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Measuring Risk in Complex Stochastic Systems

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Release : 2012-12-06
Genre : Mathematics
Kind : eBook
Book Rating : 146/5 ( reviews)

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Book Synopsis Measuring Risk in Complex Stochastic Systems by : J. Franke

Download or read book Measuring Risk in Complex Stochastic Systems written by J. Franke. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: Complex dynamic processes of life and sciences generate risks that have to be taken. The need for clear and distinctive definitions of different kinds of risks, adequate methods and parsimonious models is obvious. The identification of important risk factors and the quantification of risk stemming from an interplay between many risk factors is a prerequisite for mastering the challenges of risk perception, analysis and management successfully. The increasing complexity of stochastic systems, especially in finance, have catalysed the use of advanced statistical methods for these tasks. The methodological approach to solving risk management tasks may, however, be undertaken from many different angles. A financial insti tution may focus on the risk created by the use of options and other derivatives in global financial processing, an auditor will try to evalu ate internal risk management models in detail, a mathematician may be interested in analysing the involved nonlinearities or concentrate on extreme and rare events of a complex stochastic system, whereas a statis tician may be interested in model and variable selection, practical im plementations and parsimonious modelling. An economist may think about the possible impact of risk management tools in the framework of efficient regulation of financial markets or efficient allocation of capital.

Measuring Risk in Complex Stochastic Systems

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Author :
Release : 1999
Genre :
Kind : eBook
Book Rating : 800/5 ( reviews)

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Book Synopsis Measuring Risk in Complex Stochastic Systems by :

Download or read book Measuring Risk in Complex Stochastic Systems written by . This book was released on 1999. Available in PDF, EPUB and Kindle. Book excerpt:

Introduction to Credit Risk Modeling

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Release : 2016-04-19
Genre : Business & Economics
Kind : eBook
Book Rating : 934/5 ( reviews)

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Book Synopsis Introduction to Credit Risk Modeling by : Christian Bluhm

Download or read book Introduction to Credit Risk Modeling written by Christian Bluhm. This book was released on 2016-04-19. Available in PDF, EPUB and Kindle. Book excerpt: Contains Nearly 100 Pages of New MaterialThe recent financial crisis has shown that credit risk in particular and finance in general remain important fields for the application of mathematical concepts to real-life situations. While continuing to focus on common mathematical approaches to model credit portfolios, Introduction to Credit Risk Modelin

Multivariate Dispersion, Central Regions, and Depth

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Release : 2012-12-06
Genre : Mathematics
Kind : eBook
Book Rating : 452/5 ( reviews)

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Book Synopsis Multivariate Dispersion, Central Regions, and Depth by : Karl Mosler

Download or read book Multivariate Dispersion, Central Regions, and Depth written by Karl Mosler. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: This book has many applications to stochastic comparison problems in economics and other fields. It covers theory of lift zonoids and demonstrates its usefulness in multivariate analysis, an informal introduction to basic ideas, and a comprehensive investigation into the theory, as well as various applications of the lift zonoid approach and may be separately studied. Readers are assumed to have a firm grounding in probability at the graduate level.

Topics in Optimal Design

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Release : 2012-12-06
Genre : Mathematics
Kind : eBook
Book Rating : 495/5 ( reviews)

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Book Synopsis Topics in Optimal Design by : Erkki P. Liski

Download or read book Topics in Optimal Design written by Erkki P. Liski. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: This book covers a wide range of topics in both discrete and continuous optimal designs. The topics discussed include designs for regression models, covariates models, models with trend effects, and models with competition effects. The prerequisites are a basic course in the design and analysis of experiments and some familiarity with the concepts of optimality criteria.

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