Isbn: 9781849965996 - financial modeling under non-gaussian distributions (springer finance) (4 Ergebnisse)

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  • Sprache: Englisch

    Verlag: Springer, 2010

    1849965994 / 9781849965996

    Serie: Buch 25 von 53 - Springer Finance

    • Softcover

    Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections

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    Zustand: Neu

    EUR 140,97

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    Zustand: New. In English.

  • Sprache: Englisch

    Verlag: Springer London, 2010

    1849965994 / 9781849965996

    Serie: Buch 25 von 53 - Springer Finance

    • Softcover

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

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    Taschenbuch. Zustand: Sehr gut. Gebraucht - Sehr gut SG - leichte Beschädigungen oder Verschmutzungen, ungelesenes Mängelexemplar, gestempelt - Practitioners and researchers who have handled financial market data know that asset returns do not behave according to the bell-shaped curve, associated with the Gaussian or normal distribution. Indeed, the use of Gaussian models when the asset return distributions are not normal could lead to a wrong choice of portfolio, the underestimation of extreme losses or mispriced derivative products. Consequently, non-Gaussian models and models based on processes with jumps are gaining popularity among financial market practitioners.Non-Gaussian distributions are the key theme of this book which addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. One of the main aims is to bridge the gap between the theoretical developments and the practical implementations of what many users and researchers perceive as 'sophisticated' models or black boxes. The book is written for non-mathematicians who want to model financial market prices so the emphasis throughout is on practice. There are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series, such as exchange and interest rates. The authors have taken care to make the material accessible to anyone with a basic knowledge of statistics, calculus and probability, while at the same time preserving the mathematical rigor and complexity of the original models. This book will be an essential reference for practitioners in the finance industry, especially those responsible for managing portfolios and monitoring financial risk, but it will also be useful for mathematicians who want to know more about how their mathematical tools are applied in finance, and as a text for advanced courses in empirical finance; financial econometrics and financial derivatives This book examines non-Gaussian distributions. It addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The book is written for non-mathematicians who want to model financial market prices so the emphasis throughout is on practice. There are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series.

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    Sprache: Englisch

    Verlag: Springer, 2010

    1849965994 / 9781849965996

    Serie: Buch 25 von 53 - Springer Finance

    • Softcover

    Anbieter: preigu, Osnabrück, Deutschlandpreigu

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    Taschenbuch. Zustand: Neu. Financial Modeling Under Non-Gaussian Distributions | Eric Jondeau (u. a.) | Taschenbuch | xviii | Englisch | 2010 | Springer | EAN 9781849965996 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Sprache: Englisch

    Verlag: Springer, Springer, 2010

    1849965994 / 9781849965996

    Serie: Buch 25 von 53 - Springer Finance

    • Softcover

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

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    Zustand: Neu

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    Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Non-Gaussian distributions are the key theme of this book which addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The aim is to bridge the gap between theoretical developments and the practical implementations of what many users and researchers perceive as 'sophisticated' models. The emphasis throughout is on practice: there are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series, such as exchange and interest rates. This book will be an essential reference for practitioners in the finance industry, especially those responsible for managing portfolios and monitoring financial risk, but it will also be useful for mathematicians who want to know more about how their mathematical tools are applied in finance, and as a text for advanced courses in empirical finance; financial econometrics and financial derivatives.