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Robust Simulation for Mega-Risks : The Path from Single-Solution to Competitive, Multi-Solution Methods for Mega-Risk Management by Craig Taylor (2015, Hardcover)

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About this product

Product Identifiers

PublisherSpringer International Publishing A&G

ISBN-103319194127

ISBN-139783319194127

eBay Product ID (ePID)211844810

Product Key Features

Number of PagesXxi, 164 Pages

Publication NameRobust Simulation for Mega-Risks : The Path from Single-Solution to Competitive, Multi-Solution Methods for Mega-Risk Management

LanguageEnglish

Publication Year2015

SubjectNatural Disasters, Methodology, Decision-Making & Problem Solving, Computer Simulation, System Theory

TypeTextbook

AuthorCraig Taylor

Subject AreaNature, Computers, Social Science, Science, Business & Economics

FormatHardcover

Dimensions

Item Weight156.1 Oz

Item Length9.3 in

Item Width6.1 in

Additional Product Features

Intended AudienceScholarly & Professional

Dewey Edition23

Number of Volumes1 vol.

IllustratedYes

Dewey Decimal658.155

Table Of ContentIntroduction: Initial Queries Going Forward.- The Deductivist Theory of Probability and Statistics.- The Frequency Theory of Probability.- Probability and Randomness as Beliefs: Bayesian Theory.- More Challenges to Tradition: Extreme Value Diagnostics, Power Laws, and the Wobble.- Mathematization of Statistics: Flexibility and Convergence.- Robust Simulation and Non-linear Reasoning: Quantitative and Qualitative Examples.- Managing Expectations: Qualitative Considerations And Quantitative Decision Procedures.- Conclusions and Queries.

SynopsisThis book introduces a new way of analyzing, measuring and thinking about mega-risks, a "paradigm shift" that moves from single-solutions to multiple competitive solutions and strategies. "Robust simulation" is a statistical approach that demonstrates future risk through simulation of a suite of possible answers. To arrive at this point, the book systematically walks through the historical statistical methods for evaluating risks. The first chapters deal with three theories of probability and statistics that have been dominant in the 20th century, along with key mathematical issues and dilemmas. The book then introduces "robust simulation" which solves the problem of measuring the stability of simulated losses, incorporates outliers, and simulates future risk through a suite of possible answers and stochastic modeling of unknown variables. This book discusses various analytical methods for utilizing divergent solutions in making pragmatic financial and risk-mitigation decisions. The book emphasizes the importance of flexibility and attempts to demonstrate that alternative credible approaches are helpful and required in understanding a great many phenomena.

LC Classification NumberGB5000-5030