The Experts below are selected from a list of 23697 Experts worldwide ranked by ideXlab platform
Gennady Samorodnitsky - One of the best experts on this subject based on the ideXlab platform.
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extreme Value Theory as a risk management tool
The North American Actuarial Journal, 1999Co-Authors: Paul Embrechts, Sidney I Resnick, Gennady SamorodnitskyAbstract:The financial industry, including banking and insurance, is undergoing major changes. The (re)insurance industry is increasingly exposed to catastrophic losses for which the requested cover is only just available. An increasing complexity of financial instruments calls for sophisticated risk management tools. The securitization of risk and alternative risk transfer highlight the convergence of finance and insurance at the product level. Extreme Value Theory plays an important methodological role within risk management for insurance, reinsurance, and finance.
Raymond P. Perry - One of the best experts on this subject based on the ideXlab platform.
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The Control-Value Theory of Achievement Emotions. An Integrative Approach to Emotions in Education.
Emotion in Education, 2007Co-Authors: Raymond P. Perry, Anne C. Frenzel, Thomas Goetz, Reinhard PekrunAbstract:This chapter presents an overview of the assumptions and corollaries of the control-Value Theory of achievement emotions, as well as some of its implications for educational practice. The control-Value Theory provides a theoretical framework making it possible to integrate constructs and assumptions from a variety of theoretical approaches to emotions in education and to achievement emotions more generally. Empirically, many facets of the Theory have consistently been corroborated in qualitative and quantitative investigations. However, the assumptions provided by the Theory on how to design emotionally sound learning environments for students, and occupational environments for teachers, have yet to be tested in empirical intervention studies. There is evidence that educational interventions can reduce students' test anxiety. The control-Value Theory implies that shaping educational environments in adequate ways can help to change achievement emotions other than anxiety as well. Future research should systematically explore measures to help both students and teachers to develop adaptive achievement emotions, prevent maladaptive emotions, and use their emotions in productive and healthy ways. © 2007 Copyright © 2007 Elsevier Inc. All rights reserved.
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the control Value Theory of achievement emotions an integrative approach to emotions in education
Emotion in Education, 2007Co-Authors: Reinhard Pekrun, Thomas Goetz, Anne C. Frenzel, Raymond P. PerryAbstract:Publisher Summary This chapter presents an overview of the assumptions and corollaries of the control-Value Theory of achievement emotions, as well as some of its implications for educational practice. The control-Value Theory provides a theoretical framework making it possible to integrate constructs and assumptions from a variety of theoretical approaches to emotions in education and to achievement emotions more generally. Empirically, many facets of the Theory have consistently been corroborated in qualitative and quantitative investigations. However, the assumptions provided by the Theory on how to design emotionally sound learning environments for students, and occupational environments for teachers, have yet to be tested in empirical intervention studies. There is evidence that educational interventions can reduce students' test anxiety. The control-Value Theory implies that shaping educational environments in adequate ways can help to change achievement emotions other than anxiety as well. Future research should systematically explore measures to help both students and teachers to develop adaptive achievement emotions, prevent maladaptive emotions, and use their emotions in productive and healthy ways.
Paul Embrechts - One of the best experts on this subject based on the ideXlab platform.
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extreme Value Theory as a risk management tool
The North American Actuarial Journal, 1999Co-Authors: Paul Embrechts, Sidney I Resnick, Gennady SamorodnitskyAbstract:The financial industry, including banking and insurance, is undergoing major changes. The (re)insurance industry is increasingly exposed to catastrophic losses for which the requested cover is only just available. An increasing complexity of financial instruments calls for sophisticated risk management tools. The securitization of risk and alternative risk transfer highlight the convergence of finance and insurance at the product level. Extreme Value Theory plays an important methodological role within risk management for insurance, reinsurance, and finance.
Evis Kellezi - One of the best experts on this subject based on the ideXlab platform.
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An Application of Extreme Value Theory for Measuring Risk
2020Co-Authors: Manfred Gilli, Evis KelleziAbstract:Many Þelds of modern science and engineering have to deal with events which are rare but have signiÞcant consequences. Extreme Value Theory is considered to provide the basis for the statistical modelling of such extremes. The potential of extreme Value Theory applied to Þnancial problems has only been recognized recently. This paper aims at introducing the fundamentals of extreme Value Theory as well as practical aspects for estimating and assessing statistical models for tail-related risk measures.
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an application of extreme Value Theory for measuring financial risk
Computing in Economics and Finance, 2006Co-Authors: Manfred Gilli, Evis KelleziAbstract:Assessing the probability of rare and extreme events is an important issue in the risk management of financial portfolios. Extreme Value Theory provides the solid fundamentals needed for the statistical modelling of such events and the computation of extreme risk measures. The focus of the paper is on the use of extreme Value Theory to compute tail risk measures and the related confidence intervals, applying it to several major stock market indices.
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extreme Value Theory for tail related risk measures
FAME Research Paper Series, 2000Co-Authors: Evis Kellezi, Manfred GilliAbstract:Many fields of modern science and engineering have to deal with events which are rare but have significant consequences. Extreme Value Theory is considered to provide the basis for the statistical modeling of such extremes. The potential of extreme Value Theory applied to financial problems has only been recognized recently. This paper aims at introducing the fundamentals of extreme Value Theory as well as practical aspects for estimating and assessing statistical models for tail-related risk measures.
Claudia Klüppelberg - One of the best experts on this subject based on the ideXlab platform.
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Risk management with extreme Value Theory.
2020Co-Authors: Claudia KlüppelbergAbstract:In this paper we review certain aspects around the Value-at-Risk, which is nowadays the industry benchmark risk measure. As a small quantile (usually 1%) Value-at-Risk is closely related to extreme Value Theory. We explain an estimation method based on extreme Value Theory. Since the variance of the estimated Value-at-Risk may depend on the dependence structure of the data, we investigate the extreme behaviour of some of the most prominent time series models in finance, continuous as well as discrete time models. We also determine optimal portfolios, when risk is measured by the Value-at-Risk. Again we use realistic models, moving away from the traditional Black-Scholes model to the class of Levy processes. This paper is the contribution to a book by several authors on Extreme Value Theory, which will appear by CRC/Chapman and Hall.
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Extreme Value Theory in Finance
Wiley StatsRef: Statistics Reference Online, 2014Co-Authors: Erik Brodin, Claudia KlüppelbergAbstract:Extreme Value Theory is a practical and useful tool for modeling and quantifying risk. In this article, after introducing basic concepts, we indicate how to apply it within a financial framework. Keywords: extreme Value Theory; financial risk management; generalized pareto distribution; high quantile; multivariate extreme Value Theory; peaks over threshold; time series analysis; Value at risk