doi:10.1016/j.ejor.2003.06.022
Copyright © 2003 Elsevier B.V. All rights reserved.
Models for bundle trading in financial markets
Jawad Abrache
,
, a, b, Teodor Gabriel Crainic
, b, c, d and Michel Gendreau
, a, b, d
a Département d'informatique et recherche opérationnelle, Université de Montréal, C.P. 6128, Succursale Centre-ville, Montreal, Canada H3C 3J7
b Centre de recherche sur les transports, Université de Montréal, C.P. 6128, Succursale Centre-ville, Montreal, Canada H3C 3J7
c Département management et technologie, Université du Québec à Montréal, Succursale Centre-ville, Montreal, Canada H3C 4R2
d CIRANO, 2020, Rue University, Montreal, Canada H3A 2A5
Received 1 September 2002;
accepted 1 June 2003.
Available online 20 October 2003.
References and further reading may be available for this article. To view references and further reading you must
purchase this article.
Abstract
Bundle trading is a new trend in financial markets that allows traders to submit consolidated orders to sell and buy packages of assets. We propose a new bundle-based market-clearing formulation for portfolio balancing that extends the previous models in the literature through a more detailed representation of portfolios and the formulation of new bidding requirements. We also present post-optimality tie-breaking procedures intended to discriminate between equivalent orders on the basis of submission times. Numerical results evaluate the “bundle” effect as well as the bidding flexibility and the computational complexity of the formulation.
Author Keywords: Auction design; Financial markets; Bundle trading; Discrimination procedures
Fig. 1. A model for bundle price formation.
Fig. 2. DATASET-1: Market surplus.
Fig. 3. DATASET-1: Cumulative value aggregation.
Fig. 4. Integrality gaps and CPU times for DATASET-2 test problems.
Fig. 5. Economic gaps for DATASET-3 test problems.
Fig. 6. Integrality gaps and CPU times for DATASET-3 problems.
Table 1. Example of portfolio bundle trading

Table 2. DATASET-l––basic bundle trading allocation problems

Table 3. DATASET-2––lower bound allocation problems

Table 4. DATASET-3––XOR allocation problems
