Approaching Collateral Optimization for NISQ and Quantum-Inspired Computing
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00381690" target="_blank" >RIV/68407700:21230/23:00381690 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/TQE.2023.3314839" target="_blank" >https://doi.org/10.1109/TQE.2023.3314839</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TQE.2023.3314839" target="_blank" >10.1109/TQE.2023.3314839</a>
Alternative languages
Result language
angličtina
Original language name
Approaching Collateral Optimization for NISQ and Quantum-Inspired Computing
Original language description
Collateral optimization refers to the systematic allocation of financial assets to satisfy obligations or secure transactions while simultaneously minimizing costs and optimizing the usage of available resources. This involves assessing the number of characteristics, such as the cost of funding and quality of the underlying assets to ascertain the optimal collateral quantity to be posted to cover exposure arising from a given transaction or a set of transactions. One of the common objectives is to minimize the cost of collateral required to mitigate the risk associated with a particular transaction or a portfolio of transactions while ensuring sufficient protection for the involved parties. Often, this results in a large-scale combinatorial optimization problem. In this study, we initially present a mixed-integer linear programming formulation for the collateral optimization problem, followed by a quadratic unconstrained binary optimization (QUBO) formulation in order to pave the way toward approaching the problem in a hybrid-quantum and noisy intermediate-scale quantum-ready way. We conduct local computational small-scale tests using various software development kits and discuss the behavior of our formulations as well as the potential for performance enhancements. We find that while the QUBO-based approaches fail to find the global optima in the small-scale experiments, they are reasonably close suggesting their potential for large instances. We further survey the recent literature that proposes alternative ways to attack combinatorial optimization problems suitable for collateral optimization.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Transactions on Quantum Engineering
ISSN
2689-1808
e-ISSN
2689-1808
Volume of the periodical
4
Issue of the periodical within the volume
October
Country of publishing house
US - UNITED STATES
Number of pages
18
Pages from-to
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UT code for WoS article
001363364800003
EID of the result in the Scopus database
2-s2.0-85171599377