title: Information Pooling Game in Multi-Portfolio Optimization
metadata.name: dc.contributor.author
metadata.value: Fu, Jing
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2018-07-18T13:15:40Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2018-07-18T13:15:40Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2017
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Fu, J. (2017). Information pooling game in multi-portfolio optimization. Contributions to Game Theory and Management, 10(0), 27-41.
metadata.lang: en_GB
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/10450
metadata.lang: -
metadata.name: dc.description
metadata.value: Collected papers presented on the Tenth International Conference Game Theory and Management / Editors Leon A. Petrosyan, Nikolay A. Zenkevich. – SPb.: Saint Petersburg State University, 2017. – 404 p.
metadata.lang: en_GB
metadata.name: dc.description.abstract
metadata.value: In this paper, an information pooling game is proposed and studied for multi-portfolio optimization. Our approach differs from the classical multi-portfolio optimization in several aspects, with a key distinction of allowing the clients to decide whether and to what extent their private trading information is shared with others, which directly affects the market impact cost split ratio. We introduce a built-in factor related to the clients’ vertical fairness regarding the outcomes, which is termed as “dissatisfaction indicator”.
  With balanced horizontal dissatisfactions across all accounts, the main formulation guarantees that no client is systematically advantaged or disadvantaged by the information pooling process. This is a novel mechanism to
  incorporate both the horizontal and vertical fairness in the optimization process. We show that information pooling solution outperforms the pro-rata collusive solution from fairness aspect, and the Cournot-Nash equilibrium solution for its Pareto optimality. Moreover, the empirical results suggest that within our framework, information pooling has non-negative impact on all participants’ perceived fairness, although it may hurt some account’s realized benefit compared to null information pool.
metadata.lang: en_GB
metadata.name: dc.description.sponsorship
metadata.value: This work was supported by start-up grants of Fukuoka Institute of Technology.
metadata.lang: -
metadata.name: dc.language.iso
metadata.value: en
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: Saint Petersburg State University
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: information pooling
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: multi-portfolio optimization
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: horizontal fairness
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: vertical fairness
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Information Pooling Game in Multi-Portfolio Optimization
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Other
metadata.lang: en_GB