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Mapping Financial Stability: Computational Risk Management

Autor Peter Sarlin
en Limba Engleză Hardback – 22 mai 2014
This book approaches macroprudential oversight from the viewpoint of three tasks. The focus concerns a tight integration of means for risk communication into analytical tools for risk identification and risk assessment. Generally, this book explores approaches for representing complex data concerning financial entities on low-dimensional displays. Data and dimension reduction methods, and their combinations, hold promise for representing multivariate data structures in easily understandable formats.  Accordingly, this book creates a Self-Organizing Financial Stability Map (SOFSM), and lays out a general framework for mapping the state of financial stability. Beyond external risk communication, the aim of the visual means is to support disciplined and structured judgmental analysis based upon policymakers' experience and domain intelligence.
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Specificații

ISBN-13: 9783642549557
ISBN-10: 3642549551
Pagini: 252
Ilustrații: XVI, 233 p. 61 illus., 38 illus. in color.
Dimensiuni: 160 x 241 x 20 mm
Greutate: 0.55 kg
Ediția:2014
Editura: Springer
Colecția Computational Risk Management
Seria Computational Risk Management

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

Introduction.- Macroprudential Oversight.- Macroprudential Data.- Data and Dimension Reduction.- Data-Dimension Reductions: A Comparison.- Extending the SOM.- Self-Organizing Financial Stability Map (SOFSM).- Exploiting the SOFSM.- Decomposing Financial Crises with SOTMs.- Conclusions, Limitations and the Future.

Textul de pe ultima copertă

This book approaches macroprudential oversight from the viewpoint of three tasks.  The focus concerns a tight integration of means for risk communication into analytical tools for risk identification and risk assessment. Generally, this book explores approaches for representing complex data concerning financial entities on low-dimensional displays. Data and dimension reduction methods, and their combinations, hold promise for representing multivariate data structures in easily understandable formats.  Accordingly, this book creates a Self-Organizing Financial Stability Map (SOFSM), and lays out a general framework for mapping the state of financial stability. Beyond external risk communication, the aim of the visual means is to support disciplined and structured judgmental analysis based upon policymakers' experience and domain intelligence.