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Fairness and Efficiency in Multiportfolio Optimization

Author

Listed:
  • Dan A. Iancu

    (Graduate School of Business, Stanford University, Stanford, California 94305)

  • Nikolaos Trichakis

    (Technology and Operations Management, Harvard Business School, Boston, Massachusetts 02163)

Abstract

We deal with the problem faced by a portfolio manager in charge of multiple accounts. We argue that because of market impact costs, this setting differs in several subtle ways from the classical (single account) case, with the key distinction being that the performance of each individual account typically depends on the trading strategies of other accounts, as well. We propose a novel, tractable approach for jointly optimizing the trading activities of all accounts and also splitting the associated market impact costs between the accounts. Our approach allows the manager to balance the conflicting objectives of maximizing the aggregate gains from joint optimization and distributing them across the accounts in an equitable way. We perform numerical studies that suggest that our approach outperforms existing methods employed in the industry or discussed in the literature.

Suggested Citation

  • Dan A. Iancu & Nikolaos Trichakis, 2014. "Fairness and Efficiency in Multiportfolio Optimization," Operations Research, INFORMS, vol. 62(6), pages 1285-1301, December.
  • Handle: RePEc:inm:oropre:v:62:y:2014:i:6:p:1285-1301
    DOI: 10.1287/opre.2014.1310
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. David Rea & Craig Froehle & Suzanne Masterson & Brian Stettler & Gregory Fermann & Arthur Pancioli, 2021. "Unequal but Fair: Incorporating Distributive Justice in Operational Allocation Models," Production and Operations Management, Production and Operations Management Society, vol. 30(7), pages 2304-2320, July.
    2. Chong Hyun Park & Gemma Berenguer, 2020. "Supply Constrained Location‐Distribution in Not‐for‐Profit Settings," Production and Operations Management, Production and Operations Management Society, vol. 29(11), pages 2461-2483, November.
    3. Hussein El Hajj & Douglas R. Bish & Ebru K. Bish, 2021. "Equity in genetic newborn screening," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(1), pages 44-64, February.
    4. Aziz, Haris & Huang, Xin & Mattei, Nicholas & Segal-Halevi, Erel, 2023. "Computing welfare-Maximizing fair allocations of indivisible goods," European Journal of Operational Research, Elsevier, vol. 307(2), pages 773-784.
    5. Samim Ghamami & Paul Glasserman, 2019. "Submodular Risk Allocation," Management Science, INFORMS, vol. 65(10), pages 4656-4675, October.
    6. Gur, Yonatan & Iancu, Dan & Warnes, Xavier, 2020. "Value Loss in Allocation Systems with Provider Guarantees," Research Papers 3813, Stanford University, Graduate School of Business.
    7. Gerry Tsoukalas & Jiang Wang & Kay Giesecke, 2019. "Dynamic Portfolio Execution," Management Science, INFORMS, vol. 67(5), pages 2015-2040, May.
    8. Kelli Francis-Staite, 2022. "Internal multi-portfolio rebalancing processes: Linking resource allocation models and biproportional matrix techniques to portfolio management," Papers 2201.06183, arXiv.org.
    9. Heras, Jorge & Martín, Mariano, 2020. "Social issues in the energy transition: Effect on the design of the new power system," Applied Energy, Elsevier, vol. 278(C).
    10. Yonatan Gur & Dan Iancu & Xavier Warnes, 2021. "Value Loss in Allocation Systems with Provider Guarantees," Management Science, INFORMS, vol. 67(6), pages 3757-3784, June.
    11. Lampariello, Lorenzo & Neumann, Christoph & Ricci, Jacopo M. & Sagratella, Simone & Stein, Oliver, 2021. "Equilibrium selection for multi-portfolio optimization," European Journal of Operational Research, Elsevier, vol. 295(1), pages 363-373.

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