The Handbooks in Finance are intended to be a definitive source for comprehensive and accessible information in the field of finance. Each individual volume in the series should present an accurate self-contained survey of a sub-field of finance,...
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The Handbooks in Finance are intended to be a definitive source for comprehensive and accessible information in the field of finance. Each individual volume in the series should present an accurate self-contained survey of a sub-field of finance, suitable for use by finance and economics professors and lecturers, professional researchers, graduate students and as a teaching supplement. The goal is to have a broad group of outstanding volumes in various areas of finance. The Handbook of Heavy Tailed Distributions in Finance is the first handbook to be published in this series. This volume presents current research focusing on heavy tailed distributions in finance. The contributions cover methodological issues, i.e., probabilistic, statistical and econometric modeling under non- Gaussian assumptions, as well as the applications of the stable and other non -Gaussian models in finance and risk management
Electronic reproduction; Available via World Wide Web
Brendan O. Bradley and Murad S. Taqqu: Heavy tails in finance for independent or multifractal price incrementsBenoit B. MandelbrotFinancial risk and heavy tails
John P. Nolan: Modeling financial data with stable distributions
Tomasz J. Kozubowski, Anna K. Panorska and Svetlozar T. Rachev: Statistical issues in modeling multivariate stable portfolios
Wolfgang J. Runggaldier: Jump-diffusion models
Bo Martin Bibby and Michael Sørensen: Hyperbolic processes in finance
Svetlozar T. Rachev, Eduardo S. Schwartz and Irina Khindanova: Stable modeling of market and credit value at risk
Paul Embrechts, Filip Lindskog and Alexander McNeil: Mo delling dependence with copulas and applications to risk management
Stefan Mittnik and Marc S. Paolella: Prediction of financial downside-risk with heavy-tailed conditional distributions
Bernhard Martin, Svetlozar T. Rachev and Eduardo S. Schwartz: Stable non-Gaussian models for credit risk management
Alexander Levin and Alexander TchernitseMo dellingodelling the term structure of monetary rates: Multifactor stochastic variance models in risk management : maximum entropy approach and Lévy processes
Yesim Tokat, Svetlozar T. Rachev and Eduardo S. Schwartz: Asset liability management : a review and some new results in the presence of heavy tails
Sergio Ortobelli ... [et al.]: Portfolio choice theory with non-Gaussian distributed returns
Mark M. Meerschaert and Hans-Peter Scheffler: Portfolio modeling with heavy tailed random vectors
Borjana Racheva-Iotova and Gennaday Samorodnitsky.: Long range dependence in heavy tailed stochastic processes
Handbook of heavy tailed distributions in finance
Erschienen:
2010
Verlag:
Elsevier, Amsterdam
Heavy tails in finance for independent or multifractal price increments Benoit B. Mandelbrot -- Financial risk and heavy tails Brendan O. Bradley and Murad S. Taqqu -- Modeling financial data with stable distributions John P. Nolan -- Statistical...
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Heavy tails in finance for independent or multifractal price increments Benoit B. Mandelbrot -- Financial risk and heavy tails Brendan O. Bradley and Murad S. Taqqu -- Modeling financial data with stable distributions John P. Nolan -- Statistical issues in modeling multivariate stable portfolios Tomasz J. Kozubowski, Anna K. Panorska and Svetlozar T. Rachev -- Jump-diffusion models Wolfgang J. Runggaldier -- Hyperbolic processes in finance Bo Martin Bibby and Michael Sørensen -- Stable modeling of market and credit value at risk Svetlozar T. Rachev, Eduardo S. Schwartz and Irina Khindanova -- Mo delling dependence with copulas and applications to risk management Paul Embrechts, Filip Lindskog and Alexander McNeil -- Prediction of financial downside-risk with heavy-tailed conditional distributions Stefan Mittnik and Marc S. Paolella -- Stable non-Gaussian models for credit risk management Bernhard Martin, Svetlozar T. Rachev and Eduardo S. Schwartz -- Multifactor stochastic variance models in risk management : maximum entropy approach and Lévy processes Alexander Levin and Alexander TchernitseMo dellingodelling the term structure of monetary rates Luisa Izzi -- Asset liability management : a review and some new results in the presence of heavy tails Yesim Tokat, Svetlozar T. Rachev and Eduardo S. Schwartz -- Portfolio choice theory with non-Gaussian distributed returns Sergio Ortobelli [and others] -- Portfolio modeling with heavy tailed random vectors Mark M. Meerschaert and Hans-Peter Scheffler -- Long range dependence in heavy tailed stochastic processes Borjana Racheva-Iotova and Gennaday Samorodnitsky. - The Handbooks in Finance are intended to be a definitive source for comprehensive and accessible information in the field of finance. Each individual volume in the series should present an accurate self-contained survey of a sub-field of finance, suitable for use by finance and economics professors and lecturers, professional researchers, graduate students and as a teaching supplement. The goal is to have a broad group of outstanding volumes in various areas of finance. The Handbook of Heavy Tailed Distributions in Finance is the first handbook to be published in this series. This volume presents current research focusing on heavy tailed distributions in finance. The contributions cover methodological issues, i.e., probabilistic, statistical and econometric modeling under non- Gaussian assumptions, as well as the applications of the stable and other non -Gaussian models in finance and risk management
Includes bibliographical references and indexes. - Print version record
Print version record
Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002
Online-Ausg. [S.l.] : HathiTrust Digital Library
Brendan O. Bradley and Murad S. Taqqu: Heavy tails in finance for independent or multifractal price incrementsBenoit B. MandelbrotFinancial risk and heavy tails
John P. Nolan: Modeling financial data with stable distributions
Tomasz J. Kozubowski, Anna K. Panorska and Svetlozar T. Rachev: Statistical issues in modeling multivariate stable portfolios
Wolfgang J. Runggaldier: Jump-diffusion models
Bo Martin Bibby and Michael Sørensen: Hyperbolic processes in finance
Svetlozar T. Rachev, Eduardo S. Schwartz and Irina Khindanova: Stable modeling of market and credit value at risk
Paul Embrechts, Filip Lindskog and Alexander McNeil: Mo delling dependence with copulas and applications to risk management
Stefan Mittnik and Marc S. Paolella: Prediction of financial downside-risk with heavy-tailed conditional distributions
Bernhard Martin, Svetlozar T. Rachev and Eduardo S. Schwartz: Stable non-Gaussian models for credit risk management
Alexander Levin and Alexander TchernitseMo dellingodelling the term structure of monetary rates: Multifactor stochastic variance models in risk management : maximum entropy approach and Lévy processes
Yesim Tokat, Svetlozar T. Rachev and Eduardo S. Schwartz: Asset liability management : a review and some new results in the presence of heavy tails
Sergio Ortobelli ... [et al.]: Portfolio choice theory with non-Gaussian distributed returns
Mark M. Meerschaert and Hans-Peter Scheffler: Portfolio modeling with heavy tailed random vectors
Borjana Racheva-Iotova and Gennaday Samorodnitsky.: Long range dependence in heavy tailed stochastic processes