A maximal predictability portfolio using absolute deviation reformulation
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Apr 3, 2008 · This paper shows that a large-scale maximal predictability portfolio (MPP) optimization problem can be solved within a practical amount of ...
In this paper, we will propose a practical method for improving the performance of a maximal predictability portfolio (MPP) model proposed by Lo and ...
This paper shows that a large-scale maximal predictability portfolio (MPP) optimization problem can be solved within a practical amount of computational ...
Apr 3, 2008 · The purpose of this paper is to show that a large scale MPP including 1,600 assets can be obtained by solving another optimization problem by ...
Apr 3, 2008 · The purpose of this paper is to show that a large scale MPP including 1,600 assets can be obtained by solving another optimization problem by ...
The purpose of this paper is to show that an algorithm recently proposed by authors can in fact solve a maximal predictability portfolio (MPP) optimization ...
The purpose of this note is to present a reformulation of the model presented by Konno and Yamazaki (1991).
Missing: predictability | Show results with:predictability
In this paper, we will consider a maximal predictability portfolio subject to transaction cost. To reduce transaction cost, we employ turnover constraint. It ...
Nov 3, 2023 · We construct the maximally predictable portfolio (MPP) of stocks using machine learning. Solving for the optimal constrained weights in the ...
The principal idea is to find a blend of investments in financial securities that achieves an optimal trade-off between financial risk and return.
Missing: predictability | Show results with:predictability