Dantzig type optimization method with applications to portfolio selection

Seyoung Park; Eun Ryung Lee; Sungchul Lee; Geonwoo Kim

doi:10.3390/su11113216

Dantzig type optimization method with applications to portfolio selection

Seyoung Park, Eun Ryung Lee, Sungchul Lee, Geonwoo Kim

Department of Mathematics

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

This paper investigates a novel optimization problem motivated by sparse, sustainable and stable portfolio selection. The existing benchmark portfolio via the Dantzig type optimization is used to construct a sparse, sustainable and stable portfolio. Based on the formulations, this paper proposes two portfolio selection methods, west and north portfolio selection, and investigates their empirical properties. Numerical results presented for 12 datasets and various simulated data show that the west selection can reduce risk, and the north selection may outperform the benchmark as to risk-adjusted returns (based on, e.g., information ratio and Sharpe ratio).

Original language	English
Article number	3216
Journal	Sustainability (Switzerland)
Volume	11
Issue number	11
DOIs	https://doi.org/10.3390/su11113216
Publication status	Published - 2019 Jun 1

Bibliographical note

Funding Information:
Funding: Seyoung Park is supported by the National Research Foundation of Korea grant funded by the Korea government (MSIP) (No. NRF-2019R1C1C1003805). Eun Ryung Lee is supported by the National Research Foundation of Korea grant funded by the Korea government (MSIT) (No. NRF-2019R1F1A1062795). Sungchul Lee is supported by the National Research Foundation of Korea grant funded by the Korea government (No. NRF-2017R1A2B2005661). Geonwoo Kim is supported by the National Research Foundation of Korea grant funded by the Korea government (No. NRF-2017R1E1A1A03070886).

Funding Information:
Seyoung Park is supported by the National Research Foundation of Korea grant funded by the Korea government (MSIP) (No. NRF-2019R1C1C1003805). Eun Ryung Lee is supported by the National Research Foundation of Korea grant funded by the Korea government (MSIT) (No. NRF-2019R1F1A1062795). Sungchul Lee is supported by the National Research Foundation of Korea grant funded by the Korea government (No. NRF-2017R1A2B2005661). Geonwoo Kim is supported by the National Research Foundation of Korea grant funded by the Korea government (No. NRF-2017R1E1A1A03070886).

Publisher Copyright:
© 2019 by the authors.

All Science Journal Classification (ASJC) codes

Geography, Planning and Development
Renewable Energy, Sustainability and the Environment
Environmental Science (miscellaneous)
Energy Engineering and Power Technology
Management, Monitoring, Policy and Law

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3390/su11113216

Cite this

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title = "Dantzig type optimization method with applications to portfolio selection",

abstract = "This paper investigates a novel optimization problem motivated by sparse, sustainable and stable portfolio selection. The existing benchmark portfolio via the Dantzig type optimization is used to construct a sparse, sustainable and stable portfolio. Based on the formulations, this paper proposes two portfolio selection methods, west and north portfolio selection, and investigates their empirical properties. Numerical results presented for 12 datasets and various simulated data show that the west selection can reduce risk, and the north selection may outperform the benchmark as to risk-adjusted returns (based on, e.g., information ratio and Sharpe ratio).",

author = "Seyoung Park and Lee, {Eun Ryung} and Sungchul Lee and Geonwoo Kim",

note = "Funding Information: Funding: Seyoung Park is supported by the National Research Foundation of Korea grant funded by the Korea government (MSIP) (No. NRF-2019R1C1C1003805). Eun Ryung Lee is supported by the National Research Foundation of Korea grant funded by the Korea government (MSIT) (No. NRF-2019R1F1A1062795). Sungchul Lee is supported by the National Research Foundation of Korea grant funded by the Korea government (No. NRF-2017R1A2B2005661). Geonwoo Kim is supported by the National Research Foundation of Korea grant funded by the Korea government (No. NRF-2017R1E1A1A03070886). Funding Information: Seyoung Park is supported by the National Research Foundation of Korea grant funded by the Korea government (MSIP) (No. NRF-2019R1C1C1003805). Eun Ryung Lee is supported by the National Research Foundation of Korea grant funded by the Korea government (MSIT) (No. NRF-2019R1F1A1062795). Sungchul Lee is supported by the National Research Foundation of Korea grant funded by the Korea government (No. NRF-2017R1A2B2005661). Geonwoo Kim is supported by the National Research Foundation of Korea grant funded by the Korea government (No. NRF-2017R1E1A1A03070886). Publisher Copyright: {\textcopyright} 2019 by the authors.",

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N2 - This paper investigates a novel optimization problem motivated by sparse, sustainable and stable portfolio selection. The existing benchmark portfolio via the Dantzig type optimization is used to construct a sparse, sustainable and stable portfolio. Based on the formulations, this paper proposes two portfolio selection methods, west and north portfolio selection, and investigates their empirical properties. Numerical results presented for 12 datasets and various simulated data show that the west selection can reduce risk, and the north selection may outperform the benchmark as to risk-adjusted returns (based on, e.g., information ratio and Sharpe ratio).

AB - This paper investigates a novel optimization problem motivated by sparse, sustainable and stable portfolio selection. The existing benchmark portfolio via the Dantzig type optimization is used to construct a sparse, sustainable and stable portfolio. Based on the formulations, this paper proposes two portfolio selection methods, west and north portfolio selection, and investigates their empirical properties. Numerical results presented for 12 datasets and various simulated data show that the west selection can reduce risk, and the north selection may outperform the benchmark as to risk-adjusted returns (based on, e.g., information ratio and Sharpe ratio).

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Dantzig type optimization method with applications to portfolio selection

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

UN SDGs

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