A bi-level programming approach for global investment strategies with financial intermediation

Abstract : Most mathematical programming models for investment selection and portfolio management rely on centralized decisions about both budget allocation in different (real and financial) investment options and portfolio composition within the different options. However, in more realistic market scenarios investors do not directly select the portfolio composition, but only provide guidelines and requirements for the investment procedure. Financial intermediaries are then responsible for the detailed portfolio management, resulting in a hierarchical investor-intermediary decision setting. In this work, a bi-level mixed-integer quadratic optimization problem is proposed for the decentralized selection of a portfolio of financial securities and real investments. Single-level reformulation techniques are presented, along with valid-inequalities which allow speeding-up their resolution procedure, when large-scale instances are taken into account. We conducted computational experiments on large historical stock market data from the Center for Research in Security Prices to validate and compare the proposed bi-level investment framework (and the resulting single-level reformulations), under different levels of investor’s and intermediary’s risk aversion and control. The empirical tests reveled the impact of decentralization on the investment performance, and provide a comparative analysis of the computational effort corresponding to the proposed solution approaches.
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https://hal.archives-ouvertes.fr/hal-02117530
Contributor : Isabelle Celet <>
Submitted on : Thursday, May 2, 2019 - 2:00:36 PM
Last modification on : Friday, July 26, 2019 - 11:58:03 AM

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Francisco Benita, Francisco López-Ramos, Stefano Nasini. A bi-level programming approach for global investment strategies with financial intermediation. European Journal of Operational Research, Elsevier, 2019, 274 (1), pp.375-390. ⟨10.1016/j.ejor.2018.10.009⟩. ⟨hal-02117530⟩

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