………………………-28-第四章、均勻抽樣法之應用………………………………………………-30-第五章、數值結果分析……………………………………………………-32- 第一節 績效評估…………………………………………………………-33- 第二節 四種目標函數下之最適資產配置與最適提撥率………………-36- 第三節 考慮交易成本下之最適資產配置與最適提撥率………………-48- 第四節 抽樣法之應用……………………………………………………-53-第六章、結論與建議………………………………………………………-55-參考文獻……………………………………………………………………-58-附錄…………………………………………………………………………-63-表目錄表 一：目標函數(一)之最適資產配置與最適提撥率…………………- 36-表 二：目標函數(一)固定提撥率(12 %)下之最適資產配置………….-37-表 三：目標函數(二)之最適資產配置與最適提撥率，………………- 37-表 四：目標函數(二)之最適資產配置與最適提撥率，………………- 38-表 五：目標函數(二)之最適資產配置與最適提撥率，………………- 38-表 六：目標函數(三)之最適資產配置與最適提撥率，每5年考慮下跌風險………- 40-表 七：目標函數(三)之最適資產配置與最適提撥率，每年考慮下跌風險…………- 41-表 八：目標函數(三)之最適資產配置與最適提撥率，每5年考慮下跌風險……- 41-表 九：目標函數(三)之最適資產配置與最適提撥率，每年考慮下跌風險………- 42-表 十：目標函數(三)之最適資產配置與最適提撥率，每5年考慮下跌風險……- 42-表 十一：目標函數(三)之最適資產配置與最適提撥率，每年考慮下跌風險……- 43-表 十二：目標函數(四)之最適資產配置與最適提撥率…………….- 44-表 十三：目標函數(四)之最適資產配置，使用目標函數(一)之提撥率…………………….- 44-表 十四：各目標函數間之績效評估………………………………….- 47-表 十五：世界各國證券交易稅徵收標準………………………………- 48-表 十六：目標函數(一)考慮交易成本下之最適資產配置…………….-49-表 十七：目標函數(一)考慮交易成本下之最適資產配置……………- 49-表 十八：目標函數(一)考慮交易成本下之最適資產配置……………- 50-表 十九：目標函數(一)考慮交易成本下之最適資產配置…………….-51-表 二十：目標函數(一)考慮交易成本下之最適資產配置…………….-51-表 二十一：目標函數(一)使用均勻抽樣法下之最適資產配置……….-53-表 二十二：目標函數(一)使用隨機抽樣法下之最適資產配置……….-54-圖目錄圖 一：Wilkie 投資模型關係……………………………………………-16-圖 二：兩種抽樣法與未抽樣之股票顯著測度機率分配圖…………….-31- | 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/#G0923580241 | en_US |
| dc.subject (關鍵詞) | 確定提撥計畫 | zh_TW |
| dc.subject (關鍵詞) | 最適投資策略 | zh_TW |
| dc.subject (關鍵詞) | 下跌風險 | zh_TW |
| dc.subject (關鍵詞) | 生命週期型態 | zh_TW |
| dc.subject (關鍵詞) | defined-contribution plans | en_US |
| dc.subject (關鍵詞) | optimal investment strategy | en_US |
| dc.subject (關鍵詞) | downside risk | en_US |
| dc.subject (關鍵詞) | lifestyle investment strategy | en_US |
| dc.title (題名) | 確定提撥制下退休基金之最適提撥率與最適資產配置 | zh_TW |
| dc.type (資料類型) | thesis | en |
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