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| LEADER |
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|a (OCoLC)on1450930052
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| 020 |
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|a 9781315117041
|q (electronic bk.)
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| 020 |
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|a 1315117045
|q (electronic bk.)
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|a 9781351633826
|q (electronic bk. : Mobipocket)
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| 020 |
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|a 1351633821
|q (electronic bk. : Mobipocket)
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|a 9781439839492
|q (electronic bk. : PDF)
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| 020 |
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|a 1439839492
|q (electronic bk. : PDF)
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| 020 |
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|a 9781351643252
|q (electronic bk. : EPUB)
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| 020 |
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|a 1351643258
|q (electronic bk. : EPUB)
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| 020 |
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|z 9781032850498
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| 020 |
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|z 9781439839485
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| 024 |
7 |
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|a 10.1201/9781315117041
|2 doi
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| 035 |
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|a (OCoLC)1450930052
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| 037 |
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|a 9781315117041
|b Taylor & Francis
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| 050 |
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4 |
|a HG106
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| 072 |
|
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|a BUS
|x 027000
|2 bisacsh
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|a KCHS
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|a 332.072/7
|2 23/eng/20240815
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| 049 |
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|a TXAM
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| 100 |
1 |
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|a Lai, T. L.,
|e author.
|u Stanford University, California, USA.
|1 https://id.oclc.org/worldcat/entity/E39PBJtX6Xvxp3pWR6jPBcCmh3
|
| 245 |
1 |
0 |
|a Data science and risk analytics in finance and insurance /
|c Tze Leung Lai and Haipeng Xing.
|
| 250 |
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|a First edition.
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| 264 |
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1 |
|a Boca Raton :
|b CRC Press,
|c 2025.
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| 300 |
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|a 1 online resource (xiv, 366 pages).
|
| 336 |
|
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 490 |
1 |
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|a Chapman & Hall/CRC financial mathematics series
|
| 505 |
0 |
|
|a PrefacePart 1: Background and Basic Analytics 1. Risk management and regulation2. Basic concepts and methods in risk management3. Financial derivatives and their pricing theory4. Insurance risk and credibility theoryPart 2: Advanced Data and Risk Analytics 5. Supervised and unsupervised learning6. Bandit, Markov decision process and reinforcement learning7. Monte Carlo methods and rare event analytics8. Surveillance and predictive analyticsPart 3: Data and Risk Analytics in FinTech 9. FinTech ABCD and analyticsBibliographyIndex
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| 520 |
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|a 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.
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| 521 |
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|a Researchers and graduate students in statistics, finance, and economics.
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| 545 |
0 |
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|a 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.
|
| 588 |
0 |
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|a Online resource; title from PDF title page (Taylor & Francis, viewed August 15, 2024).
|
| 650 |
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0 |
|a Finance
|x Mathematical models.
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| 650 |
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0 |
|a Finance
|x Statistical methods.
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| 650 |
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|a Insurance
|x Data processing.
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| 650 |
|
6 |
|a Finances
|x Modèles mathématiques.
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| 650 |
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6 |
|a Finances
|x Méthodes statistiques.
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| 650 |
|
6 |
|a Assurance
|x Informatique.
|
| 650 |
|
7 |
|a BUSINESS & ECONOMICS / Finance
|2 bisacsh
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| 655 |
|
7 |
|a Electronic books.
|2 local
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| 700 |
1 |
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|a Xing, Haipeng,
|e author.
|d SUNY, Stony Brook, New York, USA
|
| 710 |
2 |
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|a Taylor & Francis
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| 830 |
|
0 |
|a Chapman & Hall/CRC financial mathematics series.
|
| 856 |
4 |
0 |
|u http://proxy.library.tamu.edu/login?url=https://www.taylorfrancis.com/books/9781315117041
|z Connect to the full text of this electronic book
|t 0
|
| 955 |
|
|
|a Taylor and Francis MATHnetBASE
|
| 994 |
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|a 92
|b TXA
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| 952 |
f |
f |
|a Texas A&M University
|b College Station
|c Electronic Resources
|d Available Online
|t 0
|e HG106
|h Library of Congress classification
|
| 998 |
f |
f |
|a HG106
|t 0
|l Available Online
|