Cutting plane algorithms for mean-CVaR portfolio optimization with nonconvex transaction costs

Takano, Yasunari; Nanjo, Keisuke; Sukegawa, Noriyoshi; Mizuno, Shinji

doi:10.1007/s10287-014-0209-7

Cited by 11 publications

(11 citation statements)

References 26 publications

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“…We derive some theoretical results in Section II under the proposed Wasserstein ambiguity set. Moreover, to obtain the optimal portfolio strategy, models (11) and (12) are solved in this subsection.…”

Section: A Data and Methodologymentioning

confidence: 99%

“…Without loss of generality, we set the parameter ∆ j = 1, j = 1, ..., m in model (12). Note that the constraints on the box and budget uncertainty set are both linear.…”

Section: Comparisons Between Box and Budget Uncertainty Setmentioning

confidence: 99%

“…11 is plotted. It shows the optimal objective values of model (11) and (12) at different risk levels with ∆ j = 1, j = 1, ..., 20. It reveals that the objective value increases with the escalation of risk level.…”

Section: Comparisons Between Box and Budget Uncertainty Setmentioning

confidence: 99%

“…Ben-Tal et al [11] illustrated that the CVaR approximation of the probability constraint is the best among the approximations yielded by our generating-function-based approximation scheme. CVaR is currently a popular risk measure suggested by theoreticians and market practitioners [12]- [13].…”

Section: Introductionmentioning

confidence: 99%

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A New Data-Driven Distributionally Robust Portfolio Optimization Method Based on Wasserstein Ambiguity Set

Liu

2021

IEEE Access

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Section: A Data and Methodologymentioning

confidence: 99%

“…Without loss of generality, we set the parameter ∆ j = 1, j = 1, ..., m in model (12). Note that the constraints on the box and budget uncertainty set are both linear.…”

Section: Comparisons Between Box and Budget Uncertainty Setmentioning

confidence: 99%

Section: Comparisons Between Box and Budget Uncertainty Setmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A New Data-Driven Distributionally Robust Portfolio Optimization Method Based on Wasserstein Ambiguity Set

Liu

2021

IEEE Access

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“…Figure 1 shows only an illustrative example of a piecewise linear function based on Takano et al (2015). The procedure for a piecewise linear approximation is described as follows:…”

Section: Piecewise Linear Approximationmentioning

confidence: 99%

Multi-period resource allocation for estimating project costs in competitive bidding

Takano

Ishii

Muraki

2016

Cent Eur J Oper Res

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In competitive bidding for project contracts, contractors estimate the cost of completing a project and then determine the bid price. Accordingly, the bid price is markedly affected by the inaccuracies in the estimated cost. To establish a profitmaking strategy in competitive bidding, it is crucial for contractors to estimate project costs accurately. Although allocating a large amount of resources to cost estimates allows contractors to prepare more accurate estimates, there is usually a limit to available resources in practice. To the best of our knowledge, however, none of the existing studies have addressed the resource allocation problem for estimating project costs in competitive bidding. To maximize a contractor's expected profit, this paper develops a multi-period resource allocation method for estimating project costs in a sequential competitive bidding situation. Our resource allocation model is posed as a mixed integer linear programming problem by making piecewise linear approximations of the expected profit functions. Numerical experiments examine the characteristics of the optimal resource allocation and demonstrate the effectiveness of our resource allocation method. B Yuichi Takano

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A Decomposition-Based Hybrid Estimation of Distribution Algorithm for Practical Mean-CVaR Portfolio Optimization

Wang

Chen

2019

Intelligent Computing Theories and Application

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Cutting plane algorithms for mean-CVaR portfolio optimization with nonconvex transaction costs

Cited by 11 publications

References 26 publications

A New Data-Driven Distributionally Robust Portfolio Optimization Method Based on Wasserstein Ambiguity Set

A New Data-Driven Distributionally Robust Portfolio Optimization Method Based on Wasserstein Ambiguity Set

Multi-period resource allocation for estimating project costs in competitive bidding

A Decomposition-Based Hybrid Estimation of Distribution Algorithm for Practical Mean-CVaR Portfolio Optimization

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