Robust Simulation for Mega-Risks

The Path from Single-Solution to Competitive, Multi-Solution Methods for Mega-Risk Management
Softcover Nachdruck of the original 1. Auflage 2015
ISBN: 978-3-319-36907-5
Verlag: Springer International Publishing

Buch, Englisch, 164 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 2934 g

This 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.

Zielgruppe

Research

Autoren/Hrsg.

Taylor, Craig E.

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Risikobewertung, Risikotheorie
• Wirtschaftswissenschaften Betriebswirtschaft Management Risikomanagement

Inhaltsverzeichnis

Introduction: 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.