An Intelligent Agent System for Multi-scenario Asset Allocation Decision Support
碩士 === 元智大學 === 資訊管理研究所 === 91 === Asset allocation is the choice of how much to invest among classes of assets to achieve the best portfolio given the investor’s objectives and investment constraints. The approach that explores the nature of risk-return trade-off and the principles of r...
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ndltd-TW-091YZU003960432015-10-13T13:39:20Z http://ndltd.ncl.edu.tw/handle/68192940461347867946 An Intelligent Agent System for Multi-scenario Asset Allocation Decision Support 多情境資產配置之智慧代理人系統架構設計 Jen Huan Chen 陳振寰 碩士 元智大學 資訊管理研究所 91 Asset allocation is the choice of how much to invest among classes of assets to achieve the best portfolio given the investor’s objectives and investment constraints. The approach that explores the nature of risk-return trade-off and the principles of rational portfolio selection associated with it was first proposed by the Markowitz Model. In practice, the number of required data inputs for applying Markowitz model with multi-scenario analysis is extremely large. In addition, the sophisticated valuation models and computations complicate the situation. We therefore proposed an intelligent agent system for multi-scenario asset allocation decision support. By way of many intelligent agents’ co-work and coordination, the large amount of data computation and various jobs of analysis can be flexibly performed. In this thesis, we defined the roles and jobs of different agents, including: financial data collection agent, scenario-defined agent, scenario probability forecasting agent, investor agent, asset evaluation agent, and asset allocation decision support agent, to simulate multi-scenario asset allocation decisions. Yi-Chuan Lu 盧以詮 2003 學位論文 ; thesis 136 zh-TW |
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碩士 === 元智大學 === 資訊管理研究所 === 91 === Asset allocation is the choice of how much to invest among classes of assets to achieve the best portfolio given the investor’s objectives and investment constraints. The approach that explores the nature of risk-return trade-off and the principles of rational portfolio selection associated with it was first proposed by the Markowitz Model. In practice, the number of required data inputs for applying Markowitz model with multi-scenario analysis is extremely large. In addition, the sophisticated valuation models and computations complicate the situation. We therefore proposed an intelligent agent system for multi-scenario asset allocation decision support. By way of many intelligent agents’ co-work and coordination, the large amount of data computation and various jobs of analysis can be flexibly performed. In this thesis, we defined the roles and jobs of different agents, including: financial data collection agent, scenario-defined agent, scenario probability forecasting agent, investor agent, asset evaluation agent, and asset allocation decision support agent, to simulate multi-scenario asset allocation decisions.
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Yi-Chuan Lu |
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Yi-Chuan Lu Jen Huan Chen 陳振寰 |
author |
Jen Huan Chen 陳振寰 |
spellingShingle |
Jen Huan Chen 陳振寰 An Intelligent Agent System for Multi-scenario Asset Allocation Decision Support |
author_sort |
Jen Huan Chen |
title |
An Intelligent Agent System for Multi-scenario Asset Allocation Decision Support |
title_short |
An Intelligent Agent System for Multi-scenario Asset Allocation Decision Support |
title_full |
An Intelligent Agent System for Multi-scenario Asset Allocation Decision Support |
title_fullStr |
An Intelligent Agent System for Multi-scenario Asset Allocation Decision Support |
title_full_unstemmed |
An Intelligent Agent System for Multi-scenario Asset Allocation Decision Support |
title_sort |
intelligent agent system for multi-scenario asset allocation decision support |
publishDate |
2003 |
url |
http://ndltd.ncl.edu.tw/handle/68192940461347867946 |
work_keys_str_mv |
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