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Machine Learning for Financial Risk Mana Abdullah Karasan Paperback
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Item specifics
- Condition
- Book Title
- O'Reilly Media
- ISBN
- 9781492085256
- Subject Area
- Computers, Business & Economics
- Publication Name
- Machine Learning for Financial Risk Management with Python : Algorithms for Modeling Risk
- Publisher
- O'reilly Media, Incorporated
- Item Length
- 9.1 in
- Subject
- Computer Science, Economics / General, Insurance / Risk Assessment & Management
- Publication Year
- 2022
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Item Height
- 0.8 in
- Item Weight
- 20.5 Oz
- Item Width
- 7 in
- Number of Pages
- 331 Pages
About this product
Product Identifiers
Publisher
O'reilly Media, Incorporated
ISBN-10
1492085251
ISBN-13
9781492085256
eBay Product ID (ePID)
6050406798
Product Key Features
Number of Pages
331 Pages
Publication Name
Machine Learning for Financial Risk Management with Python : Algorithms for Modeling Risk
Language
English
Publication Year
2022
Subject
Computer Science, Economics / General, Insurance / Risk Assessment & Management
Type
Textbook
Subject Area
Computers, Business & Economics
Format
Trade Paperback
Dimensions
Item Height
0.8 in
Item Weight
20.5 Oz
Item Length
9.1 in
Item Width
7 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2023-275992
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
658.155
Synopsis
Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Python-based machine learning and deep learning models for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to replace traditional financial risk models with ML models. Author Abdullah Karasan helps you explore the theory behind financial risk modeling before diving into practical ways of employing ML models in modeling financial risk using Python. With this book, you will: Review classical time series applications and compare them with deep learning models Explore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learning Improve market risk models (VaR and ES) using ML techniques and including liquidity dimension Develop a credit risk analysis using clustering and Bayesian approaches Capture different aspects of liquidity risk with a Gaussian mixture model and Copula model Use machine learning models for fraud detection Predict stock price crash and identify its determinants using machine learning models
LC Classification Number
HD61
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Seller feedback (264)
- 7***w- Feedback left by buyer.Past monthVerified purchaseItem arrived quickly, well-packed, and as described. Great seller!
- m***r (324)- Feedback left by buyer.Past 6 monthsVerified purchaseWell packed, reasonably priced and arrived prestine as described.Dian Hanson's: The History of Men's Magazines. Vol. 6: 1970s Under the Counter d (#387445972703)
- o***1 (176)- Feedback left by buyer.Past monthVerified purchaseGreat book. Just as described. Packed well and promptly shipped.