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The interaction between mathematicians and statisticians has been shown to be an e?ective approach for dealing with actuarial, insurance and ?nancial problems, both from an academic perspective and from an operative one. The collection of original papers presented in this volume pursues precisely this purpose. It covers a wide variety of subjects in actuarial, insurance and ?nance ?elds, all treated in the light of the successful cooperation between the above two quantitative approaches.
The papers published in this volume present theoretical and methodological contributions and their applications to real contexts. With respect to the theoretical and methodological contributions, some of the considered areas of investigation are: actuarial models; alternative testing approaches; behavioral ?nance; clustering techniques; coherent and non-coherent risk measures; credit scoring approaches; data envelopment analysis; dynamic stochastic programming; ?nancial contagion models; ?nancial ratios; intelligent ?nancial trading systems; mixture normality approaches; Monte Carlo-based methods; multicriteria methods; nonlinear parameter estimation techniques; nonlinear threshold models; particle swarm optimization; performance measures; portfolio optimization; pricing methods for structured and non-structured derivatives; risk management; skewed distribution analysis; solvency analysis; stochastic actuarial valuation methods; variable selection models; time series analysis tools. As regards the applications, they are related to real problems associated, among the others, to: banks; collateralized fund obligations; credit portfolios; de?ned bene?t pension plans; double-indexed pension annuities; ef?cient-market hypothesis; exchange markets; ?nancial time series; ?rms; hedge funds; non-life insurance companies; returns distributions; socially responsible mutual funds; unit-linked contracts.
This book is aimed at academics, Ph.D. students, practitioners, professionals and researchers. But it will also be of interest to readers with some quantitative background knowledge.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
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The interaction between mathematicians and statisticians has been shown to be an e?ective approach for dealing with actuarial, insurance and ?nancial problems, both from an academic perspective and from an operative one. The collection of original papers presented in this volume pursues precisely this purpose. It covers a wide variety of subjects in actuarial, insurance and ?nance ?elds, all treated in the light of the successful cooperation between the above two quantitative approaches.
The papers published in this volume present theoretical and methodological contributions and their applications to real contexts. With respect to the theoretical and methodological contributions, some of the considered areas of investigation are: actuarial models; alternative testing approaches; behavioral ?nance; clustering techniques; coherent and non-coherent risk measures; credit scoring approaches; data envelopment analysis; dynamic stochastic programming; ?nancial contagion models; ?nancial ratios; intelligent ?nancial trading systems; mixture normality approaches; Monte Carlo-based methods; multicriteria methods; nonlinear parameter estimation techniques; nonlinear threshold models; particle swarm optimization; performance measures; portfolio optimization; pricing methods for structured and non-structured derivatives; risk management; skewed distribution analysis; solvency analysis; stochastic actuarial valuation methods; variable selection models; time series analysis tools. As regards the applications, they are related to real problems associated, among the others, to: banks; collateralized fund obligations; credit portfolios; de?ned bene?t pension plans; double-indexed pension annuities; ef?cient-market hypothesis; exchange markets; ?nancial time series; ?rms; hedge funds; non-life insurance companies; returns distributions; socially responsible mutual funds; unit-linked contracts.
This book is aimed at academics, Ph.D. students, practitioners, professionals and researchers. But it will also be of interest to readers with some quantitative background knowledge.
Dalla quarta di copertina
The interaction between mathematicians and statisticians has been shown to be an e?ective approach for dealing with actuarial, insurance and ?nancial problems, both from an academic perspective and from an operative one. The collection of original papers presented in this volume pursues precisely this purpose. It covers a wide variety of subjects in actuarial, insurance and ?nance ?elds, all treated in the light of the successful cooperation between the above two quantitative approaches.
The papers published in this volume present theoretical and methodological contributions and their applications to real contexts. With respect to the theoretical and methodological contributions, some of the considered areas of investigation are: actuarial models; alternative testing approaches; behavioral ?nance; clustering techniques; coherent and non-coherent risk measures; credit scoring approaches; data envelopment analysis; dynamic stochastic programming; ?nancial contagion models; ?nancial ratios; intelligent ?nancial trading systems; mixture normality approaches; Monte Carlo-based methods; multicriteria methods; nonlinear parameter estimation techniques; nonlinear threshold models; particle swarm optimization; performance measures; portfolio optimization; pricing methods for structured and non-structured derivatives; risk management; skewed distribution analysis; solvency analysis; stochastic actuarial valuation methods; variable selection models; time series analysis tools. As regards the applications, they are related to real problems associated, among the others, to: banks; collateralized fund obligations; credit portfolios; de?ned bene?t pension plans; double-indexed pension annuities; ef?cient-market hypothesis; exchange markets; ?nancial time series; ?rms; hedge funds; non-life insurance companies; returns distributions; socially responsible mutual funds; unit-linked contracts.
This book is aimed at academics, Ph.D. students, practitioners, professionals and researchers. But it will also be of interest to readers with some quantitative background knowledge.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
- EditoreSpringer Nature
- Data di pubblicazione2013
- ISBN 10 3319024981
- ISBN 13 9783319024981
- RilegaturaCopertina rigida
- LinguaInglese
- Numero di pagine313
- RedattoreCorazza Marco, Pizzi Claudio
- Contatto del produttorenon disponibile
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Mathematical and Statistical Methods for Actuarial Sciences and Finance
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The interaction between mathematicians and statisticians has been shown to be an e ective approach for dealing with actuarial, insurance and financial problems, both from an academic perspective and from an operative one. The collection of original papers presented in this volume pursues precisely this purpose. It covers a wide variety of subjects in actuarial, insurance and finance fields, all treated in the light of the successful cooperation between the above two quantitative approaches. The papers published in this volume present theoretical and methodological contributions and their applications to real contexts. With respect to the theoretical and methodological contributions, some of the considered areas of investigation are: actuarial models; alternative testing approaches; behavioral finance; clustering techniques; coherent and non-coherent risk measures; credit scoring approaches; data envelopment analysis; dynamic stochastic programming; financial contagion models; financial ratios; intelligent financial trading systems; mixture normality approaches; Monte Carlo-based methods; multicriteria methods; nonlinear parameter estimation techniques; nonlinear threshold models; particle swarm optimization; performance measures; portfolio optimization; pricing methods for structured and non-structured derivatives; risk management; skewed distribution analysis; solvency analysis; stochastic actuarial valuation methods; variable selection models; time series analysis tools. As regards the applications, they are related to real problems associated, among the others, to: banks; collateralized fund obligations; credit portfolios; defined benefit pension plans; double-indexed pension annuities; efficient-market hypothesis; exchange markets; financial time series; firms; hedge funds; non-life insurance companies; returns distributions; socially responsible mutual funds; unit-linked contracts. This book is aimed at academics, Ph.D. students, practitioners, professionals and researchers. But it will also be of interest to readers with some quantitative background knowledge. 324 pp. Englisch. Codice articolo 9783319024981
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The interaction between mathematicians and statisticians has been shown to be an e ective approach for dealing with actuarial, insurance and financial problems, both from an academic perspective and from an operative one. The collection of original papers presented in this volume pursues precisely this purpose. It covers a wide variety of subjects in actuarial, insurance and finance fields, all treated in the light of the successful cooperation between the above two quantitative approaches. The papers published in this volume present theoretical and methodological contributions and their applications to real contexts. With respect to the theoretical and methodological contributions, some of the considered areas of investigation are: actuarial models; alternative testing approaches; behavioral finance; clustering techniques; coherent and non-coherent risk measures; credit scoring approaches; data envelopment analysis; dynamic stochastic programming; financial contagion models; financial ratios; intelligent financial trading systems; mixture normality approaches; Monte Carlo-based methods; multicriteria methods; nonlinear parameter estimation techniques; nonlinear threshold models; particle swarm optimization; performance measures; portfolio optimization; pricing methods for structured and non-structured derivatives; risk management; skewed distribution analysis; solvency analysis; stochastic actuarial valuation methods; variable selection models; time series analysis tools. As regards the applications, they are related to real problems associated, among the others, to: banks; collateralized fund obligations; credit portfolios; defined benefit pension plans; double-indexed pension annuities; efficient-market hypothesis; exchange markets; financial time series; firms; hedge funds; non-life insurance companies; returns distributions; socially responsible mutual funds; unit-linked contracts. This book is aimed at academics, Ph.D.students, practitioners, professionals and researchers. But it will also be of interest to readers with some quantitative background knowledge. Codice articolo 9783319024981
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Buch. Condizione: Neu. Neuware -The interaction between mathematicians and statisticians has been shown to be an e¿ective approach for dealing with actuarial, insurance and ¿nancial problems, both from an academic perspective and from an operative one. The collection of original papers presented in this volume pursues precisely this purpose. It covers a wide variety of subjects in actuarial, insurance and ¿nance ¿elds, all treated in the light of the successful cooperation between the above two quantitative approaches.The papers published in this volume present theoretical and methodological contributions and their applications to real contexts. With respect to the theoretical and methodological contributions, some of the considered areas of investigation are: actuarial models; alternative testing approaches; behavioral ¿nance; clustering techniques; coherent and non-coherent risk measures; credit scoring approaches; data envelopment analysis; dynamic stochastic programming; ¿nancial contagion models; ¿nancial ratios; intelligent ¿nancial trading systems; mixture normality approaches; Monte Carlo-based methods; multicriteria methods; nonlinear parameter estimation techniques; nonlinear threshold models; particle swarm optimization; performance measures; portfolio optimization; pricing methods for structured and non-structured derivatives; risk management; skewed distribution analysis; solvency analysis; stochastic actuarial valuation methods; variable selection models; time series analysis tools. As regards the applications, they are related to real problems associated, among the others, to: banks; collateralized fund obligations; credit portfolios; de¿ned bene¿t pension plans; double-indexed pension annuities; ef¿cient-market hypothesis; exchange markets; ¿nancial time series; ¿rms; hedge funds; non-life insurance companies; returns distributions; socially responsible mutual funds; unit-linked contracts.This book is aimed at academics, Ph.D.students, practitioners, professionals and researchers. But it will also be of interest to readers with some quantitative background knowledge.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 324 pp. Englisch. Codice articolo 9783319024981
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Mathematical and Statistical Methods for Actuarial Sciences and Finance
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Gebunden. Condizione: New. Contains both mathematical and statistical issuesPresents the most advanced research results in actuarial sciences, insurance and financeContains theoretical and applicative perspectivesThe interaction between mathematicians and . Codice articolo 4496454
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