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  1. 113 工学系研究科・工学部
  2. 22 電気系工学専攻
  3. 1132225 修士論文(電気系工学専攻)
  1. 0 資料タイプ別
  2. 20 学位論文
  3. 025 修士論文

Multi-Objective Portfolio Optimization and Re-balancing using Genetic Algorithms

http://hdl.handle.net/2261/51628
http://hdl.handle.net/2261/51628
b6947698-4727-4591-a0ce-0aa6080d34de
名前 / ファイル ライセンス アクション
37106528.pdf 37106528.pdf (2.2 MB)
Item type 学位論文 / Thesis or Dissertation(1)
公開日 2012-05-18
タイトル
タイトル Multi-Objective Portfolio Optimization and Re-balancing using Genetic Algorithms
言語
言語 eng
資源タイプ
資源 http://purl.org/coar/resource_type/c_46ec
タイプ thesis
その他のタイトル
その他のタイトル 遺伝的アルゴリズムを用いた多目的ポートフォリオ最適化とリバランシング
著者 Soam, Vishal

× Soam, Vishal

WEKO 8166

Soam, Vishal

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著者別名
識別子Scheme WEKO
識別子 8167
姓名 ソーム, ヴィシャル
著者所属
著者所属 東京大学大学院工学系研究科電気系工学専攻
著者所属
著者所属 Department of Electrical Engineering and Information Systems, Graduate School of Engineering, The University of Tokyo
Abstract
内容記述タイプ Abstract
内容記述 An asset is any financial instrument like shares of companies, bonds, foreign exchange assets and a lot of others. A Portfolio is collection of these assets held by companies, financial and other institutions and rich individuals. People invest in Portfolios to invest their capital and make profits out of them. In this work, we discuss in depth the problem of Portfolio Optimization through the application of Evolutionary Algorithms, Genetic Algorithms in particular. Portfolio Optimization can be considered a resource allocation problem, where the capital to be invested is the resource and it is invested in various assets held the Portfolio. It is mainly based on the Modern Portfolio Theory (MPT) proposed by Harry Markowitz in 1952. The main idea is that by diversification, holding various kinds of assets, the total risk associated with the Portfolio can be reduced (the specific risk) while maintaining the target expected return. A lot of researchers have proposed various optimizing techniques to find an optimized Portfolio for different markets. The MPT was an extremely significant work in this field. However, it has a lot of restrictions and assumptions in it. If we can reduce/remove those restrictions that do not hold in real world, the problem becomes a very complicated one. At the same time, the optimized Portfolio evolved like this is much more realistic and can be practically used. There have been a number of researches proposing various numerical techniques to solve this problem. We are going to concentrate on Genetic Algorithms in this work, which are random search meta-heuristics. Genetic Algorithms have proved time and again, to work well with these kinds of problems. In this work, we have proposed some new points, which we believe will overcome the weak points of previous researches. The point of new mutation operator that optimizes each and every weight present in the Portfolio has been proposed, in addition to the concept of Traded Volumes which is basically an indirect way of incorporating the impact of news on the financial markets. The results achieved are motivating and the approach, we believe, will be used as a reference for future related works to develop Portfolios in real world.
書誌情報 発行日 2012-03-22
日本十進分類法
主題Scheme NDC
主題 007
学位名
学位名 修士(工学)
学位
値 master
研究科・専攻
工学系研究科電気系工学専攻
学位授与年月日
学位授与年月日 2012-03-22
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