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Data Science and Risk Analytics in Finance and Insurance (Chapman and Hall/CRC Financial Mathematics Series) by Tze Leung Lai, Haipeng Xing is a nonfiction available to read on EtoBox.

What is Data Science and Risk Analytics in Finance and Insurance (Chapman and Hall/CRC Financial Mathematics Series) about?

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 facilita

Who reads Data Science and Risk Analytics in Finance and Insurance (Chapman and Hall/CRC Financial Mathematics Series)?

Author

Tze Leung Lai, Haipeng Xing

Publisher

CRC Press Inc

Published

2024

Language

EN

ISBN

9781315117041

Category

nonfiction

Subjects

Mathematics, Finance, Reference