Multi-portfolio Optimization: A Potential Game Approach

Yang Yang; Francisco Rubio; Gesualdo Scutari; Daniel Palomar

Game Theory for Networks. 2nd International ICST Conference, GAMENETS 2011, Shanghai, China, April 16-18, 2011, Revised Selected Papers

Research Article

Multi-portfolio Optimization: A Potential Game Approach

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@INPROCEEDINGS{10.1007/978-3-642-30373-9_13,
    author={Yang Yang and Francisco Rubio and Gesualdo Scutari and Daniel Palomar},
    title={Multi-portfolio Optimization: A Potential Game Approach},
    proceedings={Game Theory for Networks. 2nd International ICST Conference, GAMENETS 2011, Shanghai, China, April 16-18, 2011, Revised Selected Papers},
    proceedings_a={GAMENETS},
    year={2012},
    month={10},
    keywords={},
    doi={10.1007/978-3-642-30373-9_13}
}

Yang Yang
Francisco Rubio
Gesualdo Scutari
Daniel Palomar
Year: 2012
Multi-portfolio Optimization: A Potential Game Approach
GAMENETS
Springer
DOI: 10.1007/978-3-642-30373-9_13

Yang Yang¹^,*, Francisco Rubio¹^,*, Gesualdo Scutari²^,*, Daniel Palomar¹^,*

1: The Hong Kong University of Science and Technology
2: State University of New York (SUNY)

*Contact email: yangyang@ust.hk, eerubio@ust.hk, gesualdo@buffalo.edu, palomar@ust.hk

Abstract

Trades from separately managed accounts are usually pooled together for execution and the transaction cost for a given account may depend on the overall level of trading. Multi-portfolio optimization is a technique for combing multiple accounts at the same time, considering their joint effects while adhering to account-specific constraints. In this paper, we model multi-portfolio optimization as a game problem and adopt as a desirable objective the concept of Nash Equilibrium (NE). By formulating the game problem as a potential game, we are able to provide a complete characterization of NE and derive iterative algorithms with a distributed nature and satisfactory convergence property.

Published: 2012-10-08

: http://dx.doi.org/10.1007/978-3-642-30373-9_13

Multi-portfolio Optimization: A Potential Game Approach

Abstract

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