Robust Simulation for Mega-Risks

Name: Robust Simulation for Mega-Risks
Brand: Springer International Publishing AG
SKU: 9783319369075
Price: 212.46 PLN
Availability: InStock

The Path from Single-Solution to Competitive, Multi-Solution Methods for Mega-Risk Management

Autor: Craig E. Taylor

Język:

Oprawa: Miękka

Wydawca: Springer International Publishing AG

Dostępność: Dostępna u dostawcy

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This book introduces a new way of analyzing, measuring and thinking about mega-risks, a "paradigm sh...

Informacje o książce

Autor

Craig E. Taylor

Język

Angielski

Oprawa

Książka - Miękka

Data wydania

2016

strony

164

EAN

9783319369075

ISBN

3319369075

Enbook ID

18051348

Wydawca

Springer International Publishing AG

Waga

2934

Wymiary

155 x 235 x 11

Pełny opis

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.

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Robust Simulation for Mega-Risks

The Path from Single-Solution to Competitive, Multi-Solution Methods for Mega-Risk Management

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