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| 研究生： |
黃孝慈 |
|---|---|
| 論文名稱： |
應用模擬最佳化來求解產險公司之資產配置的兩篇論文 |
| 指導教授： |
陳春龍
蔡政憲 |
| 學位類別： |
博士
Doctor |
| 系所名稱： |
商學院 - 資訊管理學系 Department of Management Information System |
| 論文出版年： | 2009 |
| 畢業學年度： | 97 |
| 語文別： | 英文 |
| 論文頁數： | 70 |
| 中文關鍵詞： | 模擬最佳化 、財產保險 、資產配置 |
| 外文關鍵詞： | simulation optimization, property-casualty insurance, asset allocation |
| 相關次數： | 點閱：206 下載：0 |
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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.
Research 1 COUPLING A MULTIPHASE GENETIC ALGORITHM WITH A SIMULATION MODEL TO SEARCH
FOR THE OPTIMAL MULTIPERIOD ASSET ALLOCATIONS OF A PROPERTYCASUALTY INSURER.............
.............................................................................................................................. 5
1. NTRODUCTION ...............................................................................................5
2. THE SIMULATION MODEL ............................................................................ 8
3. THE OPTIMIZATION PROBLEM AND ALGORITHM .................................. 13
3.1 The Optimization Problem ............................................................................... 13
3.2 The Basic GA ................................................................................................. 14
3.3 MPGA ............................................................................................................ 19
4. INVESTMENT STRATEGIES AND OPTIMIZATION RESULTS ................... 22
4.1 Investment Strategies ....................................................................................... 22
4.2 Optimization Results ........................................................................................ 23
5. SUMMARIES AND CONCLUSIONS ............................................................... 28
REFERENCE ........................................................................................................ 29
Research 2 APPLYING SIMULATION OPTIMIZATION WITH MULTIPHASE EVOLUTIONARY STRATEGIES
TO THE ASSET ALLOCATION OF A PROPERTYCASUALTY INSURER ... 32
1. INTRODUCTION ............................................................................................. 32
2. STOCHASTIC INVESTMENT AND INSURANCE MARKET MODELS .......... 35
2.1 Investment Markets ........................................................................................... 35
2.2 Insurance Markets ............................................................................................. 37
3. THE DYNAMICS OF THE INSURERS OPERATIONS ................................ 37
3.1 Insurance Activities ........................................................................................... 38
3.2 Investment Activities ......................................................................................... 39
4. THE OPTIMIZATION OF THE INSURERS ASSET ALLOCATION ............ 43
4.1 objective Function ............................................................................................. 43
4.2 Investment Strategies ......................................................................................... 44
5. MULTIPHASE EVOLUTION STRATEGIES (MPES) .................................... 46
5.1 Basic Evolution Strategies .................................................................................. 46
5.2 MultiPhase Evolution Strategies ...................................................................... 49
5.3 Effectiveness and Robustness of the MultiPhase Evolution Strategies ............... 50
6. SIMULATION RESULTS ................................................................................... 54
6.1 Objective Function Analysis ................................................................................ 55
6.2 ASSETS ALLOCATIONS ACROSS RUIN PROBABILITIES .......................... 58
7. SUMMARIES AND CONCLUSION .................................................................... 61
REFERENCES ........................................................................................................ 64
Appendix 1 .............................................................................................................. 67
Appendix 2 .............................................................................................................. 69
List of Figures and Tables
Research 1 COUPLING A MULTIPHASE GENETIC ALGORITHM WITH A SIMULATION MODEL TO
SEARCH FOR THE OPTIMAL MULTIPERIOD ASSET ALLOCATIONS OF A PROPERTYCASUALTY INSURER
Figure 1: Three dimensional sketch of f1 when n = 2. .................................................. 21
Table 1: The benchmark functions used to test the performance of optimization algorithms ...... 18
Table 2: Optimization results of MPGA for the five benchmark functions ..................... 22
Table 3: Results of the three investment strategies ( 1 k =0.165, 2 k =2.50E+10, and p=1%) ..... 25
Table 4: Results of changing k1 while keeping 2.50 10 2 k = E + and p = 1% ................ 26
Table 5: Results of changing p while keeping 1 k = 0.165 and 2 k = 2.50E+10 ............... 27
Research 2 APPLYING SIMULATION OPTIMIZATION WITH MULTIPHASE EVOLUTIONARY STRATEGIES
TO THE ASSET ALLOCATION OF A PROPERTYCASUALTY INSURER
Figure 1: The simulated activities of the insurer ............................................................. 38
Figure 2: Three dimensional sketch of f3. ..................................................................... 52
Figure 3: Three dimensional sketch of f4 ...................................................................... 52
Figure 4: Three dimensional sketch of f5. ..................................................................... 53
Figure 5: Averages of the fivetime asset allocations across tolerable ruin probabilities.. 61
Table 1: Notations used in describing investment activities ............................................ 40
Table 2: High dimension benchmark functions .............................................................. 51
Table 3: Computational results of MPES for the five benchmark functions ..................... 54
Table 4: Comparisons of optimized objective value using different strategies and methods ....... 57
Table 51: Asset allocations across ruin probabilities under MPES reallocation (ruin probabilities
ranges from 0.005 to 0.03) ........................................................................................... 59
Table 52: Asset allocations across ruin probabilities under MPES Reallocation (ruin probabilities
ranges from 0.04 to 0.1) ............................................................................................... 60
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