A FAST ALGORITHM FOR SOLVING LARGE SCALE MEAN-VARIANCE MODELS BY COMPACT FACTORIZATION OF COVARIANCE MATRICES

スポンサーリンク

概要

• 論文の詳細を見る

• A fast algorithm for solving large scale MV (mean-variance) portfolio optimization problems is proposed. It is shown that by using T independent data representing the rate of return of the assets, the MV model consisting of n assets can be put into a quadratic program with n + T variables, T linear constraints and T quadratic terms in the objective function. As a result, the computation time required to solve this problem would increase very mildly as a function of n. This implies that a very large scale MV model can now be solved in a practical amount of time.

• 社団法人日本オペレーションズ・リサーチ学会の論文

著者

• Suzuki K

  Tokyo Inst. Technol. Tokyo Jpn

• Konno Hiroshi

  Tokyo Institute of Technology

• Suzuki Ken-ichi

  Tokyo Institute of Technology

関連論文

• A FAST ALGORITHM FOR SOLVING LARGE SCALE MEAN-VARIANCE MODELS BY COMPACT FACTORIZATION OF COVARIANCE MATRICES
• A PARAMETRIC SUCCESSIVE UNDERESTIMATION METHOD FOR CONVEX PROGRAMMING PROBLEMS WITH AN ADDITIONAL CONVEX MULTIPLICATIVE CONSTRAINT
• OUTER APPROXIMATION ALGORITHMS FOR LOWER RANK BILINEAR PROGRAMMING PROBLEMS
• Minimal Cost Rebalancing under Concave Transaction Costs and Minimal Transaction Unit Constraints
• MEAN-ABSOLUTE DEVIATION PORTFOLIO OPTIMIZATION MODEL UNDER TRANSACTION COSTS
• SOLVING LARGE SCALE MEAN-VARIANCE MODELS WITH DENSE NON-FACTORABLE COVARIANCE MATRICES

スポンサーリンク