Interior point algorithms for large-scale optimization problems and their applications to portfolio selections

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タイトル: Interior point algorithms for large-scale optimization problems and their applications to portfolio selections

博士論文

資料形態 : テキストデータプレーンテキスト

コレクション : 国立国会図書館デジタルコレクション > デジタル化資料 > 博士論文

Contents
1 Introduction
I Interior Point Algorithms for Large-Scale Portfolio Optimization
2 The Stationary Ball Method for Linear Programming:A Primal Simplex Method with a New Column Selection Rule
3 An Interior Point Algorithm for Linear Complementarity Problem
4 An Interior Point Algorithm for a Separable Convex Programming Problem
II Applications of the Interior Point Methods in Portfolio Selections
5 An Interior Point Algorithm for Large-Scale Portfolio Optimization
6 A Penalty Function Approach to Portfolio Selections
III Empirical Studies on the Portfolio Selection Problems
7 An Empirical Study on the Mean-Variance Portfolio Selection Model:Risk Management and Mean-Reversion in Japanese Stock Prices
8 International Diversification When Small Firm Stocks Are Treated as Separate Investment Assets:An Application of the Multi-Period Model