Measuring Risk in Complex Stochastic Systems
(Sprache: Englisch)
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...
Leider schon ausverkauft
versandkostenfrei
Bisher 109.99 €*
Buch (Kartoniert) -50%
54.99 €
*Preisbindung aufgehoben
- Lastschrift, Kreditkarte, Paypal, Rechnung
- Kostenlose Rücksendung
- Ratenzahlung möglich
Produktdetails
Produktinformationen zu „Measuring Risk in Complex Stochastic Systems “
Klappentext zu „Measuring Risk in Complex Stochastic Systems “
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.
Inhaltsverzeichnis zu „Measuring Risk in Complex Stochastic Systems “
- Integrated Risk Management and Extreme Value Theory- Coherent Allocation Capital for Credit Portfolios
- A Simple Approach to Country Risk
- The Structure of Credit Risk
- Extreme Value Theory and Risk Management: Basic Results
- Sensitivity of Values at Risk
- Extremes of ARCH Models
- Risk Exposure and its Sensitivity to Model Misspecification
- Neural Networks and Applications in Finance
- Nonlinear Approximation and Statistical Applications I
- Semiparametric Lower Bounds for Tail Index Estimation
- Bandwith Choice for M-estimators in Projection Pursuit and Single Index Regression
- Semiparametric Indirect Inference
- Change-point Problem in ARCH Models
- Change in Polynomial Regression and Related Processes
Autoren-Porträt
Wolfgang Härdle is a professor of statistics at the Humboldt-Universität zu Berlin and director of C.A.S.E. the Centre for Applied Statistics and Economics. He teaches quantitative finance and semiparametric statistical methods. His research focuses on dynamic factor models, multivariate statistics in finance and computational statistics. He is an elected ISI member and advisor to the Guanghua School of Management, Peking University and to National Central University, Taiwan.
Bibliographische Angaben
- 2000, Softcover reprint of the original 1st ed. 2000, XIV, 260 Seiten, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Herausgegeben: J. Franke, Wolfgang Härdle, Gerhard Stahl
- Verlag: Springer, Berlin
- ISBN-10: 038798996X
- ISBN-13: 9780387989969
- Erscheinungsdatum: 15.06.2000
Sprache:
Englisch
Kommentar zu "Measuring Risk in Complex Stochastic Systems"
Schreiben Sie einen Kommentar zu "Measuring Risk in Complex Stochastic Systems".
Kommentar verfassen