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An algorithm for computing solutions of variational problems with global convexity constraints


Ekeland, Ivar; Moreno-Bromberg, Santiago (2010). An algorithm for computing solutions of variational problems with global convexity constraints. Numerische Mathematik, 115(1):45-69.

Abstract

We present an algorithm to approximate the solutions to variational problems where set of admissible functions consists of convex functions. The main motivation behind the numerical method is to compute solutions to Adverse Selection problems within a Principal-Agent framework. Problems such as product lines design, optimal taxation, structured derivatives design, etc. can be studied through the scope of these models. We develop a method to estimate their optimal pricing schedules.

Abstract

We present an algorithm to approximate the solutions to variational problems where set of admissible functions consists of convex functions. The main motivation behind the numerical method is to compute solutions to Adverse Selection problems within a Principal-Agent framework. Problems such as product lines design, optimal taxation, structured derivatives design, etc. can be studied through the scope of these models. We develop a method to estimate their optimal pricing schedules.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Banking and Finance
Dewey Decimal Classification:330 Economics
Scopus Subject Areas:Physical Sciences > Computational Mathematics
Physical Sciences > Applied Mathematics
Language:English
Date:2010
Deposited On:24 Nov 2020 14:50
Last Modified:27 Jan 2022 03:15
Publisher:Springer
ISSN:0029-599X
OA Status:Closed
Publisher DOI:https://doi.org/10.1007/s00211-009-0270-2
Related URLs:https://link.springer.com/content/pdf/10.1007/s00211-009-0270-2.pdf (Publisher)
Other Identification Number:merlin-id:7968

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