Portfolio optimization problem under concave transaction costs and minimal transaction unit constraints

Konno, Hiroshi; Wijayanayake, A.

doi:10.1007/pl00011397

Cited by 169 publications

(83 citation statements)

References 16 publications

(15 reference statements)

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“…For example, [20] extends the work of [4] to limited diversification portfolios, and [12] solves portfolio problems with minimum transaction levels, limited diversification and round lot constraints (which requires investing in discrete units) in a branch-and-bound context. In [15], the authors solve a portfolio optimization problem that maximizes net returns where the transaction costs are modeled by a concave function. They successively estimate the concave function by a piecewise linear function and solve the resulting LP.…”

Section: Portfolio Selectionmentioning

confidence: 99%

Algorithm for cardinality-constrained quadratic optimization

2007

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This paper describes an algorithm for cardinality-constrained quadratic optimization problems, which are convex quadratic programming problems with a limit on the number of non-zeros in the optimal solution. In particular, we consider problems of subset selection in regression and portfolio selection in asset management and propose branch-and-bound based algorithms that take advantage of the special structure of these problems. We compare our tailored methods against CPLEX's quadratic mixed-integer solver and conclude that the proposed algorithms have practical advantages for the special class of problems we consider.

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Section: Portfolio Selectionmentioning

confidence: 99%

Algorithm for cardinality-constrained quadratic optimization

2007

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“…Note that (48) solves for v A given η i , J and J ′ . On the other hand, (42), (43) and (44) determine η i , J and J ′ in terms of v A . The entire system can then be solved iteratively.…”

Section: Optimization With Factor Modelmentioning

confidence: 99%

Combining alpha streams with costs

Kakushadze¹

2015

JOR

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We discuss investment allocation to multiple alpha streams traded on the same execution platform with internal crossing of trades and point out differences with allocating investment when alpha streams are traded on separate execution platforms with no crossing. First, in the latter case allocation weights are non-negative, while in the former case they can be negative. Second, the effects of both linear and nonlinear (impact) costs are different in these two cases due to turnover reduction when the trades are crossed. Third, the turnover reduction depends on the universe of traded alpha streams, so if some alpha streams have zero allocations, turnover reduction needs to be recomputed, hence an iterative procedure. We discuss an algorithm for finding allocation weights with crossing and linear costs. We also discuss a simple approximation when nonlinear costs are added, making the allocation problem tractable while still capturing nonlinear portfolio capacity bound effects. We also define "regression with costs" as a limit of optimization with costs, useful in often-occurring cases with singular alpha covariance matrix.

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“…As (Horst and Tuy, 1996;Horst and Thoai, 1999) Konno and Wijayanayake (2001), an iterative procedure can be used to compute an ε -optimal solution to that particular DC problem. The procedure is based on the construction of a convex relaxation of the original problem (by replacing each univariate concave cost function by an underestimating envelope function which is linear and univariate).…”

Section: Appendix a -Mathematical Proofsmentioning

confidence: 99%

Export diversification through resource-based industrialization: The case of natural gas

Massol

Banal‐Estañol

2014

European Journal of Operational Research

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This is the accepted version of the paper.This version of the publication may differ from the final published version. February 14, 2014 Permanent AbstractFor small resource-rich developing economies, specialization in raw exports is usually considered to be detrimental to growth and Resource-Based Industrialization (RBI) is often advocated to promote export diversification. This paper develops a new methodology to assess the performance of these RBI policies. We first formulate an adapted mean-variance portfolio model that explicitly takes into consideration: (i) a technology-based representation of the set of feasible export combinations, and (ii) the cost structure of the resource processing industries. Second, we provide a computationally tractable reformulation of the resulting mixed-integer nonlinear optimization problem.Finally, we present an application to the case of natural gas, comparing current and efficient export-oriented industrialization strategies of nine gas-rich developing countries.

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Portfolio optimization problem under concave transaction costs and minimal transaction unit constraints

Cited by 169 publications

References 16 publications

Algorithm for cardinality-constrained quadratic optimization

Algorithm for cardinality-constrained quadratic optimization

Combining alpha streams with costs

Export diversification through resource-based industrialization: The case of natural gas

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