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… Mehr…
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. TOC:Part I: Financial Markets and Financial Time Series.- Introduction. Statistical Properties of Financial Market Data. Functioning of Financial Markets and Theoretical Models for Returns. Part II: Econometric Modeling of Asset Returns.- Modeling Volatility. Modeling Higher Moments. Modeling Correlation. Extreme Value Theory. Part III: Applications of Non-Gaussian Econometrics.- Risk Management and VaR. Portfolio Allocation. Part IV: Option Pricing with Non-Gaussian Returns.-Fundamentals of Option Pricing. Non-Structural Option Pricing. Structural Option Pricing. Part V: Appendices on Option Pricing Mathematics.- Brownian Motion and Stochastic Calculus. Martingale and Changing Measure. Characteristic Functions and Fourier Transforms. Jump Processes.- References.- Index. eBook Eric Jondeau#Michael Rockinger#Ser-Huang Poon PDF, Springer, 05.04.2007, Springer, 2007<
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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… Mehr…
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. TOC:Part I: Financial Markets and Financial Time Series.- Introduction. Statistical Properties of Financial Market Data. Functioning of Financial Markets and Theoretical Models for Returns. Part II: Econometric Modeling of Asset Returns.- Modeling Volatility. Modeling Higher Moments. Modeling Correlation. Extreme Value Theory. Part III: Applications of Non-Gaussian Econometrics.- Risk Management and VaR. Portfolio Allocation. Part IV: Option Pricing with Non-Gaussian Returns.-Fundamentals of Option Pricing. Non-Structural Option Pricing. Structural Option Pricing. Part V: Appendices on Option Pricing Mathematics.- Brownian Motion and Stochastic Calculus. Martingale and Changing Measure. Characteristic Functions and Fourier Transforms. Jump Processes.- References.- Index. eBook Ser-Huang Poon#Eric Jondeau#Michael Rockinger 05.04.2007, Springer, Springer<
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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… Mehr…
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. Books > Mathematics eBook, Springer Shop<
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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… Mehr…
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., Springer<
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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… Mehr…
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. TOC:Part I: Financial Markets and Financial Time Series.- Introduction. Statistical Properties of Financial Market Data. Functioning of Financial Markets and Theoretical Models for Returns. Part II: Econometric Modeling of Asset Returns.- Modeling Volatility. Modeling Higher Moments. Modeling Correlation. Extreme Value Theory. Part III: Applications of Non-Gaussian Econometrics.- Risk Management and VaR. Portfolio Allocation. Part IV: Option Pricing with Non-Gaussian Returns.-Fundamentals of Option Pricing. Non-Structural Option Pricing. Structural Option Pricing. Part V: Appendices on Option Pricing Mathematics.- Brownian Motion and Stochastic Calculus. Martingale and Changing Measure. Characteristic Functions and Fourier Transforms. Jump Processes.- References.- Index. eBook Eric Jondeau#Michael Rockinger#Ser-Huang Poon PDF, Springer, 05.04.2007, Springer, 2007<
Nr. 24484547. Versandkosten:, Sofort per Download lieferbar, DE. (EUR 0.00)
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… Mehr…
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. TOC:Part I: Financial Markets and Financial Time Series.- Introduction. Statistical Properties of Financial Market Data. Functioning of Financial Markets and Theoretical Models for Returns. Part II: Econometric Modeling of Asset Returns.- Modeling Volatility. Modeling Higher Moments. Modeling Correlation. Extreme Value Theory. Part III: Applications of Non-Gaussian Econometrics.- Risk Management and VaR. Portfolio Allocation. Part IV: Option Pricing with Non-Gaussian Returns.-Fundamentals of Option Pricing. Non-Structural Option Pricing. Structural Option Pricing. Part V: Appendices on Option Pricing Mathematics.- Brownian Motion and Stochastic Calculus. Martingale and Changing Measure. Characteristic Functions and Fourier Transforms. Jump Processes.- References.- Index. eBook Ser-Huang Poon#Eric Jondeau#Michael Rockinger 05.04.2007, Springer, Springer<
Nr. 24484547. Versandkosten:, Sofort per Download lieferbar, zzgl. Versandkosten. (EUR 17.05)
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… Mehr…
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. Books > Mathematics eBook, Springer Shop<
new in stock. Versandkosten:zzgl. Versandkosten. (EUR 0.00)
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… Mehr…
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., Springer<
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Buch in der Datenbank seit 2010-10-12T17:58:19+02:00 (Berlin) Detailseite zuletzt geändert am 2023-10-07T07:05:16+02:00 (Berlin) ISBN/EAN: 1846286964
ISBN - alternative Schreibweisen: 1-84628-696-4, 978-1-84628-696-4 Alternative Schreibweisen und verwandte Suchbegriffe: Autor des Buches: huang, rockinger, rocking Titel des Buches: springer, gauss, financial modeling, huang
Daten vom Verlag:
Autor/in: Eric Jondeau Titel: Springer Finance; Financial Modeling Under Non-Gaussian Distributions Verlag: Springer; Springer London 541 Seiten Erscheinungsjahr: 2007-04-05 London; GB Sprache: Englisch 219,00 € (DE)
EA; E107; eBook; Nonbooks, PBS / Mathematik/Sonstiges; Angewandte Mathematik; Verstehen; Stochastic calculus; Time series; calculus; correlation; econometrics; function; mathematics; statistics; quantitative finance; B; Mathematics in Business, Economics and Finance; Statistics in Business, Management, Economics, Finance, Insurance; Econometrics; Mathematics and Statistics; Wirtschaftswissenschaft, Finanzen, Betriebswirtschaft und Management; Wahrscheinlichkeitsrechnung und Statistik; Ökonometrie und Wirtschaftsstatistik; BB
Financial Markets and Financial Time Series.- Statistical Properties of Financial Market Data.- Functioning of Financial Markets and Theoretical Models for Returns.- Econometric Modeling of Asset Returns.- Modeling Volatility.- Modeling Higher Moments.- Modeling Correlation.- Extreme Value Theory.- Applications of Non-Gaussian Econometrics.- Risk Management and VaR.- Portfolio Allocation.- Option Pricing with Non-Gaussian Returns.- Fundamentals of Option Pricing.- Non-structural Option Pricing.- Structural Option Pricing.- Appendices on Option Pricing Mathematics.- Brownian Motion and Stochastic Calculus.- Martingale and Changing Measure.- Characteristic Functions and Fourier Transforms.- Jump Processes.- Lévy Processes.
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