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Viac informácií o knihe Mathematical and Statistical Methods for Actuarial Sciences and Finance

• Parametre knihy
• Anotácia kniha
• Obľúbené z iného súdka

Nákupom získate 345 bodov

Anotácia knihy

The interaction between mathematicians and statisticians reveals to be an effective approach for dealing with actuarial, insurance and financial problems, both in an academic and in an operative perspective. The international conference MAF 2008, held at the University Ca Foscari of Venezia (Italy) in 2008, had precisely this purpose, and the collection here published gathers a selection of about the one hundred papers presented at the conference and successively referred and reviewed to this aim. They cover a wide variety of subjects in actuarial, insurance and financial fields, all treated in light of the successful cooperation between the two quantitative approaches. The subjects considered in the book are: mathematical models for actuarial sciences and insurance (namely: demographic risk; management of actuarial risks; management in insurance business; solvency-based approaches); mathematical models for finance (namely: energy markets; fund and portfolio management; methods for derivative pricing; risk and volatility models); statistical models in finance (namely: artificial neural networks; clustering techniques; kernel-based and robust estimation methods; multivariate methods for the analysis of financial markets; non-standard probabilistic models). The book is mainly addressed to academicians, practitioners, professionals and researchers.

Parametre knihy

Zaradenie knihy Knihy po anglicky Economics, finance, business & management Economics Macroeconomics

• Celý názov: Mathematical and Statistical Methods for Actuarial Sciences and Finance
• Autor: Marco Corazza, Claudio Pizzi
• Jazyk: Angličtina
• Väzba: Pevná
• Počet strán: 314
• EAN: 9788847014800
• ISBN: 8847014808
• ID: 01966921
• Nakladateľ: Springer Verlag
• Hmotnosť: 664 g
• Rozmery: 241 × 160 × 22 mm
• Dátum vydania: 01. November 2009

Obľúbené z iného súdka

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