Articles liés à Data Science and Risk Analytics in Finance and Insurance

Data Science and Risk Analytics in Finance and Insurance - Couverture rigide

Livre 66 sur 71: Chapman and Hall/CRC Financial Mathematics

Lai, Tze Leung; Xing, Haipeng

 
9781439839485: Data Science and Risk Analytics in Finance and Insurance
Couverture rigide
ISBN 10 : 1439839484 ISBN 13 : 9781439839485
Editeur : CRC Press, 2024

Synopsis

This book presents statistics and data science methods for risk analytics in quantitative finance and insurance. Part I covers the background, financial models, and data analytical methods for market risk, credit risk, and operational risk in financial instruments, as well as models of risk premium and insolvency in insurance contracts. Part II provides an overview of machine learning (including supervised, unsupervised, and reinforcement learning), Monte Carlo simulation, and sequential analysis techniques for risk analytics. In Part III, the book offers a non-technical introduction to four key areas in financial technology: artificial intelligence, blockchain, cloud computing, and big data analytics.

Key Features:

  • Provides a comprehensive and in-depth overview of data science methods for financial and insurance risks.
  • Unravels bandits, Markov decision processes, reinforcement learning, and their interconnections.
  • Promotes sequential surveillance and predictive analytics for abrupt changes in risk factors.
  • Introduces the ABCDs of FinTech: Artificial intelligence, blockchain, cloud computing, and big data analytics.
  • Includes supplements and exercises to facilitate deeper comprehension.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l'auteur

Tze Leung Lai is the Ray Lyman Wilbur Professor and Professor of Statistics at Stanford University. He received the COPSS Presidents' Award in 1983. He has published extensively on sequential statistical analysis and a wide range of applications in the biomedical sciences, engineering, and finance.

Haipeng Xing is a Professor of Applied Mathematics and Statistics at State University of New York, Stony Brook. His research interests include sequential statistical methods and its applications, econometrics, quantitative finance, and recursive methods in macroeconomics.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
CRC Press
Date d'édition
2024
Langue
anglais
ISBN 10 
1439839484
ISBN 13 
9781439839485
Reliure
Relié
Nombre de pages
449
Coordonnées du fabricant
non disponible
Personne responsable
GPSR Kontakt
gpsr@libri.de

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