Penalty ADM Algorithm for Cardinality Constrained Mean-Absolute Deviation Portfolio Optimization

  • Temadher A. Almaadeed Department of Mathematics, Statistics and Physics, College of Arts and Sciences, Qatar University, Doha, Qatar
  • Tahereh Khodamoradi Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran
  • Maziar Salahi Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran
  • Abdelouahed Hamdi Department of Mathematics, Statistics and Physics, College of Arts and Sciences, Qatar University, Doha, Qatar
DOI: https://doi.org/10.19139/soic-2310-5070-1312
Keywords: MAD model; Cardinality constrained; PADM method

Abstract

In this paper, we study the cardinality constrained mean-absolute deviation portfolio optimization problem with risk-neutral interest rate and short-selling. We enhance the model by adding extra constraints to avoid investing in those stocks without short-selling positions. Also, we further enhance the model by determining the short rebate based on the return. The penalty alternating direction method is used to solve the mixed integer linear model. Finally, numerical experiments are provided to compare all models in terms of Sharpe ratios and CPU times using the data set of the NASDAQ and S&P indexes.

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Published
2022-02-03
How to Cite
AlMaadeed, T., Khodamoradi, T., Salahi, M., & Hamdi, A. (2022). Penalty ADM Algorithm for Cardinality Constrained Mean-Absolute Deviation Portfolio Optimization. Statistics, Optimization & Information Computing, 10(3), 775-788. https://doi.org/10.19139/soic-2310-5070-1312
Issue
Vol 10 No 3 (2022)
Section
Research Articles
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