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Journal ArticleDOI

A Gradient Technique of Adaptive Monte Carlo

E. L. Pugh
- 01 Jul 1966 - 
- Vol. 8, Iss: 3, pp 346-355
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This article is published in Siam Review.The article was published on 1966-07-01. It has received 19 citations till now. The article focuses on the topics: Hybrid Monte Carlo & Monte Carlo method in statistical physics.

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Citations
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Journal ArticleDOI

Stochastic Optimization of Insurance Portfolios for Managing Exposure to Catastrophic Risks

TL;DR: An approach that integrates catastrophe modeling with stochastic optimization techniques to support decision making on coverages of losses, profits, stability, and survival of insurers is developed.
Journal ArticleDOI

A system approach to management of catastrophic risks

TL;DR: The paper discusses some methodological challenges concerning the design of such models and decision support systems and the role of system approaches, models and accompanying decisionSupport systems becomes of critical importance for managing catastrophic risks.
Posted Content

The Design of Optimal Insurance Decisions in the Presence of Catastrophic Risks

TL;DR: In this article, a two-stage spatial catastrophic model is extended to dynamic cases reflecting dependencies of risk accumulation processes in time, which can be used for the analysis of decisions under changing frequencies of events and values of properties.
Journal ArticleDOI

Insurability of Catastrophic Risks: The Stochastic Optimization Model

TL;DR: In this article, the authors derive the insurability of dependent catastrophic risks by calculating conditions that would aid insurers in deliberate selection of their portfolios, and discuss the connections between the probability of ruin and nonsmooth risk functions.
References
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Book

Monte Carlo methods

TL;DR: The general nature of Monte Carlo methods can be found in this paper, where a short resume of statistical terms is given, including random, pseudorandom, and quasirandom numbers.
Journal ArticleDOI

Importance sampling in monte carlo analysis

TL;DR: In this article, an elementary description of importance sampling as used in Monte Carlo analyses is given, along with an overview of the statistical sampling procedures that can be used to reduce the required computer time.
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