Stochastic Generalized Gradient Method with Application to Insurance Risk Management
AbstractRecently we analyzed important classes of nonsmooth and nonconvex risk control problems which can not be solved by standard optimization techniques. The aim of this article is to develop computational procedures enabling us to bypass some of the obstacles identified in this paper. We illustrate this by using insurance risk processes with insolvency (stopping time).
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by International Institute for Applied Systems Analysis in its series Working Papers with number ir97021.
Date of creation: Apr 1997
Date of revision:
Contact details of provider:
Postal: A-2361 Laxenburg
Web page: http://www.iiasa.ac.at/Publications/Catalog/PUB_ONLINE.html
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Ermoliev, Yu. & Keyzer, M. A. & Norkin, V., 2000. "Global convergence of the stochastic tatonnement process," Journal of Mathematical Economics, Elsevier, vol. 34(2), pages 173-190, October.
- G. Guerkan & A.Y. Oezge & S.M. Robinson, 1994. "Sample-Path Optimization in Simulation," Working Papers wp94070, International Institute for Applied Systems Analysis.
- T.Y. Ermolieva, 1997. "The Design of Optimal Insurance Decisions in the Presence of Catastrophic Risks," Working Papers ir97068, International Institute for Applied Systems Analysis.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Krichel).
If references are entirely missing, you can add them using this form.