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Data Science and Risk Analytics in Finance and Insurance. 金融と保険におけるデータサイエンスとリスク分析
・ISBN 978-1-4398-3948-5 cloth GB£ 83.99
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電子版あり 大学・学術機関向け電子ブック（eBook）ISBN 978-1-315-11704-1
| 著者・編者 | Lai, Tze Leung / Xing, Haipeng, |
|---|---|
| シリーズ | Chapman & Hall/CRC Financial Mathematics Series |
| 出版社 | (CRC Pr., US) |
| 出版年月 | 2024 |
| ページ数 | 366 pp. |
| 言語 | ENG |
| ニュース番号 | ＜610-485 610-L168＞ |
解説
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.