Asset pricing with short-selling constraints and many belief types: three fast solution algorithms
Asset pricing with short-selling constraints and many belief types: three fast solution algorithms
Short-selling is common in financial markets but is also strictly regulated. When short selling is banned, heterogeneous beliefs determine which investors take long positions and which have constrained positions of zero in equilibrium. Solving such models is computationally intensive. We set out three algorithms suited to solving models with very large numbers of investor types – such as millions – quickly on a standard laptop or desktop computer. The fastest algorithm combines price iterations with a divide and conquer approach. As an application we study the impact of a short-selling ban on price dynamics and wealth distribution in a market of many investor types in evolutionary competition, and we observe that both can be affected substantially.
Hatcher, Michael
e0846252-6d46-44f8-ba3c-05cf1fba64ab
21 February 2026
Hatcher, Michael
e0846252-6d46-44f8-ba3c-05cf1fba64ab
Hatcher, Michael
(2026)
Asset pricing with short-selling constraints and many belief types: three fast solution algorithms.
Computational Economics.
(doi:10.1007/s10614-025-11301-8).
Abstract
Short-selling is common in financial markets but is also strictly regulated. When short selling is banned, heterogeneous beliefs determine which investors take long positions and which have constrained positions of zero in equilibrium. Solving such models is computationally intensive. We set out three algorithms suited to solving models with very large numbers of investor types – such as millions – quickly on a standard laptop or desktop computer. The fastest algorithm combines price iterations with a divide and conquer approach. As an application we study the impact of a short-selling ban on price dynamics and wealth distribution in a market of many investor types in evolutionary competition, and we observe that both can be affected substantially.
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s10614-025-11301-8
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Accepted/In Press date: 27 December 2025
Published date: 21 February 2026
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© The Author(s) 2026.
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Local EPrints ID: 510117
URI: http://eprints.soton.ac.uk/id/eprint/510117
ISSN: 1572-9974
PURE UUID: f8298295-d11d-4085-a595-2893bd80c67c
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Date deposited: 17 Mar 2026 18:09
Last modified: 18 Mar 2026 02:48
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