Bhattacherjee, Sanjay, Sarkar, Palash (2024) On Using Proportional Representation Methods as Alternatives to Pro-Rata Based Order Matching Algorithms in Stock Exchanges. Computational Economics, 65 . pp. 1-20. ISSN 0927-7099. (doi:10.1007/s10614-024-10576-7) (KAR id:109920)
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Official URL: https://doi.org/10.1007/s10614-024-10576-7 |
Abstract
The first observation of the paper is that methods for determining proportional representation in electoral systems may be suitable as alternatives to the pro-rata order matching algorithm used in stock exchanges. The main part of our work is to comprehensively consider various well known proportional representation methods and analyse in details their suitability for replacing the pro-rata algorithm. Our analysis consists of a theoretical study as well as simulation studies based on data sampled from a distribution which has been suggested in the literature as models of limit orders. Based on our analysis, we put forward the suggestion that the well known Hamilton's method is a superior alternative to the pro-rata algorithm for order matching applications.
Item Type: | Article |
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DOI/Identification number: | 10.1007/s10614-024-10576-7 |
Uncontrolled keywords: | order matching algorithm, pro-rata algorithm, proportional representation, Hamilton's method, Jefferson/D'Hondt method, Webster/Saint-Lague method |
Subjects: |
H Social Sciences > HB Economic Theory H Social Sciences > HG Finance |
Institutional Unit: |
Schools > School of Computing Institutes > Institute of Cyber Security for Society |
Former Institutional Unit: |
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing University-wide institutes > Institute of Cyber Security for Society
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Funders: | University of Kent (https://ror.org/00xkeyj56) |
Depositing User: | Sanjay Bhattacherjee |
Date Deposited: | 17 May 2025 07:42 UTC |
Last Modified: | 20 May 2025 10:29 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/109920 (The current URI for this page, for reference purposes) |
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