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Mathematical and statistical methods...

Corazza, Marco.

Mathematical and statistical methods for actuarial sciences and FinanceMAF 2018 /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Mathematical and statistical methods for actuarial sciences and Financeedited by Marco Corazza ... [et al.].
Reminder of title:	MAF 2018 /
other author:	Corazza, Marco.
Published:	Cham :Springer International Publishing :2018.
Description:	xvi, 518 p. :digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Mathematics.
Online resource:	http://dx.doi.org/10.1007/978-3-319-89824-7
ISBN:	9783319898247$q(electronic bk.)

Mathematical and statistical methods for actuarial sciences and FinanceMAF 2018 /
Mathematical and statistical methods for actuarial sciences and FinanceMAF 2018 /[electronic resource] :edited by Marco Corazza ... [et al.]. - Cham :Springer International Publishing :2018. - xvi, 518 p. :digital ;24 cm.

The interaction between mathematicians, statisticians and econometricians working in actuarial sciences and finance is producing numerous meaningful scientific results. This volume introduces new ideas, in the form of four-page papers, presented at the international conference Mathematical and Statistical Methods for Actuarial Sciences and Finance (MAF), held at Universidad Carlos III de Madrid (Spain), 4th-6th April 2018. The book covers a wide variety of subjects in actuarial science and financial fields, all discussed in the context of the cooperation between the three quantitative approaches. The topics include: actuarial models; analysis of high frequency financial data; behavioural finance; carbon and green finance; credit risk methods and models; dynamic optimization in finance; financial econometrics; forecasting of dynamical actuarial and financial phenomena; fund performance evaluation; insurance portfolio risk analysis; interest rate models; longevity risk; machine learning and soft-computing in finance; management in insurance business; models and methods for financial time series analysis, models for financial derivatives; multivariate techniques for financial markets analysis; optimization in insurance; pricing; probability in actuarial sciences, insurance and finance; real world finance; risk management; solvency analysis; sovereign risk; static and dynamic portfolio selection and management; trading systems. This book is a valuable resource for academics, PhD students, practitioners, professionals and researchers, and is also of interest to other readers with quantitative background knowledge.

ISBN: 9783319898247$q(electronic bk.)

Standard No.: 10.1007/978-3-319-89824-7doiSubjects--Topical Terms:

184409
Mathematics.

LC Class. No.: HG8781 / .M384 2018

Dewey Class. No.: 368.01

Mathematical and statistical methods for actuarial sciences and FinanceMAF 2018 /
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245 0 0 $a Mathematical and statistical methods for actuarial sciences and Finance $h [electronic resource] : $b MAF 2018 / $c edited by Marco Corazza ... [et al.].
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300 $a xvi, 518 p. : $b digital ; $c 24 cm.
520 $a The interaction between mathematicians, statisticians and econometricians working in actuarial sciences and finance is producing numerous meaningful scientific results. This volume introduces new ideas, in the form of four-page papers, presented at the international conference Mathematical and Statistical Methods for Actuarial Sciences and Finance (MAF), held at Universidad Carlos III de Madrid (Spain), 4th-6th April 2018. The book covers a wide variety of subjects in actuarial science and financial fields, all discussed in the context of the cooperation between the three quantitative approaches. The topics include: actuarial models; analysis of high frequency financial data; behavioural finance; carbon and green finance; credit risk methods and models; dynamic optimization in finance; financial econometrics; forecasting of dynamical actuarial and financial phenomena; fund performance evaluation; insurance portfolio risk analysis; interest rate models; longevity risk; machine learning and soft-computing in finance; management in insurance business; models and methods for financial time series analysis, models for financial derivatives; multivariate techniques for financial markets analysis; optimization in insurance; pricing; probability in actuarial sciences, insurance and finance; real world finance; risk management; solvency analysis; sovereign risk; static and dynamic portfolio selection and management; trading systems. This book is a valuable resource for academics, PhD students, practitioners, professionals and researchers, and is also of interest to other readers with quantitative background knowledge.
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